Bayesian integration of audio and visual information for multi-target tracking using a CB-member filter
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Date
2011
Authors
Hoseinnezhad, R.
Vo, B.
Vo, B.
Suter, D.
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Conference paper
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2011 IEEE International Conference on Acoustics, Speech, and Signal Processing : Proceedings, 2011: pp.2300-2303
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Reza Hoseinnezhad, Ba-Ngu Vo, Ba-Tuong Vo, David Suter
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IEEE International Conference on Acoustics, Speech and Signal Processing (36th : 2011 : Prague, Czech Republic)
Abstract
A new method is presented for integration of audio and visual information in multiple target tracking applications. The proposed approach uses a Bayesian filtering formulation and exploits multi-Bernoulli random finite set approximations. The work presented in this paper is the first principled Bayesian estimation approach to solve the sensor fusion problems that involve intermittent sensory data (e.g. audio data for a person who occasionally speaks.) We have examined our method with case studies from the SPEVI database. The results show nearly perfect tracking of people not only when they are silent but also when they are not visible to the camera (but speaking).
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Copyright ©2011 by the Institute of Electrical and Electronics Engineers, Inc. All rights reserved.