2007 IEEE International Conference on Image Processing - San Antonio, Texas, U.S.A. - September 16-19, 2007

Technical Program

Paper Detail

Paper:WA-L2.1
Session:Video Object Segmentation and Tracking II
Time:Wednesday, September 19, 09:50 - 10:10
Presentation: Lecture
Title: MULTI-MODAL PARTICLE FILTERING TRACKING USING APPEARANCE, MOTION AND AUDIO LIKELIHOODS
Authors: Matteo Bregonzio; Queen Mary, University of London 
 Murtaza Taj; Queen Mary, University of London 
 Andrea Cavallaro; Queen Mary, University of London 
Abstract: We propose a multi-modal object tracking algorithm that combines appearance, motion and audio information in a particle filter. The proposed tracker fuses at the likelihood level the audio-visual observations captured with a video camera coupled with two microphones. Two video likelihoods are computed that are based on a 3D color histogram appearance model and on a color change detection, whereas an audio likelihood provides information about the direction of arrival of a target. The direction of arrival is computed based on a multi-band generalized cross-correlation function enhanced with a noise suppression and reverberation filtering that uses the precedence effect. We evaluate the tracker on single and multi-modality tracking and quantify the performance improvement introduced by integrating audio and visual information in the tracking process.



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