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Asian Conference on Computer Vision

ACCV 2006: Computer Vision – ACCV 2006 pp 674–683Cite as

Multiregion Level Set Tracking with Transformation Invariant Shape Priors

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3851))

Abstract

Tracking of regions and object boundaries in an image sequence is a well studied problem in image processing and computer vision. So far, numerous approaches tracking different features of the objects (contours, regions or points of interest) have been presented. Most of these approaches have problems with robustness. Typical reasons are noisy images, objects with identical features or partial occlusions of the tracked features. In this paper we propose a novel level set based tracking approach, that allows robust tracking on noisy images. Our framework is able to track multiple regions in an image sequence, where a level set function is assigned to every region. For already known or learned objects, transformation invariant shape priors can be added to ensure a robust tracking even under partial occlusions. Furthermore, we introduce a simple decision function to maintain the desired topology for multiple regions. Experimental results demonstrate the method for arbitrary numbers of shape priors. The approach can even handle full occlusions and objects which are temporarily hidden in containers.

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Author information

Authors and Affiliations

  1. Institute of Electrical Measurement and Measurement Signal Processing, Graz University of Technology, Schießstattgasse 14b, 8010, Graz, Austria

    Michael Fussenegger & Axel Pinz

  2. INRIA, 2004 route des Lucioles, BP 93, 06902, Sophia Antipolis, France

    Rachid Deriche

Authors
  1. Michael Fussenegger
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  2. Rachid Deriche
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  3. Axel Pinz
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Editor information

Editors and Affiliations

  1. International Institute of Information Technology, Center for Visual Information Technology, Hyderabad, India

    P. J. Narayanan

  2. Department of Computer Science, Columbia University, 500 West 120th Street, 10027, New York, NY, USA

    Shree K. Nayar

  3. Microsoft Research Asia, Beijing, P.R. China

    Heung-Yeung Shum

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© 2006 Springer-Verlag Berlin Heidelberg

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Fussenegger, M., Deriche, R., Pinz, A. (2006). Multiregion Level Set Tracking with Transformation Invariant Shape Priors. In: Narayanan, P.J., Nayar, S.K., Shum, HY. (eds) Computer Vision – ACCV 2006. ACCV 2006. Lecture Notes in Computer Science, vol 3851. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11612032_68

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  • DOI: https://doi.org/10.1007/11612032_68

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-31219-2

  • Online ISBN: 978-3-540-32433-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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