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International Conference on Advanced Concepts for Intelligent Vision Systems

ACIVS 2006: Advanced Concepts for Intelligent Vision Systems pp 287–298Cite as

Object Tracking Using Discriminative Feature Selection

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4179))

Abstract

This paper presents an approach for evaluating multiple color histograms during object tracking. The method adaptively selects histograms that well distinguish foreground from background. The variance ratio is utilized to measure the separability of object and background and to extract top-ranked discriminative histograms. Experimental results demonstrate how this method adapts to changing appearances of both object undergoing tracking and surrounding background. The advantages and limitations of the particle filter with embedded mechanism of histogram selection are demonstrated in comparisons with the standard CamShift tracker and a combination of CamShift with histogram selection.

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Author information

Authors and Affiliations

  1. Rzeszów University of Technology, W. Pola 2, 35-959, Rzeszów, Poland

    Bogdan Kwolek

Authors
  1. Bogdan Kwolek
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Editor information

Editors and Affiliations

  1. DGA/D4S/MRIS, 94114, Arcueil, France

    Jacques Blanc-Talon

  2. Ghent University, 9000, Gent, Belgium

    Wilfried Philips

  3. CSIRO ICT Centre, 1710, Sydney, NSW, Australia

    Dan Popescu

  4. University of Antwerp, 2610, Wilrijk, Belgium

    Paul Scheunders

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© 2006 Springer-Verlag Berlin Heidelberg

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Kwolek, B. (2006). Object Tracking Using Discriminative Feature Selection. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2006. Lecture Notes in Computer Science, vol 4179. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11864349_26

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  • DOI: https://doi.org/10.1007/11864349_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44630-9

  • Online ISBN: 978-3-540-44632-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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