DocumentCode :
2826887
Title :
A Probabilistic Framework for Multi-modal Multi-Person Tracking
Author :
Checka, Neal ; Wilson, Kevin ; Rangarajan, Vibhav ; Darrell, Trevor
Author_Institution :
Massachusetts Institute of Technology
Volume :
9
fYear :
2003
fDate :
16-22 June 2003
Firstpage :
100
Lastpage :
100
Abstract :
In this paper, we present a probabilistic tracking framework that combines sound and vision to achieve more robust and accurate tracking of multiple objects. In a cluttered or noisy scene, our measurements have a non-Gaussian, multi-modal distribution. We apply a particle filter to track multiple people using combined audio and video observations. We have applied our algorithm to the domain of tracking people with a stereo-based visual foreground detection algorithm and audio localization using a beamforming technique. Our model also accurately reflects the number of people present. We test the efficacy of our system on a sequence of multiple people moving and speaking in an indoor environment.
Keywords :
Acoustic noise; Artificial intelligence; Filtering; Indoor environments; Laboratories; Layout; Microphone arrays; Particle filters; Particle tracking; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition Workshop, 2003. CVPRW '03. Conference on
Conference_Location :
Madison, Wisconsin, USA
ISSN :
1063-6919
Print_ISBN :
0-7695-1900-8
Type :
conf
DOI :
10.1109/CVPRW.2003.10099
Filename :
4624364
Link To Document :
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