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2007
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Multi-Modal Particle Filtering Tracking using Appearance, Motion and Audio Likelihoods

10 years 11 months ago
Multi-Modal Particle Filtering Tracking using Appearance, Motion and Audio Likelihoods
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.
Matteo Bregonzio, Murtaza Taj, Andrea Cavallaro
Added 21 Oct 2009
Updated 21 Oct 2009
Type Conference
Year 2007
Where ICIP
Authors Matteo Bregonzio, Murtaza Taj, Andrea Cavallaro
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