Joint audio-video object localization using a recursive multi-state multi-sensor estimator

Conference contribution
(Conference Contribution)


Publication Details

Author(s): Strobel N, Spors S, Rabenstein R
Publisher: IEEE
Publishing place: Piscataway, NJ, United States
Publication year: 2000
Volume: 4
Pages range: 2397-2400


Abstract


Object localization based on audio and video information is important for the analysis of dynamic scenes such as video conferences or traffic situations. In this paper, we view the dynamic audio-video object localization problem as a joint recursive estimation problem. It is solved using a decentralized Kalman filter fusing both audio and video position estimates. To better take into account different object maneuvers, multiple state-space equations are also incorporated. The result is a recursive multi-state multi-sensor estimator. Experiments show that it yields significantly improved joint position estimates compared to results achieved by using either an audio or a video system only.



FAU Authors / FAU Editors

Rabenstein, Rudolf Prof. Dr.
Lehrstuhl für Multimediakommunikation und Signalverarbeitung


External institutions
Siemens AG


How to cite

APA:
Strobel, N., Spors, S., & Rabenstein, R. (2000). Joint audio-video object localization using a recursive multi-state multi-sensor estimator. In Proceedings of the 2000 IEEE Interntional Conference on Acoustics, Speech, and Signal Processing (pp. 2397-2400). Istanbul, TR: Piscataway, NJ, United States: IEEE.

MLA:
Strobel, Norbert, Sascha Spors, and Rudolf Rabenstein. "Joint audio-video object localization using a recursive multi-state multi-sensor estimator." Proceedings of the 2000 IEEE Interntional Conference on Acoustics, Speech, and Signal Processing, Istanbul Piscataway, NJ, United States: IEEE, 2000. 2397-2400.

BibTeX: 

Last updated on 2019-03-06 at 07:11