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    Bayesian integration of audio and visual information for multi-target tracking using a CB-member filter

    Access Status
    Fulltext not available
    Authors
    Hoseinnezhad, R.
    Vo, Ba-Ngu
    Vo, Ba Tuong
    Suter, D.
    Date
    2011
    Type
    Conference Paper
    
    Metadata
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    Citation
    Hoseinnezhad, R. and Vo, B. and Vo, B.T. and Suter, D. 2011. Bayesian integration of audio and visual information for multi-target tracking using a CB-member filter, pp. 2300-2303.
    Source Title
    ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
    DOI
    10.1109/ICASSP.2011.5946942
    ISBN
    9781457705397
    School
    School of Electrical Engineering and Computing
    URI
    http://hdl.handle.net/20.500.11937/55473
    Collection
    • Curtin Research Publications
    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). © 2011 IEEE.

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