Sweet Streams are Made of This: The System Engineer’s View on Energy Efficiency in Video Communications (Preprint) - Herglotz, Christian; Kränzler, Matthias; Schober, Robert; Kaup, André (Ieee Circuits and Systems Magazine, 2023)

Switchable Motion Models for Non-Block-Based Inter Prediction in Learning-Based Video Coding - Brand, Fabian; Seiler, Jürgen; Kaup, André (Picture Coding Symposium (PCS), 2021)
Most state-of-the-art video coders rely on a block structure. For inter-frame prediction, motion vectors are transmitted per block. For example in VVC, the coder can choose between a translational or an affine motion model on a block level, depending on the content. In non-block-based coding, which is on the rise since the development of end-to-end learning based image compression, the motion vectors have to be transmitted differently. Due to the missing inherent block structure, switching between different motion models presents a challenge, but also an opportunity. In this paper, we propose an alternative approach to efficiently signal additional information regarding the motion model to improve the quality of the motion compensated image. Using our methods, we are able to increase the quality of the prediction image in our scenario by 0.40 dB on average and by up to 0.88 dB for sequences with strong and complex motion at the same rate.<br

Symbolic Analysis of Quantization Errors in Transform and Subband Coders - Heinle, Frank; Lerzer, J.; Runze, Gerhard (Proc. International Conference on Digital Signal Processing, 1997)
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Synchronization of acoustic sensors for distributed ad-hoc audio networks and its use for blind source separation - Wehr, Stefan; Kellermann, Walter; Lienhart, R.; Kozintsev, I. (IEEE Sixth International Symposium on Multimedia Software Engineering, MSE 2004, 2004)
Advanced computing devices equipped with various wired and wireless network capabilities, built-in micro-phones and audio capture devices are becoming increasingly popular. At the same time, sophisticated signal processing algorithms for hands-free acoustic human-machine interfaces are being developed. Those algorithms are currently restricted to dedicated audio hardware, in part because they require perfectly synchronized audio data. Naive attempts to use the available audio devices for microphone array processing in a distributed wireless setting fails due to the algorithms' sensitivity to deviations in the sampling rates of the distributed devices. We propose here a synchronization scheme, which combines the microphones of different spatially distributed computing devices to an acoustic ad-hoc network. The proposed scheme is capable to significantly compensate the sampling rate deviations of the different audio capture devices and we will show that, as an example, blind source separation performs well with the synchronized data of distributed acoustic sensors. © 2004 IEE

Synthesis of ICA-based methods for localization of multiple broadband sound sources - Lombard, Anthony; Zheng, Yuanhang; Kellermann, Walter (36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011, 2011)
In this paper, minimization of the statistical dependence is exploited for acoustic source localization purposes. Originally developed for the separation of signal mixtures, we show that Independent Component Analysis (ICA) can also be successfully applied to localize multiple simultaneously active sound sources, with possibly less sensors than sources. First, the recently proposed Averaged Directivity Pattern (ADP) and State Coherence Transform (SCT) methods are reviewed. Similarities and differences between both approaches are underlined and analyzed, leading to a new method merging elements from both concepts, which we call the Modified ADP (MADP). Since the investigated methods do not suffer from the permutation ambiguity, they can be applied in combination with any narrowband or broadband ICA algorithm, without the need to solve the still challenging permutation issue. Experimental results are presented for speech sources in a reverberant environment. © 2011 IEE
Keywords: BSS; ICA; Localization; microphone array

Synthetic hyperspectral array video database with applications to cross-spectral reconstruction and hyperspectral video coding - Sippel, Frank; Seiler, Jürgen; Kaup, André (Journal of the Optical Society of America A-Optics Image Science and Vision, 2023)
In this paper, a synthetic hyperspectral video database is introduced. Since it is impossible to record ground-truth hyperspectral videos, this database offers the possibility to leverage the evaluation of algorithms in diverse applications. For all scenes, depth maps are provided as well to yield the position of a pixel in all spatial dimensions as well as the reflectance in spectral dimension. Two novel algorithms for two different applications are proposed to prove the diversity of applications that can be addressed by this novel database. First, a cross-spectral image reconstruction algorithm is extended to exploit the temporal correlation between two consecutive frames. The evaluation using this hyperspectral database shows an increase in peak signal-to-noise ratio (PSNR) of up to 5.6 dB dependent on the scene. Second, a hyperspectral video coder is introduced, which extends an existing hyperspectral image coder by exploiting temporal correlation. The evaluation shows rate savings of up to 10% depending on the scen
Keywords: Hyperspectral imaging; Hyperspectral video database; Camera Array

Synthetisches Multicondition-Training zur robusten Erkennung verhallter Sprache - Sehr, Armin; Gress, O.; Kellermann, Walter (Proc. ITG Fachtagung Sprachkommunikation, 2006)
Dieser Beitrag untersucht experimentell die Abhängigkeit der Erkennungsrate eines kontinuierlichen Spracherkenners mit großem Wortschatz von der Nachhallzeit in realen Umgebungen. Zur Verbesserung der Robustheit gegenüber Nachhall wird ein neuartiges, besonders aufwandsgünstiges Trainingsverfahren, das sogenannte synthetischeMulticondition-Training, vorgestellt und mit anderenMethoden des verhallten Trainings verglichen. In diesem Vergleich erreicht das synthetische Multicondition-Training die robustesten Modelle, die in unterschiedlichen Umgebungen und über einen großen Bereich von Nachhallzeiten deutliche Verbesserungen der Erkennungsraten gegenüber unverhalltem Training erzielen. © 2006 V
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System Identification Methods for Refined Fault Detection in LVDC-Microgrids - Strobl, Christian; Schäfer, Maximilian; Rabenstein, Rudolf (International Conference on DC Microgrids (ICDCM), 2019)

SYSTOOL - An online learning tool for signals and systems - Rabenstein, Rudolf (2002 IEEE International Conference on Acoustic, Speech, and Signal Processing, 2002)
SYSTOOL is an online learning tool for real or virtual courses in signals and systems. It provides a collection of Java applets for interactive simulation and visualisation of linear systems. While based on a traditional textbook, SYSTOOL is accessible online though the Virtual University of Bavaria. This article describes structure and content of this learning tool and presents selected modules.

Tackling the Acoustic Front-end for Distant-Talking Automatic Speech Recognition (keynote) - Kellermann, Walter (Conf. Rec. SPS-DARTS 2007, 2007)
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Talbot bands and temporal processing of optical signals - Jahns, J.; Lohmann, Adolf; Bohling, M. (Journal of the European Optical Society: Rapid Publications, 2006)
Talbot’s bands can be observed in one of the diffraction orders of a grating spectrometer with a partially phase-shifted input beam. This experiment has long been considered as a curiosity. Here, we look at it from a new perspective: we discuss the Talbot band experiment as a combination of two kinds of dispersion, refractive and diffractive. This may be of interest for various tasks of temporal optical signal processing such as dispersion management and the shaping of ps/fs-pulses. For this purpose, we demonstrate the use of micromachined optical elements to alter the performance of the classical Talbot band setup. A theoretical description and experimental results are presente
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Talbot- und Montgomery-Selbstabbildung in der optischen Nachrichtentechnik - Jahns, J.; Knuppertz, H.; Lohmann, Adolf (104. Jahrestagung der DGaO, Münster, 2003)
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TanDEM-X Acquisition Planning and DEM Performance in the Third Year of Operation - Schulze, Daniel; Bachmann, Markus; Borla-Tridon, Daniela; Zink, Manfred; Krieger, Gerhard (CSA Advanced SAR Workshop (ASAR), 2013)
TanDEM-X is a spaceborne SAR mission with the goal to derive a global Digital Elevation Model (DEM). The two incorporated satellites fly in a close formation with distances of around 500 m. These small baselines form a single pass bistatic interferometer for accurate DEM acquisitions. The final DEM product will enter a new level of detail and accuracy on a global scale. The absolute height error shall be less than 10 m in a 90% confidence interval at a pixel spacing of 12 m. The vertical height specification for the TanDEM-X mission foresees a 90% point-to-point error of 2 m (4 m) for areas with predominant terrain slopes smaller than 20% (greater than 20%) for a 1^i̧rc by 1^i̧rc cell. This presentation gives an overview about the planning and the actual status of the global DEM acquisition. This includes the acquisition plan after the first two years of operation, i. e. two global coverages, including the acquisitions of the Antarctica and difficult terrain. Also, the actual performance status in terms of absolute and relative height error and the narrow relation between the DEM acquisition planning and the performance evaluation is presented.
DLR Import::2019-04-03
Keywords: TanDEM-X; Synthetic aperture radar; Digital Elevation Model; DEM; Performance; Acquisition Planning

TDOA-based speed of sound estimation for air temperature and room geometry inference - Annibale, Paolo; Filos, Jason; Naylor, Patrick A.; Rabenstein, Rudolf (IEEE Transactions on Audio Speech and Language Processing, 2013)
Spatially distributed acoustic sensors find increasingly many new applications in speech-based human-machine interfaces. One well researched topic is the localization of sound sources from Time Differences Of Arrival (TDOAs) measurements. Typically, the propagation speed of sound is considered a known constant. However due to temperature variations its value is known only up to some uncertainty. This paper exploits TDOA-based localization techniques in order to estimate accurately the actual speed of sound. Experimental results using both simulated and real data demonstrate the feasibility of the proposed method. Furthermore, the practical validation of this work considers two distinct experiments that are aimed at inferring information about enclosed sound fields. The first experiment concerns the calculation of the air temperature from the estimated speed of sound. The second experiment highlights the effects of temperature variations on the inference of the physical location of reflective boundaries of the acoustic enclosure. In the latter case it is shown that the position estimates of the reflective surfaces in a room can be improved when the correct propagation speed is first estimated using this method. © 2012 IEE
Keywords: Acoustic propagation; acoustic sensors; acoustic waves; speed of sound; temperature; time difference of arrival (TDOA)

TDOA estimation for multiple sound sources in noisy and reverberant environments using broadband independent component analysis - Lombard, Anthony; Zheng, Yuanhang; Buchner, Herbert; Kellermann, Walter (IEEE Transactions on Audio Speech and Language Processing, 2011)
In this paper, we show that minimization of the statistical dependence using broadband independent component analysis (ICA) can be successfully exploited for acoustic source localization. As the ICA signal model inherently accounts for the presence of several sources and multiple sound propagation paths, the ICA criterion offers a theoretically more rigorous framework than conventional techniques based on an idealized single-path and single-source signal model. This leads to algorithms which outperform other localization methods, especially in the presence of multiple simultaneously active sound sources and under adverse conditions, notably in reverberant environments. Three methods are investigated to extract the time difference of arrival (TDOA) information contained in the filters of a two-channel broadband ICA scheme. While for the first, the blind system identification (BSI) approach, the number of sources should be restricted to the number of sensors, the other methods, the averaged directivity pattern (ADP) and composite mapped filter (CMF) approaches can be used even when the number of sources exceeds the number of sensors. To allow fast tracking of moving sources, the ICA algorithm operates in block-wise batch mode, with a proportionate weighting of the natural gradient to speed up the convergence of the algorithm. The TDOA estimation accuracy of the proposed schemes is assessed in highly noisy and reverberant environments for two, three, and four stationary noise sources with speech-weighted spectral envelopes as well as for moving real speech sources. © 2011 IEE
Keywords: Acoustic source localization; adaptive filters; independent component analysis; microphone arrays; reverberation; time difference of arrival (TDOA) estimation

Temporal adaptation strategies for spatio-temporal image alignment in inter-sequence error concealment of digital TV - Tröger, Tobias; Kaup, André (2011 18th IEEE International Conference on Image Processing, ICIP 2011, 2011)
In multi-broadcast scenarios, inter-sequence error concealment replaces lost image blocks of digital TV signals with error-free ones of low-resolution reference signals. Although single reference frames are misaligned spatio-temporally, the reconstruction quality is significantly higher than for conventional techniques. However, it can be further increased by reusing the alignment parameters of previous frames in case of misalignment of the current frame. Two strategies are proposed for this temporal adaptation of the alignment parameters either minimizing the additional complexity or maximizing the reconstruction quality. Overall, a gain of up to 5.0 dB PSNR Y is obtained while the computation time does not rise by more than 1.8%. © 2011 IEE

Temporal Error Concealment for Fisheye Video Sequences Based on Equisolid Re-Projection - Eichenseer, Andrea; Seiler, Jürgen; Bätz, Michel; Kaup, André (Proc. of European Signal Processing Conference (EUSIPCO), 2015)
Wide-angle video sequences obtained by fisheye cameras exhibit characteristics that may not very well comply with standard image and video processing techniques such as error concealment. This paper introduces a temporal error concealment technique designed for the inherent characteristics of equisolid fisheye video sequences by applying a re-projection into the equisolid domain after conducting part of the error concealment in the perspective domain. Combining this technique with conventional decoder motion vector estimation achieves average gains of 0.71 dB compared against pure decoder motion vector estimation for the test sequences used. Maximum gains amount to up to 2.04 dB for selected frame
UnivIS-Import:2015-10-26:Pub.2015.tech.IE.LEN.tempor_4
Keywords: GRK-1773

Temporal filtering by double diffration - Jahns, J.; Lohmann, Adolf (Applied Optics, 2004)
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Temporal registration using 3D phase correlation and a maximum likelihood approach in the perceptual evaluation of video quality - Barkowsky, Marcus; Bialkowski, Jens; Bitto, Roland; Kaup, André (2007 IEEE 9Th International Workshop on Multimedia Signal Processing, MMSP 2007, 2007)
The estimation of the video quality is often performed using a full reference approach. One of the most important steps in a video quality measurement algorithm is to find the corresponding frames between the reference and the distorted video sequence. In this paper an algorithm with three steps is proposed. First, an extended version of the phase correlation is used to find candidate images with an arbitrary temporal offset, spatial scaling or spatial shift. Based on the assumption that the spatial scaling and spatial shift does not change during the sequence a set of probable parameters is selected. Finally, a maximum likelihood estimation is applied to select those temporal offsets which support the smoothest playback. A set of video sequences degraded with several distortions which are typical for multimedia scenarios are used to compare the performance to other algorithms. © 2007 IEE

Temporal trajectory aware video quality measure - Barkowsky, Marcus; Bialkowski, Jens; Eskofier, Björn; Bitto, Roland; Kaup, André (IEEE Journal of Selected Topics in Signal Processing, 2009)
The measurement of video quality for lossy and low-bitrate network transmissions is a challenging topic. Especially, the temporal artifacts which are introduced by video transmission systems and their effects on the viewer's satisfaction have to be addressed. This paper focuses on a framework that adds a temporal distortion awareness to typical video quality measurement algorithms. A motion estimation is used to track image areas over time. Based on the motion vectors and the motion prediction error, the appearance of new image areas and the display time of objects is evaluated. Additionally, degradations which stick to moving objects can be judged more exactly. An implementation of this framework for multimedia sequences, e.g., QCIF, CIF, or VGA resolution, is presented in detail. It shows that the processing steps and the signal representations that are generated by the algorithm follow the reasoning of a human observer in a subjective experiment. The improvements that can be achieved with the newly proposed algorithm are demonstrated using the results of the Multimedia Phase I database of the Video Quality Experts Group. © 2009 IEE
Keywords: Cognitive science; Multimedia communication; Objective video quality measurement; Temporal effects; Visual system

Temporal video segmentation using global motion estimation and discrete curve evolution - Treetasanatavorn, Siripong; Heuer, J.; Rauschenbach, U.; Kaup, André; Ilgner, K. (2004 International Conference on Image Processing, ICIP 2004, 2004)
The identification of syntactic or semantic temporal segments is an important process of video-content analysis. This paper proposes a temporal video segmentation method based on global motion in order to analyze meaningful temporal substructure of camera shots. To ensure that the detected segment optimally contributes to the shot global characteristic, the proposed method exploits a state-of-the-art discrete curve evolution. This technique leads to a subdivision of the global motion trajectory, where each segment of the subdivision has a constant relevant global motion. Experimental results based on standard test sequences acknowledge the method functionality especially for the shots characterized by pronounced camera motion. © 2004 IEEE.

Tension modulated nonlinear 2D models for digital sound synthesis with the functional transformation method - Petrausch, Stefan; Rabenstein, Rudolf (13th European Signal Processing Conference, EUSIPCO 2005, 2005)
Tension modulated nonlinearities for the modeling of string instruments are well known to increase the quality of synthesized sounds significantly. These models consider the nonlinear feedback from the string's deflection to one of its physical parameters, the string tension. Obviously this effect occurs for two dimensional models, drums or plates for instance, too, however so far only non real-time implementations are available. Therefore in this paper a new approach is presented, where the functional transformation method (FTM) is applied. The mathematical model of a dispersive and damped membrane is set up including an additional term for the tension modulated nonlinearity. Using some slight simplification this model is solved with the FTM and, thanks to the scalability of the FTM, implemented in real-time.

Testing Auditory Illusions in Augmented Reality: Plausibility, Transfer-Plausibility, and Authenticity - Meyer-Kahlen, Nils; Schlecht, Sebastian; Garí, Sebastià Amengual; Lokki, Tapio (Journal of the Audio Engineering Society, 2024)
Experiments testing sound for augmented reality can involve real and virtual sound sources. Paradigms are either based on rating various acoustic attributes or testing whether a virtual sound source is believed to be real (i.e., evokes an auditory illusion). This study compares four experimental designs indicating such illusions. The first is an ABX task suitable for evaluation under the authenticity paradigm. The second is a Yes/No task, as proposed to evaluate plausibility. The third is a three-alternative-forced-choice (3AFC) task using different source signals for real and virtual, proposed to evaluate transfer-plausibility. Finally, a 2AFC task was tested. The renderings compared in the tests encompassed mismatches between real and virtual room acoustics. Results confirm that authenticity is hard to achieve under nonideal conditions, and ceiling effects occur because differences are always detected. Thus, the other paradigms are better suited for evaluating practical augmented reality audio systems. Detection analysis further shows that the 3AFC transfer-plausibility test is more sensitive than the 2AFC task. Moreover, participants are more sensitive to differences between real and virtual sources in the Yes/No task than theory predicts. This contribution aims to aid in selecting experimental paradigms in future experiments regarding perceptual and technical requirements for sound in augmented reality.

Texture-Dependent Frequency Selective Reconstruction of Non-Regularly Sampled Images - Jonscher, Markus; Seiler, Jürgen; Kaup, André (Picture Coding Symposium (2016), 2016)
There exist many scenarios where pixel information is available only on a non-regular subset of pixel positions. For further processing, however, it is required to reconstruct such images on a regular grid. Besides many other algorithms, frequency selective reconstruction can be applied for this task. It performs a block-wise generation of a sparse signal model as an iterative superposition of Fourier basis functions and uses this model to replace missing or corrupted pixels in an image. In this paper, it is shown that it is not required to spend the same amount of iterations on both homogeneous and heterogeneous regions. Hence, a new texture-dependent approach for frequency selective reconstruction is introduced that distributes the number of iterations depending on the texture of the regions to be reconstructed. Compared to the original frequency selective reconstruction and depending on the number of iterations, visually noticeable gains in PSNR of up to 1.47 dB can be achieve

The Bjøntegaard Bible - Why your Way of Comparing Video Codecs May Be Wrong - Herglotz, Christian; Och, Hannah; Meyer, Anna; Ramasubbu, Geetha; Eichermüller, Lena; Kränzler, Matthias; Brand, Fabian; Fischer, Kristian; Nguyen, Dat Thanh; Regensky, Andy; Kaup, André (IEEE Transactions on Image Processing, 2024)
In this paper, we provide an in-depth assessment on the Bjøntegaard Delta. We construct a large data set of video compression performance comparisons using a diverse set of metrics including PSNR, VMAF, bitrate, and processing energies. These metrics are evaluated for visual data types such as classic perspective video, 360° video, point clouds, and screen content. As compression technology, we consider multiple hybrid video codecs as well as state-of-the-art neural network based compression methods. Using additional supporting points inbetween standard points defined by parameters such as the quantization parameter, we assess the interpolation error of the Bjøntegaard-Delta (BD) calculus and its impact on the final BD value. From the analysis, we find that the BD calculus is most accurate in the standard application of rate-distortion comparisons with mean errors below 0.5 percentage points. For other applications and special cases, e.g., VMAF quality, energy considerations, or inter-codec comparisons, the errors are higher (up to 5 percentage points), but can be halved by using a higher number of supporting points. We finally come up with recommendations on how to use the BD calculus such that the validity of the resulting BD-values is maximized. Main recommendations are as follows: First, relative curve differences should be plotted and analyzed. Second, the logarithmic domain should be used for saturating metrics such as SSIM and VMAF. Third, BD values below a certain threshold indicated by the subset error should not be used to draw recommendations. Fourth, using two supporting points is sufficient to obtain rough performance estimates.
CRIS-Team Scopus Importer:2024-02-02
Keywords: decoding energy; Video compression

The cocktail party robot: Sound source separation and localisation with an active binaural head - Deleforge, Antoine; Horaud, Radu (Proceedings of the seventh annual ACM/IEEE international conference on Human-Robot Interaction, 2012)
Human-robot communication is often faced with the difficult problem of interpreting ambiguous auditory data. For example, the acoustic signals perceived by a humanoid with its on-board microphones contain a mix of sounds such as speech, music, electronic devices, all in the presence of attenuation and reverberations. In this paper we propose a novel method, based on a generative probabilistic model and on active binaural hearing, allowing a robot to robustly perform sound-source separation and localization. We show how interaural spectral cues can be used within a constrained mixture model specifically designed to capture the richness of the data gathered with two microphones mounted onto a human-like artificial head. We describe in detail a novel EM algorithm, we analyse its initialization, speed of convergence and complexity, and we assess its performance with both simulated and real dat
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Keywords: blind source seperation; computational auditory scene analysis; EM algorithm; learning

The elitist particle filter based on evolutionary strategies as novel approach for nonlinear acoustic echo cancellation - Hümmer, Christian; Hofmann, Christian; Maas, Roland; Schwarz, Andreas; Kellermann, Walter (2014 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2014)
In this article, we introduce a novel approach for nonlinear acoustic echo cancellation based on a combination of particle filtering and evolutionary strategies. The nonlinear echo path is modeled as a state vector with non-Gaussian probability distribution and the relation to the observed signals and near-end interferences are captured by nonlinear functions. To estimate the probability distribution of the state vector and the model parameters, we apply the numerical sampling method of particle filtering, where each set of particles represents different realizations of the nonlinear echo path. While the classical particle-filter approach is unsuitable for system identification with large search spaces, we introduce a modified particle filter to select elitist particles based on long-term fitness measures and to create new particles based on the approximated probability distribution of the state vector. The validity of the novel approach is experimentally verified with real recordings for a nonlinear echo path stemming from a commercial smartphone. © 2014 IEE
Keywords: Echo cancellation; evolutionary strategies; nonlinear AEC; particle filter; system identification

The generalized frequency-domain adaptive filtering algorithm as an approximation of the block recursive least-squares algorithm - Schneider, Martin; Kellermann, Walter (EURASIP Journal on Advances in Signal Processing, 2016)
Acoustic echo cancellation (AEC) is a well-known application of adaptive filters in communication acoustics. To implement AEC for multichannel reproduction systems, powerful adaptation algorithms like the generalized frequency-domain adaptive filtering (GFDAF) algorithm are required for satisfactory convergence behavior. In this paper, the GFDAF algorithm is rigorously derived as an approximation of the block recursive least-squares (RLS) algorithm. Thereby, the original formulation of the GFDAF algorithm is generalized while avoiding an error that has been in the original derivation. The presented algorithm formulation is applied to pruned transform-domain loudspeaker-enclosure-microphone models in a mathematically consistent manner. Such pruned models have recently been proposed to cope with the tremendous computational demands of massive multichannel AEC. Beyond its generalization, a regularization of the GFDAF is shown to have a close relation to the well-known block least-mean-squares algorith
Keywords: Acoustic echo cancellation; Generalized frequency-domain adaptive filtering; System identification

The generalized frequency-domain adaptive filtering algorithm implemented on a GPU for large-scale multichannel acoustic echo cancellation - Schneider, Martin; Schuh, Fabian; Kellermann, Walter (ITG Symposium on Speech Communication, 2012)
For multichannel reproduction systems a trend towards increasing numbers of reproduction channels can be observed. For the use of such systems in communication scenarios, acoustic echo cancellation (AEC) is necessary, whose computational complexity scales at least linearly with the number of reproduction channels and implies a tremendous computational effort. Powerful graphics processing units (GPUs) appear to be a suitable implementation platform for such a scenario. However, inexpensive consumer-market GPUs are not designed for real-time adaptive audio processing with low-latency. In this paper we present an implementation of the Generalized Frequency-Domain Adaptive Filtering (GFDAF) algorithm on popular GPUs. Details on the parallelization of the algorithm are given and the performance of the implementation is evaluated for single precision and for double precision computation

The impact of loudspeaker array imperfections and reverberation on the performance of a multizone sound field synthesis system - Bürger, Michael; Hofmann, Christian; Kellermann, Walter (International Conference on Spatial Audio (ICSA), 2015)
In this paper, we investigate a real-world system for personalized audio rendering, whose purpose is to simultaneously synthesize different acoustic scenes in different areas of a reproduction room. The implemented system is based on a pressure matching approach, which aims at minimizing the mean squared error between the desired and reproduced sound pressure at a predefined set of control points. More precisely, a certain sound pressure distribution (e.g., as generated by a plane wave) shall be synthesized in a particular local listening area, whereas the sound pressure in the remaining areas of interest shall ideally be zero such that multiple acoustics scenes can be independently synthesized. Motivated by the Kirchhoff–Helmholtz integral equation, the virtual control points are placed on circular contours around the individual local listening areas. The reproduction system is installed in a reverberant, but acoustically controlled environment and, for evaluation, the synthesized sound field is sensed at a multitude of positions within each of the local listening areas. Thereby, the reproduction performance of the real system can be compared to that of a previously simulated system assuming ideal conditions. In particular, the impact of reverberation on the one hand, and the impact of the radiation characteristics of real loudspeakers together with positioning errors on the other hand, are of special interest and assessed separatel

The Influence of Phase Disposition of AC Grids on the Harmonic Distortion of Line-Commutated Converter based HVDC Systems - Hahn, Christoph; Luther, Matthias; Glücker, Philipp (International CIGRÉ Symposium, 2015)
This paper deals with the analysis of the characteristic harmonics of currents and voltages of linecommutated converter (LCC) based high voltage direct current (HVDC) transmission systems. The generation of harmonics of AC and DC currents and voltages of an HVDC transmission system is carried out. The characteristic harmonics are analyzed in a simulation with the help of the Fast Fourier Transformation (FFT). <br
UnivIS-Import:2015-11-17:Pub.2015.tech.IE.leen.theinf
Keywords: harmonics; HVDC; line-commutated converter; phase shift; firing angle

The LOCATA Challenge: Acoustic Source Localization and Tracking - Evers, Christine; Löllmann, Heinrich; Mellmann, Heinrich; Schmidt, Alexander; Barfuß, Hendrik; Naylor, Patrick; Kellermann, Walter (IEEE/ACM Transactions on Audio, Speech and Language Processing, 2020)
The ability to localize and track acoustic events is a fundamental prerequisite for equipping machines with the ability to be aware of and engage with humans in their surrounding environment. However, in realistic scenarios, audio signals are adversely affected by reverberation, noise, interference, and periods of speech inactivity. In dynamic scenarios, where the sources and microphone platforms may be moving, the signals are additionally affected by variations in the source-sensor geometries. In practice, approaches to sound source localization and tracking are often impeded by missing estimates of active sources, estimation errors, as well as false estimates. The aim of the LOCAlization and TrAcking (LOCATA) Challenge is an openaccess framework for the objective evaluation and benchmarking of broad classes of algorithms for sound source localization and tracking. This paper provides a review of relevant localization and tracking algorithms and, within the context of the existing literature,a detailed evaluation and dissemination of the LOCATA submissions. The evaluation highlights achievements in the field, open challenges, and identifies potential future directions.

The LOCATA Challenge Data Corpus for Acoustic Source Localization and Tracking - Löllmann, Heinrich; Evers, Christine; Schmidt, Alexander; Mellmann, Heinrich; Barfuß, Hendrik; Naylor, Patrick A.; Kellermann, Walter (IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), 2018)
Algorithms for acoustic source localization and tracking are essential for a wide range of applications such as personal assistants, smart homes, tele-conferencing systems, hearing aids, or autonomous systems. Numerous algorithms have been proposed for this purpose which, however, are not evaluated and compared against each other by using a common database so far. The IEEE-AASP Challenge on sound source localization and tracking (LOCATA) provides a novel, comprehensive data corpus for the objective benchmarking of state-of-the-art algorithms on sound source localization and tracking. The data corpus comprises six tasks ranging from the localization of a single static sound source with a static microphone array to the tracking of multiple moving speakers with a moving microphone array. It contains real-world multichannel audio recordings, obtained by hearing aids, microphones integrated in a robot head, a planar and a spherical microphone array in an enclosed acoustic environment, as well as positional information about the involved arrays and sound sources represented by moving human talkers or static loudspeakers.<br
Keywords: LOCATA Challenge; Source Localization; Source Tracking; Benchmark; Data Corpus

The man-machine-interface for the air exchange measurement system Multi-CAT - Rabenstein, Rudolf; Heidt, F. D. (11th AIVC Conference "Ventilation system performance", 1990)
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The Montgomery interferometer as a programmable filter - Knuppertz, H.; Jahns, J.; Lohmann, Adolf; Minguez-Vega, G. (EOS Top. Meet. Optics in Computing 2004, Engelberg, Schweiz, 2004)
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The New Global Digital Elevation Model: TanDEM-X DEM and its Final Performance - Gonzalez, Carolina; Rizzoli, Paola; Martone, Michele; Wecklich, Christopher; Tridon, Daniela Borla; Bachmann, Markus; Fritz, Thomas; Wessel, Birgit; Krieger, Gerhard; Zink, Manfred (European Geosciences Union (EGU), 2017)
DLR Import::2019-04-03

The NLMS algorithm with time-variant optimum stepsize derived from a Bayesian network perspective - Hümmer, Christian; Maas, Roland; Kellermann, Walter (IEEE Signal Processing Letters, 2015)
In this letter, we derive a new stepsize adaptation for the normalized least mean square algorithm (NLMS) by describing the task of linear acoustic echo cancellation from a Bayesian network perspective. Similar to the well-known Kalman filter equations, we model the acoustic wave propagation from the loudspeaker to the microphone by a latent state vector and define a linear observation equation (to model the relation between the state vector and the observation) as well as a linear process equation (to model the temporal progress of the state vector). Based on additional assumptions on the statistics of the random variables in observation and process equation, we apply the expectation-maximization (EM) algorithm to derive an NLMS-like filter adaptation. By exploiting the conditional independence rules for Bayesian networks, we reveal that the resulting EM-NLMS algorithm has a stepsize update equivalent to the optimal-stepsize calculation proposed by Yamamoto and Kitayama in 1982, which has been adopted in many textbooks. As main difference, the instantaneous stepsize value is estimated in the M step of the EM algorithm (instead of being approximated by artificially extending the acoustic echo path). The EM-NLMS algorithm is experimentally verified for synthesized scenarios with both, white noise and male speech as input signa
Keywords: Adaptive stepsize; EM algorithm; NLMS

The REVERB challenge: A benchmark task for reverberation-robust ASR techniques - Kinoshita, Keisuke; Delcroix, Marc; Gannot, Sharon; Habets, Emanuël; Haeb-Umbach, Reinhold; Kellermann, Walter; Leutnant, V.; Maas, Roland; Nakatani, Tomohiro; Raj, B.; Sehr, Armin; Yoshioka, Takuya (New Era for Robust Speech Recognition, 2017)
The REVERB challenge is a benchmark task designed to evaluate reverberation-robust automatic speech recognition techniques under various conditions. A particular novelty of the REVERB challenge database is that it comprises both real reverberant speech recordings and simulated reverberant speech, both of which include tasks to evaluate techniques for 1-, 2-, and 8-microphone situations. In this chapter, we describe the problem of reverberation and characteristics of the REVERB challenge data, and finally briefly introduce some results and findings useful for reverberant speech processing in the current deep-neural-network er

The REVERB challenge: Acommon evaluation framework for dereverberation and recognition of reverberant speech - Kinoshita, Keisuke; Delcroix, Marc; Yoshioka, Takuya; Nakatani, Tomohiro; Habets, E.; Haeb-Umbach, R.; Leutnant, V.; Sehr, Armin; Kellermann, Walter; Maas, Roland; Gannot, S.; Raj, B. (IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), 2013)
Recently, substantial progress has been made in the field of reverberant speech signal processing, including both single- and multichannel dereverberation techniques, and automatic speech recognition (ASR) techniques robust to reverberation. To evaluate state-of-the-art algorithms and obtain new insights regarding potential future research directions, we propose a common evaluation framework including datasets, tasks, and evaluation metrics for both speech enhancement and ASR techniques. The proposed framework will be used as a common basis for the REVERB (REverberant Voice Enhancement and Recognition Benchmark) challenge. This paper describes the rationale behind the challenge, and provides a detailed description of the evaluation framework and benchmark results. © 2013 IEE
Keywords: ASR; challenge; dereverberation; evaluation; Reverberant speech

The SCENIC project: Environment-aware sound sensing and rendering - Annibale, Paolo; Antonacci, Fabio; Bestagini, P.; Brutti, A.; Canclini, Antonio; Cristoforetti, L.; Habets, Emanuël; Filos, Jason; Kellermann, Walter; Kowalczyk, Konrad; Lombard, Anthony; Mabande, E.; et al. (Proc. of the 2nd European Future Technologies Conference and Exhibition, Procedia Computer Science, 2011)
The SCENIC project is aimed at making the environment become an integral part of the acoustic system. The goal is to boost the performance of arrays of speakers and microphones and, in some cases, to enable applications that would not be possible otherwise. This paper describes how this can be achieve
Keywords: environment-aware sound processing; microphone and speaker arrays; computational acoustics

The SCENIC project: Space-time audio processing for environment-aware acoustic sensing and rendering - Annibale, Paolo; Antonacci, F.; Bestagini, P.; Brutti, A.; Canclini, A.; Cristoforetti, L.; Habets, Emanuël; Filos, J.; Kellermann, Walter; Kowalczyk, Konrad; Lombard, A.; Mabande, Edwin; et al. (131st Audio Engineering Society Convention 2011, 2011)
SCENIC is an EC-funded project aimed at developing a harmonized corpus of methodologies for environmentaware acoustic sensing and rendering. The project focusses on space-time acoustic processing solutions that do not just accommodate the environment in the modeling process but that make the environment help towards achieving the goal at hand. The solutions developed within this project cover a wide range of applications, including acoustic self-calibration, aimed at estimating the parameters of the acoustic system; environment inference, aimed at identifying and characterizing all the relevant acoustic reflectors in the environment. The information gathered through such steps is then used to boost the performance of wavefield rendering methods as well as source localization/characterization/extraction in reverberant environment

The significance-aware EPFES to estimate a memoryless preprocessor for nonlinear acoustic echo cancellation - Hümmer, Christian; Hofmann, Christian; Maas, Roland; Kellermann, Walter (IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2014)
In this article, we introduce a novel approach for estimating the coefficients of a memoryless preprocessor for nonlinear acoustic echo cancellation (NL-AEC) using particle filtering. The acoustic echo path is modeled by a nonlinear-linear cascade of a memoryless preprocessor (to model the loudspeaker nonlinearities) preceding a linear finite impulse response filter (estimated by the normalized least mean square algorithm). For identifying the loudspeaker signal distortions, we follow the concept of significance-aware filtering by modeling the time-variant coefficients of the memoryless preprocessor and the direct-path part of the room impulse response vector as one state vector with non-Gaussian probability distribution. Due to the nonlinear relation between the state vector and the observation, we propose a computationally-efficient realization of the recently published elitist particle filter based on evolutionary strategies (EPFES), which evaluates realizations of the state vector based on long-term fitness measures. The experimental validation comprises predefined loudspeaker signal distortions as well as real recordings stemming from a commercial smartphone. In comparison to the well-known Hammerstein group model for NL-AEC, the computational complexity is reduced and the achievable system identification is improved for both scenario
Keywords: EPFES; Machine learning for signal processing; Memoryless preprocessor; Nonlinear AEC; Particle filtering

The spatial coherence of noise fields evoked by continuous source distributions - Bürger, Michael; Abhayapala, Thushara D.; Hofmann, Christian; Chen, Hanchi; Kellermann, Walter (The Journal of the Acoustical Society of America, 2017)
In this work, analytic expressions for the spatial coherence of noise fields are derived in the modal domain with the aim of providing a sparse representation. For this purpose, the sound field in a region of interest is expressed in terms of a given pressure distribution on a virtual surrounding cylindrical or spherical surface. According to the Huygens–Fresnel principle, the sound pressure on this surface is represented by a continuous distribution of elementary line or point sources, where orthogonal basis functions characterize the spatial properties. To describe spatially windowed pressure distributions with arbitrary angular extensions, orthogonal basis functions of limited angular support are proposed. As special cases, circular and spherical pressure distributions with uncorrelated source modes of equal power are investigated. It is shown that these distributions result, respectively, in cylindrically isotropic and spherically isotropic, i.e., diffuse noise fields. The analytic expressions derived in this work allow for a prediction of the spatial coherence between arbitrary positions within the region of interest, such that no microphones need to be placed at the actual points of interest. Simulation results are presented to validate the derived relatio

The study on application of linear prediction filter in blind source separation - Zhao, Zhijin; Kellermann, Walter; Aichner, Robert (2004 7th International Conference on Signal Processing Proceedings, ICSP, 2004)
To improve the separated speech quality, linear prediction filter(LPF) has been used, but there is no explanation why to be able to guarantee source separation by BSS algorithms after linear prediction filtering. In this paper the theoretical analysis about this issue is presentedand the concept of the LPF application is illistruted. The experimental results demonstrate their correctness.
Keywords: Blind source separation (BSS); Independent component analysis(ICA); Preprocessing

The Sturm-Liouville-Transformation for the Solution of Vector Partial Differential Equations - Trautmann, Lutz; Rabenstein, Rudolf (Proc. Workshop on Transforms and Filterbanks (WTFB), 1999)
LMS::285

The theory of wave field synthesis revisited - Spors, Sascha; Rabenstein, Rudolf; Ahrens, Jens (124th Audio Engineering Society Convention 2008, 2008)
Wave field synthesis is a spatial sound field reproduction technique aiming at authentic reproduction of auditory scenes. Its theoretical foundation has been developed almost 20 years ago and has been improved considerably since then. Most of the original work on wave field synthesis is restricted to the reproduction in a planar listening area using linear loudspeaker arrays. Extensions like arbitrarily shaped distributions of secondary sources and three-dimensional reproduction in a listening volume have not been discussed in a unified framework so far. This paper revisits the theory of wave field synthesis and presents a unified theoretical framework covering arbitrarily shaped loudspeaker arrays for two- and three-dimensional reproduction. The paper additionally gives an overview on the artifacts resulting in practical setups and briefly discusses some extensions to the traditional concepts of WF

The TRINICON framework for adaptive MIMO signal processing with focus on the generic Sylvester constraint - Buchner, Herbert; Aichner, Robert; Kellermann, Walter (Proc. ITG Conference on Speech Communication, 2008)
This paper gives an overview on TRINICON, a generic framework for broadband adaptive MIMO filtering, and some of its applications in array processing for speech capture. The motivations for this framework are to bring together the various blind and supervised MIMO adaptation techniques which have been treated largely independently in the literature so far, in order to spotlight their commonalities and relationships, to derive them in a rigorous way from first principles, to facilitate the design of improved systems, and to exploit synergies. In this paper, a special focus is on new results on the so-called Sylvester constraint, an important element of the framework. ©V
LMS::750

Time-Constant Histogram Matching for Luminance and Chrominance Compensation of Multi-View Video Sequences - Fecker, Ulrich; Barkowsky, Marcus; Kaup, André (26th Picture Coding Symposium, PCS 2007, 2007)
Significant advances have recently been made in the coding of video data recorded with multiple cameras. However, luminance and chrominance variations between the camera views may deteriorate the performance of multi-view video codecs and renderers. In this paper, the usage of time-constant histogram matching is proposed to compensate these differences in a pre-filtering step. It is shown that the usage of histogram matching prior to multi-view video coding leads to significant gains for the coding efficiency of both the luminance and the chrominance components. Histogram matching can also be useful for image-based rendering to avoid incorrect illumination and colour reproduction resulting from miscalibrations in the recording setup. It can be shown that the algorithm is further improved by additionally using RGB colour conversio
Keywords: Image-based rendering; Multi-view video; Video coding; Video signal processing

Time-frequency-bin-wise beamformer selection and masking for speech enhancement in underdetermined noisy scenarios - Yamaoka, Kouei; Brendel, Andreas; Ono, Nobutaka; Makino, Shoji; Bürger, Michael; Yamada, Takeshi; Kellermann, Walter (European Signal Processing Conference (EUSIPCO), 2018)
In this paper, we present a speech enhancement method using two microphones for underdetermined situations. A conventional speech enhancement method for underdetermined situations is time-frequency masking, where speech is enhanced by multiplying zero or one to each time-frequency component appropriately. Extending this method, we switch multiple preconstructed beamformers at each time-frequency bin, each of which suppresses a particular interferer. This method can suppress an interferer even when both the target and an interferer are simultaneously active at a given time-frequency bin. As a switching criterion, selection of minimum value of the outputs of the all beamformers at each time-frequency bin is investigated. Additionally, another method using direction of arrival estimation is also investigated. In experiments, we confirmed that the proposed methods were superior to conventional time-frequency masking and fixed beamforming in the performance of speech enhancemen

Too-Hot-to-Handle: Insights into Temperature and Noise Hyperparameters for Differentiable Neural-Architecture-Searches - Conrad, Joschua; Wilhelmstatter, Simon; Asthana, Rohan; Belagiannis, Vasileios; Ortmanns, Maurits (2024 IEEE 6th International Conference on AI Circuits and Systems (AICAS), 2024)
The deployment of neural networks on resource-constrained hardware requires architecture optimization algorithms that respect accuracy and computational cost. One emerging way for performing such an architecture optimization is the differentiable neural-architecture-search (DNAS). DNAS finds the weights of a neural network as well as its topology in a single training. The topology search-space is represented by instantiating different layer-candidates for each layer in parallel, thereby forming a so-called weighted super-network. The instances are connected via a gumbel-softmax function which employs important parameters commonly called temperature τ and noise-scale β. The temperature is scheduled during training and controls the convergence to selecting only a single final candidate per optimized layer. The noise-scale adds a random behavior in trying different candidates before deciding for a final one. The state-of-the-art (SotA) does not define rules for setting those important hyperparameters. Therefore, this work elaborates methods to predict feasible start- and end-temperature as well as noise-scale prior to training and to fine-tune the parameters from metrics obtained during a DNAS.
CRIS-Team Scopus Importer:2024-08-09
Keywords: differentiable neural-architecture-search; gumbel-softmax; temperature

Topology Simulation for Aeronautical Communication Protocols with ns-3 and DCE - Lehmann, Andreas; Kreuzer, Matthias; Deutschmann, Jörg; Berold, Ulrich; Huber, Johannes (Proceedings of the Workshop on ns-3, 2016)

Toward Bridging the Simulated-to-Real Gap: Benchmarking Super-Resolution on Real Data - Köhler, Thomas; Bätz, Michel; Naderi Boldaji, Farzad; Kaup, André; Maier, Andreas; Rieß, Christian (IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019)
UnivIS-Import:2019-08-15:Pub.2019.tech.IMMD.IMMD5.toward_0

Towards a better understanding of the effect of reverberation on speech recognition performance - Sehr, Armin; Habets, Emanuël; Maas, Roland; Kellermann, Walter (Proc. International Workshop on Acoustic Echo and Noise Control (IWAENC), 2010)
In order to tailor dereverberation approaches to automatic speech recognition (ASR) systems, it is important to thoroughly understand the effect of reverberation on ASR performance. In this work, the effect is analyzed by varying the shape of the room impulse response (RIR) using two design parameters that are useful for defining the target response of typical dereverberation algorithms. The parameters determine the amount of attenuation of the coefficients that correspond to reflections arriving with at least a delay of T after the direct-path component. By convolving clean speech signals with the modified RIRs, ideal late-reverberation suppression is simulated. By varying the level of attenuation A and the delay T , the influence of these design parameters on the recognition rates is investigated. Thus, guidelines for adjusting dereverberation algorithms to ASR systems are deduce

Towards a Framework for Continuous and Discrete Multidimensional Systems - Rabenstein, Rudolf; Trautmann, Lutz (International Journal of Applied Mathematics and Computer Science, 2003)
LMS::434

Towards a generalization of relative transfer functions to more than one source - Deleforge, Antoine; Gannot, Sharon; Kellermann, Walter (23rd European Signal Processing Conference (EUSIPCO), 2015)
We propose a natural way to generalize relative transfer functions (RTFs) to more than one source. We first prove that such a generalization is not possible using a single multichannel spectro-temporal observation, regardless of the number of microphones. We then introduce a new transform for multichannel multi-frame spectrograms, i.e., containing several channels and time frames in each time-frequency bin. This transform allows a natural generalization which satisfies the three key properties of RTFs, namely, they can be directly estimated from observed signals, they capture spatial properties of the sources and they do not depend on emitted signals. Through simulated experiments, we show how this new method can localize multiple simultaneously active sound sources using short spectro-temporal windows, without relying on source separatio
Keywords: Grassmannian manifolds; Multiple sound sources localization; Plucker Embedding; Relative Transfer Function

Towards Natural Acoustic Interfaces for Automatic Speech Recgnition - Kellermann, Walter (Proc. 13th Int. Conf. Speech and Computer, 2009)
Aiming at 'natural' hands-free acoustic human/machine inter-faces, the need for according distant-talking automatic speech recognition (ASR) systems increases and presents us with ma-jor signal processing challenges at the acoustic front-end. Con-sidering interactive TV as a challenging exemplary application scenario, we investigate the structural problems presented by noisy and reverberant multi-source environments with unpre-dictable interference and acoustic echoes of loudspeaker sig-nals, and discuss current acoustic signal processing techniques to enhance the input to the actual ASR system. For illustration, the scenario of an EU-funded project on distant-talking inter-faces for interactive TV (DICIT) is considered as a challenging exampl

Towards polarization-based excitation tailoring for extended Raman spectroscopy - Grosche, Simon; Hünermann, Richard; Sarau, George; Christiansen, Silke; Boyd, Robert W.; Leuchs, Gerd; Banzer, Peter (Optics Express, 2020)
Undoubtedly, Raman spectroscopy is one of the most elaborate spectroscopy tools in materials science, chemistry, medicine and optics. However, when it comes to the analysis of nanostructured specimens or individual sub-wavelength-sized systems, the access to Raman spectra resulting from different excitation schemes is usually very limited. For instance, the excitation with an electric field component oriented perpendicularly to the substrate plane is a difficult task. Conventionally, this can only be achieved by mechanically tilting the sample or by sophisticated sample preparation. Here, we propose a novel experimental method based on the utilization of polarization tailored light for Raman spectroscopy of individual nanostructures. As a proof of principle, we create three-dimensional electromagnetic field distributions at the nanoscale using tightly focused cylindrical vector beams impinging normally onto the specimen, hence keeping the traditional beam-path of commercial Raman systems. In order to demonstrate the convenience of this excitation scheme, we use a sub-wavelength diameter gallium-nitride nanostructure as a test platform and show experimentally that its Raman spectra depend sensitively on its location relative to the focal vector field. The observed Raman spectra can be attributed to the interaction with transverse and pure longitudinal electric field components. This novel technique may pave the way towards a characterization of Raman active nanosystems, granting direct access to growth-related parameters such as strain or defects in the material by using the full information of all Raman mode

Towards Robust Distant-Talking Automatic Speech Recognition in Reverberant Environments - Sehr, Armin; Kellermann, Walter (Speech and Audio Processing in Adverse Environments, 2008)

Towards Superdirective Beamforming with Loudspeaker Arrays - Mabande, Edwin; Kellermann, Walter (Conf. Rec. International Congress on Acoustics, 2007)
LMS::725

Towards Sustainable and Energy-aware Video Communications (SEViC) - Combemale, Benoit; Mussbacher, Gunter; Betz, Stefanie; Friday, Adrian; Hadar, Irit; Sallou, June; Groher, Iris; Muccini, Henry; Le Meur, Olivier; Herglotz, Christian; Eriksson, Elina; Penzenstadler, Birgit; et al. (Joint Proceedings of ICT4S 2023 Doctoral Symposium, Demonstrations & Posters Track and Workshops., 2023)

Towards Video Codec Performance Evaluation: A Rate-Energy-Distortion Perspective - Ramasubbu, Geetha; Kaup, André; Herglotz, Christian (2024 16th International Conference on Quality of Multimedia Experience (QoMEX), 2024)
The Bjøntegaard Delta rate (BD-rate) objectively assesses the coding efficiency of video codecs using the rate-distortion (R-D) performance but overlooks encoding energy, which is crucial in practical applications, especially for those on handheld devices. Although R-D analysis can be extended to incorporate encoding energy as energy-distortion (E-D), it fails to integrate all three parameters seamlessly. This work proposes a novel approach to address this limitation by introducing a 3D representation of rate, encoding energy, and distortion through surface fitting. In addition, we evaluate various surface fitting techniques based on their accuracy and investigate the proposed 3D representation and its projections. The overlapping areas in projections help in encoder selection and recommend avoiding the slow presets of the older encoders (x264, x265), as the recent encoders (x265, VVenC) offer higher quality for the same bitrate-energy performance and provide a lower rate for the same energy-distortion performance.<br

Tracking of multiple sources in an acoustic sensor network using an extended Gaussian mixture PHD filter - Brendel, Andreas; Kellermann, Walter (IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), 2018)
We propose an approach for tracking a varying number of simultaneously active acoustic wideband signal sources in an acoustic enclosure. Relying on the assumption of W-disjoint orthogonality, the method uses narrowband position estimates of the sources for the targets. The instantaneous position estimates form clusters rather than single points, as would be required for a conventional Probability Hypothesis Density (PHD) filter. Therefore, we model the position estimates as extended targets and use a special form of the PHD filter, the extended target Gaussian mixture PHD filter, for tracking the targets. This allows to model target birth and death, which correspond to speech onset and end of utterance, respectively. With this model and by using the well-developed theory of Finite Set Statistics (FISST)-based multi-target tracking, we provide a comprehensive, strictly Bayesian treatment of the problem of tracking wideband acoustic sources using narrowband position estimates. We validate the results by tracking a varying number of targets in an enclosure simulated with the image-source metho

Trade-Off between Source and Channel Coding for Video Transmission - Stuhlmüller, Klaus; Färber, Niko; Girod, Bernd (Int. Conf. on Image Processing (ICIP'2000), 2000)
LMS::181

Transfer Function Models for Continuous and Discrete Multidimensional Systems - Rabenstein, Rudolf (Proc. European Signal Processing Conference (EUSIPCO), 1998)
LMS::330

Transfer Function Models for Cylindrical MC Channels with Diffusion and Laminar Flow - Schäfer, Maximilian; Wicke, Wayan; Brand, Lukas; Rabenstein, Rudolf; Schober, Robert (IEEE Transactions on Molecular, Biological and Multi-Scale Communications, 2021)
The analysis and design of advection-diffusion based molecular communication (MC) systems in cylindrical environments is of particular interest for applications such as micro-fluidics and targeted drug delivery in blood vessels. Therefore, the accurate modeling of the corresponding MC channel is of high importance. The propagation of particles in these systems is caused by a combination of diffusion and flow with a parabolic velocity profile, i.e., laminar flow. The propagation characteristics of the particles can be categorized into three different regimes: The flow dominant regime where the influence of diffusion on the particle transport is negligible, the dispersive regime where diffusion has a much stronger impact than flow, and the mixed regime where both effects are important. For the limiting regimes, i.e., the flow dominant and dispersive regimes, well-known solutions and approximations for particle transport exist. For the mixed regime, approximations, numerical techniques, and particle based simulations are employed. However, the few analytical models that are applicable in all three regimes impose significant constraints on the possible transmitter locations and particle release profiles. In this paper, we develop a more general analytical model for the advection-diffusion problem in cylindrical environments, which is applicable in all three regimes and accounts for general particle release models. The proposed model exhibits a higher accuracy than existing models and is based on a transfer function approach, where the main challenge is the incorporation of laminar flow. The properties of the proposed model are analyzed by numerical evaluation for different scenarios including the uniform and point release of particles. We provide a comparison with particle based simulations and existing analytical models from the literature to demonstrate the validity of the proposed analytical model.<br
Keywords: Analytical models; Mathematical model; Numerical models; Dispersion; Biology; Transfer functions; Plugs

Transfer Function Models for Distributed-Parameter Systems with Impedance Boundary Conditions - Rabenstein, Rudolf; Schäfer, Maximilian; Strobl, Christian (International Journal of Control, 2018)
A transfer function description is derived for a general class of linear distributed parameter systems dependent on time and one spatial variable. Suitable functional transformations are the Laplace transformation for the time variable and the Sturm–Liouville transformation for the space variable. A practical problem is the determination of the eigenfunctions of the Sturm–Liouville transformation since these depend on the type and the parameters of the boundary conditions. This contribution shows that the design of a transfer function model can be separated from the correct treatment of the boundary conditions. The presented approach exhibits strong parallels to state feedback techniques from control theory. Examples for an electrical transmission line demonstrate how terminations with arbitrary complex impedances can be considered without redesigning the transmission line mode
Keywords: Transfer functions; boundary conditions; Sturm–Liouville transformation; bi-orthogonal basis functions; state feedback; closed-loop system

Transfer Function Models for Multidimensional Systems - Rabenstein, Rudolf (2. Int. Symposium on Mathematical Modelling, 1997)
LMS::387

Transfer Function Models for Multidimensional Systems with Bounded Domains - Rabenstein, Rudolf (Mathematical and Computer Modelling of Dynamical Systems, 1999)
Multidimensional (MD) systems describe relations between signals depending on two or more independent variables. They are also called distributed parameter systems, if the independent variables are time and space. The only conventional models for their description are partial differential equations. This is in contrast to onedimensional (lumped parameter) systems, where a variety of different models including transfer functions is used. This paper extends the concept of transfer function models to multidimensional systems with bounded spatial domains, i.e., systems which can be described as initial-boundary-value problems. These transfer function models are useful for system analysis and as a starting point for the derivation of numerically efficient discrete simulation models.
Keywords: 35K05; 35K15; 35K20; 35L15; 35L20; 42C15; 65C20; 65R10; 93A30; 93C20; 93C80

Transfer Function Models for Non-Self-Adjoint Multidimensional Systems - Rabenstein, Rudolf (Proc. Second Int. Conf. on Circuits, Systems, and Computers (CSC'98), 1998)
LMS::335

Transfer Function Models for Non Self-Adjoint Multidimensional Systems - Rabenstein, Rudolf (Recent Advances in Information Science and Technology, 1998)

Transfer function models for particle diffusion in a horizontal cylindrical shape with a vertical force component - Schäfer, Maximilian; Wicke, Wayan; Rabenstein, Rudolf; Schober, Robert (2018)

Transfer function models of multidimensional physical systems - Rabenstein, Rudolf (Digest of the IEE Coll. on Multidimensional Systems, 1998)
Transfer functions models of linear systems are a well established tool for the design and analysis of one-dimensional systems. This is not the case for multidimensional physical systems, given in terms of initial boundary value problems. Here, the only mathematical description of widespread use are partial differential equations. This contribution shows, how the one-dimensional transfer function concept can be generalized to multidimensional systems with initial and boundary conditions. The idea is first introduced by a simple example and then extended to arbitrary spatial dimensions, general boundary conditions, space dependent coefficients and non self-adjoint differential operators.

Transfer function models with nonlinear excitations for digital sound synthesis - Trautmann, Lutz; Rabenstein, Rudolf (2000 10th European Signal Processing Conference, EUSIPCO 2000, 2000)
Transfer functions for digital sound synthesis based on physical models have recently been presented. The method transforms a continuous model for the vibrating body, given by a partial differential equation (PDE), into a multidimensional transfer function model (TFM). The TFM not only takes initial and boundary conditions, as well as excitation functions into account, but also treats the physical effects modeled by the PDE exactly. The algorithms obtained after discretization of the TFM preserve the inherent physical stability and are suitable for real-time implementations on digital signal processors. A recently presented example of a linear transversal oscillating tightened string with frequency dependent loss terms is extended here by nonlinear excitations. They are modeled from real bow-string and hammer-string interactions in violins and pianos.

Transient Simulation of Nonuniform Multiconductor Transmission Lines by MD Wave Digital Techniques - Krauß, Herbert; Steffen, Peter (Proc. 13th Int. Conf. on Digital Signal Processing, 1997)
LMS::402

TRINICON: A versatile framework for multichannel blind signal processing - Buchner, Herbert; Aichner, Robert; Kellermann, Walter (IEEE International Conference on Acoustics, Speech, and Signal Processing, 2004)
In this paper we present a framework for multichannel blind signal v processing for convolutive mixtures, such as blind source separation (BSS) and multichannel blind deconvolution (MCBD). It is based on the use of multivariate pdfs and a compact matrix notation which considerably simplifies the representation and handling of the algorithms. By introducing these techniques into an information theoretic cost function, we can exploit the three fundamental signal properties nonwhiteness, nongaussianity, and nonstationarity. This results in a versatile tool that we call TRINICON ('Triple-N ICA for convolutive mixtures'). Both, links to popular algorithms and several novel algorithms follow from the general approach. In particular, we introduce a new concept of multichannel blind partial deconvolution (MCBPD) for speech which prevents a complete whitening of the output signals, i.e., the vocal tract is excluded from the equalization. This is especially interesting for automatic speech recognition applications. Moreover, we show results for BSS using multivariate spherically invariant random processes (SIRPs) to efficiently model speech, and show how the approach carries over to MCBPD. These concepts are also suitable for an efficient implementation in the frequency domain by using a rigorous broadband derivation avoiding the internal permutation problem and circularity effect

TRINICON-based blind system identification with application to multiple-source localization and separation - Buchner, Herbert; Aichner, Robert; Kellermann, Walter (Blind Speech Separation, 2007)
This contribution treats blind system identification approaches and how they can be used to localize multiple sources in environments where multipath propagation cannot be neglected, e.g., acoustic sources in reverberant environments. Based on TRINICON, a general framework for broadband adaptive MIMO signal processing, we first derive a versatile blind MIMO system identification method. For this purpose, the basics of TRINICON will be reviewed to the extent needed for this application, and some new algorithmic aspects will be emphasized. The generic approach then allows us to study various illustrative relations to other algorithms and applications. In particular, it is shown that the optimization criteria used for blind system identification allow a generalization of the well-known Adaptive Eigenvalue Decomposition (AED) algorithm for source localization: Instead of one source as with AED, several sources can be localized simultaneously. Performance evaluation in realistic scenarios will show that this method compares favourably with other state-of-the-art methods for source localization.©Spring

TRINICON-BSS system incorporating robust dual beamformers for noise reduction - Anderson, Craig; Meier, Stefan; Kellermann, Walter; Teal, Paul D.; Poletti, Mark A. (IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015)
In this paper, a method of adaptive noise suppression combining spatially robust fixed beamforming and the TRINICON blind source separation algorithm is presented. A multichannel sensor array is first processed using complementary fixed beamformers into maximum and minimum SINR channels. The channels form the inputs to a single 2×2 second-order statistics TRINICON-BSS system which adaptively compensates for imperfections of the fixed beamformer design relative to the acoustic scenario. It is demonstrated that integrating the TRINICON-BSS algorithm leads to improved SINR performance over the initial imperfect beamformer design, and achieves a performance comparable to a perfect MVDR beamforme
Keywords: Robust beamforming; Adaptive filtering; Blind source separation

TRINICON for Dereverberation of Speech and Audio Signals - Buchner, Herbert; Kellermann, Walter (Speech Dereverberation, 2010)
In this chapter, we develop an analytical top-down approach to the problem of blind dereverberation of speech and audio signals based on TRINICON (TRIple-N Independent component analysis for CONvolutive mixtures), a general framework for broadband adaptive Multi-Input Multi-Output (MIMO) signal processing. Two fundamentally different approaches to the dereverberation problem for realistic scenarios can be distinguished: The “identification-and-inversion approach”, which results in a two-step procedure consisting of blind identification of the acoustic MIMO mixing system, followed by an inversion of the identified system. As an alternative, the “direct-inverse approach” blindly estimates the inverse of the acoustic mixing system directly. As shown in this chapter, for both cases TRINICON yields the information-theoretically optimum estimation procedures in a unified way and allows for a direct comparison between the approaches, paves the way to synergies, and yields various useful insights for practical realizations. This chapter also relates other known algorithms, and presents novel improved algorithms as special cases of the generic concep
Keywords: finite impulse response; audio signal; blind source separation; blind signal; blind deconvolution

Tubular bells: A physical and algorithmic model - Rabenstein, Rudolf; Koch, Tilman; Popp, Christian (IEEE Transactions on Audio Speech and Language Processing, 2010)
Tubular bells are geometrically simple representatives of three-dimensional vibrating structures. Under certain assumptions, a tubular bell can be modeled as a rectangular plate with different types of homogeneous boundary conditions. Suitable functional transformations with respect to time and space turn the corresponding initial-boundary value problem into a two-dimensional transfer function. An algorithmic model follows according to the functional transformation method in digital sound synthesis. As with simpler vibrating structures (strings, membranes) the synthesis algorithms consist of a parallel arrangement of second-order sections. Their coefficients are obtained by simple analytic expressions directly from the physical parameters of the tubular bell. © 2010 IEE
Keywords: Audio signal processing; Physical modeling; Sound synthesis; Virtual instruments

Turning Vector Partial Differential Equations into Multidimensional Transfer Function Models - Trautmann, Lutz; Rabenstein, Rudolf (Mathematical and Computer Modelling of Dynamical Systems, 2001)
Transfer function models for the description of physical systems have recently been introduced. They provide an alternative to the conventional representation by partial differential equations (PDE) and are suitable for computer implementation. This paper presents transfer function modelling for vector PDEs. They arise from the physical analysis of multidimensional systems in terms of potential and flux quantities. Expressing the resulting coupled PDEs in vector form facilitates the direct formulation of boundary and interface conditions in their physical context. It is shown how a carefully constructed transformation for the space variable leads to transfer function models for vector PDEs. They are the starting point for the derivation of discrete models by standard methods for one-dimensional systems. The presented functional transformation approach is suitable for a number of technical applications, like electromagnetics, optics, acoustics and heat and mass transfer. Examples are given for the voltage and current distribution on an electrical transmission line and the velocity and force distribution on longitudinal vibrating strings.
Keywords: 35C05; 35L05; 35L45; 35L50; 35P05; 42C15; 44A10; 44A30; 65N25; 65R10; 93A30; 93C20; 93C80

Turning Vector Partial Differential Equations into Multidimensional Transfer Function Models - Trautmann, Lutz; Rabenstein, Rudolf (Proc. Third Intern. Symposium on Mathematical Modelling, 2000)
LMS::131

TWO-dimensional block based physical modeling with the functional transformation method - Petrausch, Stefan; Rabenstein, Rudolf (4th International Workshop on Multidimensional Systems, NDS 2005, 2005)
The Functional Transformation Method (FTM) is a mathematical founded method for the solution of multi- dimensional initial boundary value problems. It is based on suitable problem-specific integral transformations, that yield a transfer function model (TFM) in both, space and time frequency domain. This TFM can be discretized and, after inverse transformation, realized on computer hardware. The boundary conditions are so far inherently included in the solution. Slight changes in type or form always require a complete reanalysis. Therefore in this paper a new block-based approach for two-dimensional regions is presented, where the complete model is subdivided into smaller regions. These smaller models are solved independently with the FTM and are merged again in the discrete system. The complete procedure is demon-strated and illustrated with the two-dimensional wave equation.

Two-dimensional wave field decomposition using circular microphone arrays and its application to acoustic source localization - Teutsch, Heinz; Kellermann, Walter (Acoustical Society of America, 2004)
LMS::524

Two-Stage Exclusion of Angular Intra Prediction Modes for Fast Mode Decision in HEVC - Heindel, Andreas; Pylinski, Christoph; Kaup, André (IEEE International Conference on Image Processing (ICIP), 2016)
The latest video compression standard HEVC sets new benchmarks concerning the efficiency for both video coding and also still image coding, i.e., pure intra picture coding. Nevertheless, its high complexity created by the rate-distortion optimization procedure is a serious drawback. To reduce this computational burden, several algorithms for fast mode decision have been proposed. However, most of these methods exclude modes based on analyzing the respective prediction errors. In this paper we present an algorithm for individual angular prediction mode exclusion which intervenes earlier, namely before prediction, almost solely based on the analysis of the reference samples. It is proposed to use this approach as an extension of the global angular intra mode exclusion scheme based on the reference samples from our previous work. The combined algorithm achieves average encoding time savings of approximately 25%, accompanied by only about 1.0% bit rate increas
Keywords: HEVC; intra prediction; mode exclusion; fast mode decision; angular modes

Unbiased coherent-to-diffuse ratio estimation for dereverberation - Schwarz, Andreas; Kellermann, Walter (International Workshop on Acoustic Signal Enhancement (IWAENC), 2014)
We investigate the estimation of the time-and frequency-dependent coherent-to-diffuse ratio (CDR) from the measured spatial coherence between two omnidirectional microphones. We illustrate the relationship between several known CDR estimators using a geometric interpretation in the complex plane, discuss the problem of estimator bias, and propose unbiased versions of the estimators. Furthermore, we show that knowledge of either the direction of arrival (DOA) of the target source or the coherence of the noise field is sufficient for an unbiased CDR estimation. Finally, we apply the CDR estimators to the problem of dereverberation, using automatic speech recognition word error rate as objective performance measur
Keywords: Dereverberation; Diffuse Noise Suppression; Reverberation Suppression; Spatial Coherence

Uncertainty decoding for DNN-HMM hybrid systems based on numerical sampling - Hümmer, Christian; Maas, Roland; Schwarz, Andreas; Astudillo, Ramón Fernández; Kellermann, Walter (Annual Conference of the International Speech Communication Association (Interspeech), 2015)
In this article, we propose an uncertainty decoding scheme for DNN-HMM hybrid systems based on numerical sampling. A finite set of samples is drawn from the estimated probability distribution of the acoustic features and subsequently passed through feature transformations/extensions and the deep neural network (DNN). Then, the nonlinearly-transformed feature samples are averaged at the output of the DNN in order to approximate the posterior distribution of the context-dependent Hidden Markov Model (HMM) states. This concept is experimentally verified for the REVERB challenge task using a reverberation-robust DNN-HMM hybrid system: The numerical sampling is performed in the logmelspec domain, where we estimate the posterior distribution of the acoustic features by combining coherence-based Wiener filtering and uncertainty propagation. The experimental results highlight the good performance of the proposed uncertainty decoding scheme with significantly increased recognition accuracy even for a small number of feature sample
Keywords: Numerical sampling; Observation uncertainty; Robust speech recognition; Uncertainty decoding

Uncertainty Decoding for Reverberation-Robust Automatic Speech Recognition - Maas, Roland (Friedrich-Alexander-Universität Erlangen-Nürnberg, 2016)
The major problem in distant-talking speech recognition is the corruption of speech signals by both interfering sounds and reverberation. While a range of successful techniques has been developed since the beginnings of speech recognition research to combat additive and short convolutive noise, compensating for long-term distortion caused by reverberation has not gained wide attention until recently. This thesis further develops an uncertainty decoding approach, named REverberation MOdeling for Speech recognition (REMOS), to adapt the acoustic model of a conventional Hidden Markov Model-based recognizer to reverberant environments. By incorporating a convolutive observation model, the Viterbi decoder is extended in order to implicitly provide a state-wise late reverberation estimate leading to a relaxation of the hidden Markov models' conditional independence assumption. The experimental evaluation confirms that REMOS yields strong speech recognition performance under noisy and reverberant conditions and furthermore allows for a rapid adaptation to changing acoustic condition

Uncertainty decoding using a sampling strategy based on the eigenvalue decomposition - Hümmer, Christian; Stadter, Philipp; Kellermann, Walter (12th ITG Symposium on Speech Communication, 2016)
Uncertainty decoding combines a probabilistic distortion model with the acoustic model of a speech recognition system. This can be realized for DNN-based acoustic models by drawing feature samples from an estimated probability distribution and averaging the resulting set of posterior likelihoods at the output of the DNN. According to this principle, we consider a probabilistic feature description in the logmelspec domain to model the front-end estimation errors produced by a coherence-based Wiener filter. As main innovation with respect to previous work, we employ a sampling strategy based on the eigenvalue decomposition to capture (instead of neglect) the cross-correlations between the acoustic features as part of the uncertainty decoding scheme. The experimental results for real recordings provided by the REVERB Challenge task highlight the effectiveness of this sampling strategy in improving the recognition accuracy of a DNN-HMM hybrid syste
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Uncovered Background Prediction in an Object-Oriented Coding Environment - Kaup, André; Aach, T. (International Workshop on Coding Techniques for Very Low Bit-rate Video, Colchester, 1994)
LMS::1022

Underdetermined blind source separation of convolutive mixtures by hierarchical clustering and L1-norm minimization - Winter, Stefan; Kellermann, Walter; Sawada, H.; Makino, Shoji (Blind Speech Separation, 2007)
In this chapter we present a complete solution for underdetermined blind source separation (BSS) of convolutive speech mixtures based on two stages. In the first stage, the mixing system is estimated, for which we employ hierarchical clustering. Based on the estimated mixing system, the source signals are estimated in the second stage. The solution for the second stage utilizes the common assumption of independent and identically distributed sources. Modeling the sources by a Laplacian distribution leads to ℓ1-norm minimization.©Spring

Underdetermined source separation for colored sources - Winter, Stefan; Kellermann, Walter; Sawada, H.; Makino, Shoji (14th European Signal Processing Conference, EUSIPCO 2006, 2006)
This contribution focuses on the source separation stage as important part of underdetermined blind source separation (BSS). So far nearly all approaches for underdetermined BSS assume independently, identically distributed (i.i.d.) sources. They completely ignore the redundancy that is in the temporal structure of colored sources like speech signals. Instead, we propose multivariate models based on the multivariate Student's t or multivariate Gaussian distribution and investigate their potential for underdetermined BSS. We provide a simple yet effective filter based on the sources' autocorrelations for recovering the sources as basis for further advances in underdetermined BSS. The challenge is estimating the filter coefficients blindly. The experimental results support the idea that source separation for underdetermined BSS can be reduced to the separation of their autocorrelation

Universal Synchronization Scheme for Distributed Audio-Video Capture on Heterogeneous Computing Platforms - Lienhart, R.; Kozintsev, I.; Wehr, Stefan (Proceedings of the eleventh ACM international conference on Multimedia, 2003)
LMS::495

Using Artificially Reverberated Training Data in Distant-Talking ASR - Haderlein, Tino; Nöth, Elmar; Herbordt, Wolfgang; Kellermann, Walter; Niemann, Heinrich (Text, Speech and Dialogue; 8th International Conference TSD 2005, 2005)

Validation of a Rawdata-based Synchronization Signal (Kymogram) for a Phase-Correlated Cardiac Image Reconstruction - Ertel, D.; Pflederer, T.; Achenbach, S.; Kachelrieß, M.; Steffen, Peter; Kalender, W. A. (European Radiology, 2006)
Phase-correlated reconstruction is commonly used in computed tomography (CT)-based cardiac imaging. Alternatively to the commonly used ECG, the raw data-based kymogram function can be used as a synchronization signal. We used raw data of 100 consecutive patient exams to compare the performance of kymogram function to the ECG signal. For objective validation the correlation of the ECG and the kymogram was assessed. Additionally, we performed a double-blinded comparison of ECG-based and kymogram-based phase-correlated images. The two synchronization signals showed good correlation indicated by a mean difference in the detected heart rate of negligible 0.2 bpm. The mean image quality score was 2.0 points for kymogram-correlated images and 2.3 points for ECG-correlated images, respectively (3: best; 0: worst). The kymogram and the ECG provided images adequate for diagnosis for 93 and 97 patients, respectively. For 50% of the datasets the kymogram provided an equivalent or even higher image quality compared with the ECG signal. We conclude that an acceptable image quality can be assured in most cases by the kymogram. Improvements of image quality by the kymogram function were observed in a noticeable number of cases. The kymogram can serve as a backup solution when an ECG is not available or lacking in quality. © European Society of Radiology 20
LMS::709

Variable Blocksize Transform Coding of Four-Color Printed Images - Kaup, André; Aach, T. (Visual Communication and Image Processing, Boston, Mass., SPIE, 1991)
LMS::1014

Variational EM for binaural sound-source separation and localization - Deleforge, Antoine; Forbes, Florence; Horaud, Radu (IEEE International Conference on Acoustics, Speech and Signal Processing, 2013)
The sound-source separation and localization (SSL) problems are addressed within a unified formulation. Firstly, a mapping between white-noise source locations and binaural cues is estimated. Secondly, SSL is solved via Bayesian inversion of this mapping in the presence of multiple sparse-spectrum emitters (such as speech), noise and reverberations. We propose a variational EM algorithm which is described in detail together with initialization and convergence issues. Extensive real-data experiments show that the method outperforms the state-of-the-art both in separation and localization (azimuth and elevation
LMS::1516

Very Low Bit-Rate Video Coding Using 3-D Models - Eisert, Peter (Friedrich-Alexander-Universität Erlangen-Nürnberg, 2000)

Video analysis for universal multimedia messaging - Kaup, André; Treetasanatavorn, Siripong; Rauschenbach, U.; Heuer, J. (5th IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2002, 2002)
Multimedia messaging is expected to become a major application for next generation mobile computing and communication devices. Heterogeneous capabilities of these devices, however require adaptation of multimedia messages before rendering on any specific device. To achieve this in case of video messages, video analysis has to be performed to extract the structure of the video and control the message adaptation. This paper describes the universal multimedia messaging scenario and presents a short overview of existing video structuring approaches. A computationally efficient method for analyzing a video message in this scenario is introduced and a prototype for universal multimedia messaging conforming to the emerging MPEG-7 standard is outlined.
Keywords: Computer networks; Discrete cosine transforms; Image segmentation; Mobile communication; Mobile computing; MPEG 7 Standard; Multimedia computing; Multimedia systems; Prototypes; Video compression

Video Coding for Machines with Feature-Based Rate-Distortion Optimization - Fischer, Kristian; Brand, Fabian; Herglotz, Christian; Kaup, André (IEEE International Workshop on Multimedia Signal Processing (MMSP), 2020)
Common state-of-the-art video codecs are optimized to deliver a low bitrate by providing a certain quality for the final human observer, which is achieved by rate-distortion optimization (RDO). But, with the steady improvement of neural networks solving computer vision tasks, more and more multimedia data is not observed by humans anymore, but directly analyzed by neural networks. In this paper, we propose a standard-compliant feature-based RDO (FRDO) that is designed to increase the coding performance, when the decoded frame is analyzed by a neural network in a video coding for machine scenario. To that extent, we replace the pixel-based distortion metrics in conventional RDO of VTM-8.0 with distortion metrics calculated in the feature space created by the first layers of a neural network. Throughout several tests with the segmentation network Mask R-CNN and single images from the Cityscapes dataset, we compare the proposed FRDO and its hybrid version HFRDO with different distortion measures in the feature space against the conventional RDO. With HFRDO, up to 5.49 % bitrate can be saved compared to the VTM-8.0 implementation in terms of Bjøntegaard Delta Rate and using the weighted average precision as quality metric. Additionally, allowing the encoder to vary the quantization parameter results in coding gains for the proposed HFRDO of up 9.95 % compared to conventional VTM.
Keywords: Video Coding for Machines; Rate-Distortion Optimization; R-CNN; Versatile Video Coding

Video Coding with Superimposed Motion-Compensated Signals - Flierl, Markus (Friedrich-Alexander-Universität Erlangen-Nürnberg, 2003)

Video Decoding Energy Estimation Using Processor Events - Herglotz, Christian; Kaup, André (IEEE International Conference on Image Processing (ICIP), 2017)
In this paper, we show that processor events like instruction counts or cache misses can be used to accurately estimate the processing energy of software video decoders. Therefore, we perform energy measurements on an ARM-based evaluation platform and count processor level events using a dedicated profiling software. Measurements are performed for various codecs and decoder implementations to prove the general viability of our observations. Using the estimation method proposed in this paper, the true decoding energy for various recent video coding standards including HEVC and VP9 can be estimated with a mean estimation error that is smaller than 6
Keywords: Decoding energy; instructions; HEVC; VP9; H.264

Video Decoding Energy Reduction Using Temporal-Domain Filtering - Herglotz, Christian; Kränzler, Matthias; Ludwig, Robert; Kaup, André (First International Workshop on Green Multimedia Systems (GMSys '23) on the ACM Multimedia Systems (MMSys), 2023)

Video Error Concealment Techniques for Multi-Broadcast Reception of Digital TV, Audi-Dissertationsreihe, ISBN 978-3-95404-233-3 - Tröger, Tobias (Friedrich-Alexander-Universität Erlangen-Nürnberg, 2012)
The transmission of digital TV signals to mobile receivers is often error-prone. As most TV broadcasting techniques provide only moderate error robustness, horizontal lines of consecutive image blocks are lost during decoding of the received video signals. In order to ensure high viewing experiences, these lost slices have to be filled by error concealment techniques. However, the reconstruction qualities of classical approaches which exploit spatial, temporal, or spatio-temporal signal correlations are not convincing yet. In the future, mobile TV receivers will support different broadcasting techniques in parallel. As a result, an erroneous high-resolution video signal and a correctly received low-resolution video signal, both representing the same TV service, will often be available. Focusing on the outlined scenario for multi-broadcast reception of digital TV signals, this thesis introduces the novel category of inter-sequence error concealment algorithms. The basic idea is to fill lost slices of the high-resolution video signal by the interpolated low-resolution video signal. Since the images of this reference signal are often cropped and delayed, robust spatio-temporal image alignment is crucial. By including a pixel-based or a feature-based alignment scheme, the proposed concealment algorithms provide excellent visual qualities and outstanding reconstruction qualities of up to 41 dB PSNR. Classical concealment techniques are outperformed by up to 15 dB PSNR. To further enhance the reconstruction quality, several extensions are introduced. First, the alignment robustness and the interpolation quality are increased. Subsequently, a classical temporal approach is incorporated as an alternative concealment mode to cope with low image qualities of the reference signal. Novel aspects include robust mode selection, enhanced motion estimation, and the reconstruction of the displaced frame differences from the reference signal. As a last extension, spatial refinement tackles blurring of concealed image blocks. Missing spectral components are recovered in a frequency selective way based on approximation and extrapolation principles. By combining all relevant extensions, the PSNR gain adds up to 20 dB with respect to classical concealment. Finally, inter-sequence error concealment is adapted to multi-broadcast reception of two erroneous high-resolution video signals. While spatial alignment can be omitted, classical concealment of blocks, being lost in both video signals, and drift compensation in predictively-coded frames are novel aspects. Again, high visual qualities are obtained and classical concealment is outperformed by up to 15 dB PSN

Virtual Acoustics by Numerical Simulation - Spors, Sascha; Rabenstein, Rudolf (46th International Scientific Colloquium, 2001)
LMS::187

Visual Feature Discrimination versus Compression Ratio for Polygonal Shape Descriptors - Heuer, J.; Kaup, André (Internet Multimedia Management Systems, SPIE, 2000)
LMS::468

Volumetric deformation compensation in CUDA for coding of dynamic cardiac images - Weinlich, Andreas; Bätz, Michel; Amon, P.; Hutter, A.; Kaup, André (2013 Picture Coding Symposium, PCS 2013, 2013)
A new approach for volumetric deformation compensation in temporally predictive coding of dynamic medical heart images is presented. Instead of using conventional vectors, motion is represented by deformation values to model 3-D muscle contractions. In this way, estimated motion is more homogeneous among the image domain and predictions do not contain disturbing blocking artifacts making the approach suitable also for non-block-based transform coding. It is shown that with equal numbers of motion values the method can achieve prediction accuracies similar to cube-based motion estimation. The run time of the described parallel implementation in Nvidia CUDA is shown to be shorter than for an equivalent implementation of cube-based motion estimation. © 2013 IEE

Watermark Detection after Quantization Attacks - Eggers, Joachim; Girod, Bernd (Proceedings of the Third International Information Hiding Workshop, 1999)
LMS::296

Watermarking of MPEG-2 Encoded Video Without Decoding and Re-encoding - Hartung, Frank; Girod, Bernd (Proceedings Multimedia Computing and Networking (MMCN 97), 1997)
LMS::400

Watermarking of Uncompressed and Compressed Video - Hartung, Frank; Girod, Bernd (Signal Processing, 1998)
LMS::355

Wave-based and Geometric Representations of Sound Fields - Annibale, Paolo; Antonacci, Fabio; Canclini, Antonio; Rabenstein, Rudolf; Sarti, Augusto (9. ITG Fachtagung Sprachkommunikation, 2010)
The two main approaches for the description of sound fields are methods derived from solutions of the wave equation and geometric methods based on analogies to ray optics. Their mathematical representations are reviewed and it is shown that representations by projective geometry and descriptions by Fourier acoustics lead to similar parametric representations of sound field

Wave digital filters with multiple nonlinearities - Petrausch, Stefan; Rabenstein, Rudolf (12th European Signal Processing Conference, EUSIPCO 2004, 2004)
The wave digital filter (WDF) theory provides an elegant method for the discretization of linear continuous filters which is well known for possessing many desirable properties over other filter implementations. However, concerning nonlinear networks so far there are only solutions for circuits with a single nonlinearity, as the delay-free-feedback of the nonlinear element may result in delay-free-loops for multiple nonlinearities. In this paper we present a method to circumvent this problem by the introduction of a vector-nonlinearity. We show how to incorporate multiple nonlinear elements in a WDF structure and how to implement this method using the look-up-tables of the nonlinearities. This method of implementation is demonstrated for the scalar case by the well known Chua's circuit and for the vector case by a circuit with two real diodes.

Wave-domain adaptive filtering: Acoustic echo cancellation for full-duplex systems based on wave-field synthesis - Buchner, Herbert; Spors, Sascha; Kellermann, Walter (IEEE International Conference on Acoustics, Speech, and Signal Processing, 2004)
For high-quality multimedia communication systems such as teleconferencing or virtual reality applications, multichannel sound reproduction is highly desirable. While progress has been made in stereo and multichannel acoustic echo cancellation (MC AEC) in recent years, the corresponding sound reproduction systems still imply a restrained listening area ('sweet spot'). A volume solution for spatial sound in a large listening area is offered by wave field synthesis (WFS) or by ambisonics, where arrays of loudspeakers generate a prespecified sound field. However, before this new technique can be utilized for full-duplex systems, an efficient solution to the MC AEC problem has to be found. This paper presents a novel approach that extends the current state of the art of MC AEC and transform-domain adaptive filtering by reconciling the flexibility of adaptive filtering and the underlying physics of acoustic waves in a systematic and efficient way. To achieve this, the new framework of wave-domain adaptive filtering (WDAF) exploits the spatial information provided by densely sampled contours for both, recording and reproduction. Experimental results with a 32-channel AEC verify the concept for both, simulated and actually measured room acoustic

Wave-domain adaptive filtering for acoustic human-machine interfaces based onwavefield analysis and synthesis - Buchner, Herbert; Spors, Sascha; Herbordt, Wolfgang; Kellermann, Walter (12th European Signal Processing Conference, EUSIPCO 2004, 2004)
Wave field synthesis and wave field analysis are attractive techniques for high-quality sound-field auralization and recording using loudspeaker arrays and microphone arrays. However, to utilize these techniques in multichannel acoustic interfaces, several challenges in signal processing have to be overcome in this new context, e.g., acoustic echo cancellation (AEC) to avoid acoustic feedback in full-duplex systems, interference cancellation on the recording side, and room compensation on the reproduction side. In traditional setups, these problems are tackled using adaptive filtering techniques in the time-frequency domain. In this paper, we present a novel and highly efficient framework for adaptive filtering in the wave domain by reconciling the flexibility of adaptive filtering and the underlying physics described by the acoustic wave equation. The new framework explicitly takes into account the spatial dimensions of the closely spaced loudspeakers and the microphone arrays. Experimental results with a 32-channel AEC verify the concept for both, simulated and actually measured room acoustics.

Wave-domain loudspeaker signal decorrelation for system identification in multichannel audio reproduction scenarios - Schneider, Martin; Hümmer, Christian; Kellermann, Walter (IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2013)
For applications like acoustic echo cancellation (AEC) or listening room equalization (LRE), a loudspeaker-enclosure-microphone system (LEMS) must be identified. When using a large number of reproduction channels, as, e. g., for wave field synthesis (WFS) or Higher-Order Ambisonics (HOA), the strong correlation of the loud-speaker signals will hamper a unique identification. A state-of-the-art remedy against this so-called nonuniqueness problem is a decorrelation of the loudspeaker signals, which facilitates a unique identification. However, most of the known approaches are not suitable for acoustic wave field reproduction schemes, as they would distort the reproduced wave field in an uncontrolled manner or degrade the audio quality. In this contribution, we propose a wave-domain time-varying filtering of the loudspeaker signals, so that the reproduced wave field is rotated within a perceptually acceptable range, while preserving its shape. © 2013 IEE
Keywords: acoustic echo cancellation; decorrelation; Nonuniqueness problem; system identification; wave domain

Wave-domain transforms for irregular loudspeaker array topologies - Hofmann, Christian; Kellermann, Walter (Jahrestagung für Akustik (DAGA), 2015)
Today’s premium cars are typically equipped with a large number of loudspeakers and microphones to provide high-quality entertainment, hands-free communication via cellphones, and hands-free access to the applications running on the car’s head unit relying on a human/machine voice dialog. Especially for multichannel sound rendering, this requires multichannel Acoustic Echo Cancellation (AEC) systems. For lab environments, the concept of wave-domain AEC [1] proved to be an efficient solution for planar loudspeaker arrays by performing the adaptive filtering in a spatial transform domain. While acoustic systems typically show similarly strong couplings between all loudspeakers and all microphones, the wave-domain couplings between loudspeaker modes and microphone modes decrease with increasing difference between mode orders [1]. This prior knowledge can be exploited for improved system identification and reduced computational complexity by modeling only a subset of couplings in the spatial transform domai

Wave field analysis using multiple radii measurements - Kuntz, Achim; Rabenstein, Rudolf (2009 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2009, 2009)
Wave field analysis of stationary sound fields can be performed with high spatial resolution when sequential measurements on a circle are employed. Applying a circular harmonics decomposition to wideband audio data requires a careful setup of the measurement process to avoid noise amplification at certain frequencies. To this end, measurements with several microphones at multiple radii are considered here. Three mathematically well-founded strategies to combine their measurement signals are compared regarding the resulting noise amplification. ©2009 IEE
Keywords: Circular harmonics; Maximum ratio combining; Noise amplification; Selection combining; Wave field analysis

Wave Field Analysis Using Virtual Circular Microphone Arrays, PhD thesis - Kuntz, Achim (Friedrich-Alexander-Universität Erlangen-Nürnberg, 2009)

Wave field cancellation using wave-domain adaptive filtering - Herbordt, Wolfgang; Nakamura, S.; Spors, Sascha; Buchner, Herbert; Kellermann, Walter (Conf. Rec. Joint Workshop for Hands-Free Speech Communication and Microphone Arrays (HSCMA), 2005)
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Wavefield Decomposition Using Microphone Arrays and Its Application to Acoustic Scene Analysis - Teutsch, Heinz (Friedrich-Alexander-Universität Erlangen-Nürnberg, 2006)
Many applications of acoustic signal processing, such as teleconferencing and surveillance systems, require an estimate of several parameters present in the observed acoustic scene. The most important parameters are the location of the acoustic sources as well as the number of currently active sources. These parameters have been traditionally estimated by means of classical array signal processing using microphone arrays. The term 'classical' is used here to classify algorithms that are derived from the microphone signals directly. In contrast, the algorithms presented in this thesis are not solely based on classical array signal processing but also on the principles of wave propagation and wave scattering offered by the science of classical acoustics. Novel so-called modal array signal processing algorithms can now be derived from the fundamental solutions of the acoustic wave equation. Algorithms for parameter estimation solely based on the paradigm of classical array signal processing, often suffer from the problem that they rely on a narrowband assumption underlying the signal model, which limit their usability when broadband signals, such as speech, are present in the wavefield under observation. It will be shown that by additionally considering the paradigm of classical acoustics, algorithms can be derived that are inherently broadband, hence allowing for ubiquitous application. Moreover, it will be shown that parameter estimation, based on these novel methods, has the potential to unambiguously detect and localize multiple simultaneously active wideband sources in the array's full field-of-view. In order to take advantage of the paradigms that can be found in the field of acoustics, special array geometries are considered here, i.e. circular and spherical geometries for the analysis of wave propagation in two and three spatial dimensions, respectively. A rigorous derivation of modal array signal processing algorithms for parameter estimation as well as performance evaluations by means of simulations and measurements using an actual real-time capable implementation are presente

Wave field simulation with the functional transformation method - Petrausch, Stefan; Rabenstein, Rudolf (2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006, 2006)
The Functional Transformation Method (FTM) provides a frequency domain based analytic solution of arbitrary linear partial differential equation. For wave field simulations however, its application was so far restricted to simple geometries as the FTM involves a search for the eigenmodes of the model. Recently so called block based modeling algorithms were introduced, that follow a divide-and-conquer approach. A complex geometry is split into several simple elementary blocks. These blocks are solved and discretized separately, while their connection is realized in the discrete system during run-time. In this paper a 2D wave field simulation program based on block based modeling is demonstrated. Elementary block models are solved with the FTM and can be connected together to create complex 2D geometries. The complete system benefits from the advantages of the FTM (e.g. dispersionfree simulations), while the complexity of the geometry fits the needs of typical CAD drawings. © 2006 IEE

Wave Field Synthesis Techniques for Spatial Sound Reproduction - Rabenstein, Rudolf; Spors, Sascha; Steffen, Peter (Topics in Acoustic Echo and Noise Control, 2006)

Wavelet-Analysis of Meteorological Data - Rabenstein, Rudolf; Bartosch, Thorsten (Proc. 10. Internationales Sonnenforum (EuroSun'96), 1996)
LMS::1666

Wavelet-based multi-view video coding with full scalability and illumination compensation - Garbas, Jens-Uwe; Fecker, Ulrich; Kaup, André (15th ACM International Conference on Multimedia, MM'07, 2007)
A wavelet-based approach to scalable multi-view video coding (MVC) is examined in this paper. A 4-D wavelet transform is used to decorrelate the multi-view video data temporally, view-directionally, and spatially for efficient compression. Motion compensated temporal filtering (MCTF) is applied to each video sequence of each camera to exploit temporal correlation and inter-view dependencies are exploited with disparity compensated view filtering (DCVF). Together with a 2-D spatial wavelet transform the 4-D wavelet transform is constituted. The open-loop structure of the decomposition, together with embedded quantization and coding, allows for the construction of a bitstream which is fully scalable in temporal, view-directional, spatial and quality dimension. Results for scalable decoding in all dimensions are given, as well as comparisons to simulcast coding and state-of-the-art non-scalable multi-view video coding. Further, a significant coding gain is shown when the sequences are pre-processed with an algorithm for cross-view illumination compensation based on histogram matching. Copyright 2007 AC
Keywords: Algorithms; Experimentation

Wavelet-based multi-view video coding with joint best basis wavelet packets - Garbas, Jens-Uwe; Trocan, M.; Pesquet-Popescu, B.; Kaup, André (2008 IEEE International Conference on Image Processing, ICIP 2008, 2008)
An approach to scalable multi-view video coding with joint best basis wavelet packets is examined in this paper. A 4-D wavelet transform is used to decorrelate the multi-view video data temporally, view-directionally, and spatially for efficient scalable compression. Motion Compensated Temporal Filtering (MCTF) is used for temporal, and disparity compensated view filtering (DCVF) for view-directional decomposition. Adaptive wavelet packets as a generalized wavelet decomposition are presented for spatial decomposition. Two algorithms to find the best basis wavelet packets are evaluated and compared with classical dyadic wavelet transform: a low complexity entropy based best basis search and a search algorithm in a rate-distortion framework. In both cases, the joint best basis is determined for a group of frames rather than for each frame individually. Therefore, the rate to spend for the tree description is minimal while advantage is taken of the similarity of frames within a temporal-view-directional subband. © 2008 IEE
Keywords: Multi-view; Video coding; Wavelet packets

Wavelet-based multi-view video coding with spatial scalability - Garbas, Jens-Uwe; Kaup, André (2007 IEEE 9Th International Workshop on Multimedia Signal Processing, MMSP 2007, 2007)
In this paper, we propose two wavelet-based frameworks which allow fully scalable multi-view video coding. Using a 4-D wavelet transform, both schemes generate a bitstream that can be truncated to achieve a temporally, view-directionally, and/or spatially downscaled representation of the coded multi-view video sequence. Well-known wavelet-based scalable coding schemes for single-view video sequences have been adopted and extended to match the specific needs of scalable multi-view video coding. Motion compensated temporal filtering (MCTF) is applied to each video sequence of each camera to exploit temporal correlation and inter-view dependencies are exploited with disparity compensated view filtering (DCVF). A spatial wavelet transform is utilized either before and after temporal-view-directional decomposition (2D+T+V+2D scheme) or only after the temporal-view-directional decomposition (T+V+2D scheme) for spatial decorrelation. The influence of the two different approaches on spatial scalability is shown in this paper as well as the superior coding efficiency of both codecs compared with simulcast coding. © 2007 IEE

Wavelet Coherence Analysis of Broadband Array Data Recorded at Stromboli Volcano - Bartosch, Thorsten; Wassermann, Joachim (Bulletin of the Seismological Society of America, 2004)
LMS::504

Weakly Supervised Multi-Modal 3D Human Body Pose Estimation for Autonomous Driving - Bauer, Peter; Bouazizi, Arij; Kressel, Ulrich; Flohr, Fabian B. (IEEE Intelligent Vehicles Symposium, Proceedings, 2023)
Accurate 3D human pose estimation (3D HPE) is crucial for enabling autonomous vehicles (AVs) to make informed decisions and respond proactively in critical road scenarios. Promising results of 3D HPE have been gained in several domains such as human-computer interaction, robotics, sports and medical analytics, often based on data collected in well-controlled laboratory environments. Nevertheless, the transfer of 3D HPE methods to AVs has received limited research attention, due to the challenges posed by obtaining accurate 3D pose annotations and the limited suitability of data from other domains.We present a simple yet efficient weakly supervised approach for 3D HPE in the AV context by employing a high-level sensor fusion between camera and LiDAR data. The weakly supervised setting enables training on the target datasets without any 2D / 3D keypoint labels by using an off-the-shelf 2D joint extractor and pseudo labels generated from LiDAR to image projections. Our approach outperforms state-of-the-art results by up to 13% on the Waymo Open Dataset in the weakly supervised setting and achieves state-of-the-art results in the supervised setting.
CRIS-Team Scopus Importer:2023-08-25
Keywords: Autonomous Driving; Computer Vision; Human Pose Estimation; Sensor Fusion

Weakly Supervised Sound Activity Detection and Event Classification in Acoustic Sensor Networks - Ebbers, Janek; Drude, Lukas; Haeb-Umbach, Reinhold; Brendel, Andreas; Kellermann, Walter (IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2019)

Why B-Pictures Work: A Theory of Multi-Hypothesis Motion-Compensated Prediction - Girod, Bernd (Int. Conf. on Imag. Proc., 1998)
LMS::342

Wideband algorithms versus narrowband algorithms for adaptive filtering in the DFT domain - Kellermann, Walter; Buchner, Herbert (Conference Record of the Thirty-Seventh Asilomar Conference on Signals, Systems and Computers, 2003)
Adaptive filtering in the DFT domain is popular for its computational efficiency and its attractive convergence properties resulting from the applicability of the FFT and separate adaptation of individual DFT bins. Narrowband algorithms assume a complete decoupling of different frequency bins, which corresponds to assuming a circulant structure for the input data matrix. Wideband designs account for the difference between the actual Töplitz structure and the circulant structure by introducing additional constraints. In this contribution, we show that a wideband approach with rigorous implementation of appropriate constraints leads to highly efficient algorithms with excellent convergence properties. As examples we consider multichannel acoustic echo cancellation (MC-AEC) and blind source separation (BSS) of convolutive mixtures.

Wideband and Isotropic Room Acoustics Simulation Using 2-D Interpolated FDTD Schemes - Kowalczyk, Konrad; van Walstijn, M. (IEEE Transactions on Audio Speech and Language Processing, 2010)
In this paper, a complete method for finite-difference time-domain modeling of rooms in 2-D using compact explicit schemes is presented. A family of interpolated schemes using a rectilinear, nonstaggered grid is reviewed, and the most accurate and isotropic schemes are identified. Frequency-dependent boundaries are modeled using a digital impedance filter formulation that is consistent with locally reacting surface theory. A structurally stable and efficient boundary formulation is constructed by carefully combining the boundary condition with the interpolated scheme. An analytic prediction formula for the effective numerical reflectance is given, and a stability proof provided. The results indicate that the identified accurate and isotropic schemes are also very accurate in terms of numerical boundary reflectance, and outperform directly related methods such as Yee's scheme and the standard digital waveguide mesh. In addition, one particular scheme-referred to here as the interpolated wideband scheme-is suggested as the best scheme for most application
LMS::936
Keywords: acoustic impedance; acoustic propagation; acoustic signal processing; architectural acoustics; digital filters; finite-difference time-domain (FDTD) methods

Widely-linear Transceiver Design for Interference Alignment - Ilyas, Rameez (Friedrich-Alexander-Universität Erlangen-Nürnberg, 2014)

Wissenschaftliches Rechnen im World Wide Web - Rabenstein, Rudolf (Proc. Simulation und Visualisierung 98, 1998)
LMS::319

WOZ Acoustic Data Collection for Interactive TV - Brutti, A.; Cristoforetti, L.; Kellermann, Walter; Marquardt, Lutz; Omologo, M. (Language Resources and Evaluation, 2008)
This paper describes a multichannel acoustic data collection recorded under the European DICIT project, during Wizard of Oz (WOZ) experiments carried out at FAU and FBK-irst laboratories. The application of interest in DICIT is a distant-talking interface for control of interactive TV working in a typical living room, with many interfering devices. The objective of the experiments was to collect a database supporting efficient development and tuning of acoustic processing algorithms for signal enhancement. In DICIT, techniques for sound source localization, multichannel acoustic echo cancellation, blind source separation, speech activity detection, speaker identification and verification as well as beamforming are combined to achieve a maximum possible reduction of the user speech impairments typical of distant-talking interfaces. The collected database permitted to simulate at preliminary stage a realistic scenario and to tailor the involved algorithms to the observed user behaviors. In order to match the project requirements, the WOZ experiments were recorded in three languages: English, German and Italian. Besides the user inputs, the database also contains non-speech related acoustic events, room impulse response measurements and video data, the latter used to compute three-dimensional positions of each subject. Sessions were manually transcribed and segmented at word level, introducing also specific labels for acoustic events. ©Spring
LMS::835

WOZ acoustic data collection for interactive TV - Brutti, Alessio; Cristoforetti, Luca; Kellermann, Walter; Marquardt, Lutz; Omologo, Maurizio (Language Resources and Evaluation, 2010)
This paper describes a multichannel acoustic data collection recorded under the European DICIT project, during Wizard of Oz (WOZ) experiments carried out at FAU and FBK-irst laboratories. The application of interest in DICIT is a distant-talking interface for control of interactive TV working in a typical living room, with many interfering devices. The objective of the experiments was to collect a database supporting efficient development and tuning of acoustic processing algorithms for signal enhancement. In DICIT, techniques for sound source localization, multichannel acoustic echo cancellation, blind source separation, speech activity detection, speaker identification and verification as well as beamforming are combined to achieve a maximum possible reduction of the user speech impairments typical of distant-talking interfaces. The collected database permitted to simulate at preliminary stage a realistic scenario and to tailor the involved algorithms to the observed user behaviors. In order to match the project requirements, the WOZ experiments were recorded in three languages: English, German and Italian. Besides the user inputs, the database also contains non-speech related acoustic events, room impulse response measurements and video data, the latter used to compute three-dimensional positions of each subject. Sessions were manually transcribed and segmented at word level, introducing also specific labels for acoustic events. © 2010 Springer Science+Business Media B.
Keywords: Audio; Corpus annotation; Multimodal

Zeit-Frequenzanalyse nichtstationärer vulkanischer Tremorsignale - Bartosch, Thorsten (Friedrich-Alexander-Universität Erlangen-Nürnberg, 2000)

Zusammenhänge zwischen wellen- und geometrie-basierten Darstellungen von Schallfeldern - Annibale, Paolo; Rabenstein, Rudolf (36. Deutsche Jahrestagung für Akustik (DAGA 2010), 2010)

Diskrete Simulation linearer mehrdimensionaler kontinuierlicher Systeme - Rabenstein, Rudolf (Friedrich-Alexander-Universität Erlangen-Nürnberg, 1991)

Helical Cone-Beam Computed Tomography using the Differentiated Backprojection - Schöndube, Harald (Friedrich-Alexander-Universität Erlangen-Nürnberg, 2010)
This thesis examines the use of the differentiated backprojection (DBP) with subsequent inverse Hilbert transform (HT), which is a theoretically-exact and stable (TES) reconstruction algorithm, for helical cone-beam computed tomography. Special attention in this examination is attributed to the question if the method is suitable to process redundant data, i.e., data which have been measured but which are not necessary to achieve a TES reconstruction. Helical cone-beam CT has been chosen as an application because it is the scanning technique most common in modern CT scanners and because it requires new image reconstruction algorithms to account for the ongoing growth of CT detectors in terms of detector rows. The first part of the thesis introduces the DBP-HT method in two and three dimensions and gives all relevant proofs. It also contains a section of original work about different strategies of computing a finite inverse Hilbert transform using Söhngen's formula on discrete data. The second part of the thesis comprises three chapters presenting original research: First, the general properties of the DBP-HT method are examined and different implementation strategies are compared. Subsequently, a new algorithm is introduced, which allows for the first time to perform a TES reconstruction while beneficially including all measured data at maximum pitch. Finally we present an extension of this algorithm which enables TES reconstruction using all data at arbitrary pitch. The thesis concludes with a discussion of the results and an outlook onto possible further work. <br

Informationstheoretische Grenzen optischer 3D-Sensoren - Wagner, C. (Friedrich-Alexander-Universität Erlangen-Nürnberg, 2003)

Iterative Rekonstruktion in der Medizinischen Bildverarbeitung - Kunze, H. (Friedrich-Alexander-Universität Erlangen-Nürnberg, 2007)
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Recent Trends in Early Detection of Ocular Disorders Using Image Processing, Signal Processing, Quantum Models and Related Approaches - Das, Saumodip; Bose, Soumalya; Mitra, Saikat; Sen, Anindya (2023 7th International Conference on Electronics, Materials Engineering and Nano-Technology, IEMENTech 2023, 2023)
Ocular disorders like refractive errors, cataract, diabetic retinopathy, glaucoma and age-related macular degeneration are the major causes of blindness worldwide. Due to expensive medical equipments/procedures and disproportionate doctor to patient ratio, early diagnosis of ocular disorders is cumbersome; motivating researchers to automate the early detection process. In this review paper, the authors have briefed about some noteworthy attempts towards early detection of ocular disorder. This paper contains review on: focal biologically inspired feature(BIF) for Glaucoma Detection, three image processing techniques for glaucoma detection, BIF for peripapillary atrophy(PPA) detection, automatic method to find thickness of retinal nerve fibre layer(RFNL) from OCT images, computer aided retinal fundus image analysis scheme, discrete wavelet based glaucoma diagnosis, novel image processing method for glaucoma detection, algorithm based on Cup to Disc Ratio for glaucoma detection, Fuzzy expert system for glaucoma detection, computational tool for glaucoma detection, glaucoma detection approach using 1-D images, CNN based glaucoma detection framework, wavelet scattering based approach on fundus images, ensemble based deep learning method for identification and detection of glaucoma, comparative analysis of eight ImageNet models, cloud based framework for glaucoma screening, glaucoma detection using optimized algorithms like EPO & BFO, ImageNet based neural network classification model, intraocular pressure(IOP) based glaucoma detection and two quantum machine learning based approaches.
CRIS-Team Scopus Importer:2024-12-16
Keywords: bacterial foraging optimization (BFO); biologically inspired feature (BIF); emperor penguin optimization (EPO); image processing; ImageNet models; Ocular disorders; Quantum machine learning; wavelet-scattering

Reduction of Dominant Interference to Patient Speech Communication at Magnetic Resonance Tomography Systems - Friedrich, Marco (Friedrich-Alexander-Universität Erlangen-Nürnberg, 2013)
At current Magnetic Resonance (MR) scanners for medical imaging, understanding of patient’s speech via a communication system is significantly disturbed by intense acoustical noise, which is produced by the scanner during operation. This dissertation provides a detailed discussion of improvements to patient speech communication at MR systems and introduces a signal processing solution that achieves significant enhancement of patient speech intelligibility during MR imaging. Further, a modified Exponential Sine Sweep method is developed that reduces systematic errors of the original measurement method for nonlinear system characterization and parameter identification of nonlinear model

Simulation mehrdimensionaler Systeme mit Hilfe von Funktionaltransformationen - Rabenstein, Rudolf (Friedrich-Alexander-Universität Erlangen-Nürnberg, 1996)

Subjective and Objective Video Quality Measurement in Low-Bitrate Multimedia Scenarios - Barkowsky, Marcus (Friedrich-Alexander-Universität Erlangen-Nürnberg, 2009)
In recent years, many distribution channels for low-bitrate video transmissions were setup. The parameter settings for the encoder, the transmission channel, the decoder and the playback device are manifold. In order to maintain customer satisfaction, it is necessary to carefully select and continuously tune those parameters and to monitor the resulting video quality at the receiver. This thesis considers the quality measurement by a human observer and by an automated algorithm. In the first part of the thesis, several subjective tests are performed in order to draw conclusions about the choice of transmission parameters. The experience gained from those experiments led to three psychophysical experiments that focus on isolated aspects of the video quality in lossless or lossy low-bitrate transmissions. Three distinct algorithms are deduced from the subjective experiments which deal with the temporal aspects. First, the visibility of artifacts is modeled when the viewer only has a short period of time for the examination. Second, the influence of transmission outages is modeled: The video playback may pause and content may be skipped if retransmission is not possible. Third, the visual degradation introduced by a reduction of the frame rate is modeled. The second part of the thesis is dedicated to the objective measurement. It is assumed that the reference video sequence is available for comparison with the degraded sequence. Because the performance of the automated measurement depends strongly on the correct alignment of the degraded signal to the reference signal, various algorithms are reviewed, enhanced, and compared that locate the corresponding reference frame for a given degraded frame. So far, many algorithms have been published that reliably predict the visual quality of still images or temporally undistorted video sequences. In this thesis, a new framework is presented that allows to evaluate the performance of these algorithms for temporally distorted video transmissions. The processing steps and the signal representations follow the reasoning of a human observer in a subjective experiment as observed in the first part of the thesis. The improvements that can be achieved with the newly proposed framework are demonstrated by comparing the objective scores with the subjective results of the comprehensive Multimedia Phase I database of the Video Quality Experts Grou

Verfahren zur Beschreibung von Bild- und Videomerkmalen und deren Codierung - Heuer, J. (Friedrich-Alexander-Universität Erlangen-Nürnberg, 2004)