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BAYESIAN INTEGRATION OF AUDIO AND VISUAL INFORMATION FOR MULTI-TARGET TRACKING USING A CB-MEMBER FILTER

Joint Audio Visual Processing

Full Paper at IEEE Xplore

Presented by: Reza Hoseinnezhad, Author(s): Reza Hoseinnezhad, RMIT University, Australia; Ba-Ngu Vo, Ba-Tuong Vo, The University of Western Australia, Australia; David Suter, The University of Adelaide, Australia

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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  Lecture Information

Recorded: 2011-05-24 17:55 - 18:15, Club H
Added: 9. 6. 2011 00:58
Number of views: 35
Video resolution: 1024x576 px, 512x288 px
Video length: 0:22:59
Audio track: MP3 [7.86 MB], 0:22:59