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Multi-Modal Particle Filtering Tracking using Appearance, Motion and Audio Likelihoods | IEEE Conference Publication | IEEE Xplore

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


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 likeliho...Show More

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.
Date of Conference: 16 September 2007 - 19 October 2007
Date Added to IEEE Xplore: 12 November 2007
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Conference Location: San Antonio, TX, USA

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