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    Visual Tracking of Numerous Targets via Multi-Bernoulli Filtering of Image Data

    Access Status
    Fulltext not available
    Authors
    Hoseinnezhad, R.
    Vo, Ba-Ngu
    Vo, Ba Tuong
    Suter, D.
    Date
    2012
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Hoseinnezhad, R. and Vo, B. and Vo, B.T. and Suter, D. 2012. Visual Tracking of Numerous Targets via Multi-Bernoulli Filtering of Image Data. Pattern Recognition. 45 (10): pp. 3625-3635.
    Source Title
    Pattern Recognition
    DOI
    10.1016/j.patcog.2012.04.004
    ISSN
    00313203
    URI
    http://hdl.handle.net/20.500.11937/45836
    Collection
    • Curtin Research Publications
    Abstract

    This paper presents a novel Bayesian method to track multiple targets in an image sequence without explicit detection. Our method is formulated based on finite set representation of the multi-target state and the recently developed multi-Bernoulli filter. Experimental results on sport player and cell tracking studies show that our method can automatically track numerous targets, and it outperforms the state-of-the-art in terms of false positive (false alarm) and false negative (missing) rates as detection error measures, and in terms of label switching rate and lost tracks ratio as tracking error measures.

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