Compressed domain moving object detection based on H.264/AVC macroblock types

Conference contribution
(Conference Contribution)


Publication Details

Author(s): Laumer M, Amon P, Hutter A, Kaup A
Publisher: SCITEPRESS
Publication year: 2013
Volume: 1
Pages range: 219-228
ISBN: 9789898565471
Language: English


Abstract


This paper introduces a low complexity frame-based object detection algorithm for H.264/AVC video streams. The method solely parses and evaluates H.264/AVC macroblock types extracted from the video stream, which requires only partial decoding. Different macroblock types indicate different properties of the video content. This fact is used to segment a scene in fore- and background or, more precisely, to detect moving objects within the scene. The main advantage of this algorithm is that it is most suitable for massively parallel processing, because it is very fast and combinable with several other pre- and post-processing algorithms, without decreasing their performance. The actual algorithm is able to process about 3600 frames per second of video streams in CIF resolution, measured on an Intel® Core™ i5-2520M CPU @ 2.5 GHz with 4 GB RAM.


FAU Authors / FAU Editors

Kaup, André Prof. Dr.-Ing.
Lehrstuhl für Multimediakommunikation und Signalverarbeitung
Laumer, Marcus
Lehrstuhl für Multimediakommunikation und Signalverarbeitung


How to cite

APA:
Laumer, M., Amon, P., Hutter, A., & Kaup, A. (2013). Compressed domain moving object detection based on H.264/AVC macroblock types. In Proceedings of the 8th International Conference on Computer Vision Theory and Applications, VISAPP 2013 (pp. 219-228). Barcelona, ES: SCITEPRESS.

MLA:
Laumer, Marcus, et al. "Compressed domain moving object detection based on H.264/AVC macroblock types." Proceedings of the 8th International Conference on Computer Vision Theory and Applications, VISAPP 2013, Barcelona SCITEPRESS, 2013. 219-228.

BibTeX: 

Last updated on 2019-24-04 at 19:23