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International Symposium on Visual Computing

ISVC 2007: Advances in Visual Computing pp 592–601Cite as

Object Tracking Via Uncertainty Minimization

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4842))

Abstract

Color and texture provide important visual information for real-time tracking of non-rigid and partially occluded objects. Recent developments have shown the robustness and effectiveness of color based tracking algorithms, especially for tracking tasks where object shape exhibits dramatic variability. In this article we solve the problem by tracking color distributions of background and foreground (object) points simultaneously. The key feature of our approach is careful selection of histogram resolution (or kernel radius) on each frame of a sequence.

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Authors and Affiliations

  1. Institute of Information Technologies, RRC “Kurchatov Institute”, 1 Kurchatov square, 123182 Moscow, Russia

    Albert Akhriev

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  1. Albert Akhriev
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Editor information

George Bebis Richard Boyle Bahram Parvin Darko Koracin Nikos Paragios Syeda-Mahmood Tanveer Tao Ju Zicheng Liu Sabine Coquillart Carolina Cruz-Neira Torsten Müller Tom Malzbender

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© 2007 Springer-Verlag Berlin Heidelberg

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Akhriev, A. (2007). Object Tracking Via Uncertainty Minimization. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2007. Lecture Notes in Computer Science, vol 4842. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76856-2_58

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  • DOI: https://doi.org/10.1007/978-3-540-76856-2_58

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-76855-5

  • Online ISBN: 978-3-540-76856-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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