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
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;
Conference_Titel :
Computer Vision and Pattern Recognition Workshop, 2003. CVPRW '03. Conference on
Conference_Location :
Madison, Wisconsin, USA
Print_ISBN :
0-7695-1900-8
DOI :
10.1109/CVPRW.2003.10099