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Hierarchical Vibrations: A Structural Decomposition Approach for Image Analysis

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Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5681))

Abstract

We present results demonstrating that using a hierarchy of finite element vibration modes in an evolutionary deformable shape search provides a new interesting approach for the localization and segmentation of specific objects in 2D images. The design and coupling of the different levels of the shape hierarchy results in a multi–resolution shape space, which can be exploited in top–down part–based shape matching. The proposed strategy allows for segmenting complex objects from images, classification, as well as localization of the desired object under occlusions. It avoids misregistration by resolving several drawbacks inherent to standard shape–based approaches, which either cannot adequately represent non–linear variations, or rely on exhaustive prior training.

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Authors and Affiliations

  1. Dept. of Simulation and Graphics, Otto–von–Guericke University Magdeburg, Germany

    Karin Engel & Klaus D. Toennies

Authors
  1. Karin Engel
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  2. Klaus D. Toennies
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Editor information

Editors and Affiliations

  1. Institut für Informatik III, Rö, Universität Bonn, merstraße 164, 53117, Bonn, Germany

    Daniel Cremers

  2. Computer Science Department, University of Western Ontario, N6A 5A5, London, ON, Canada

    Yuri Boykov

  3. Microsoft Research, J.J. Thomson Avenue, CB3 OFB, Cambridge, United Kingdom

    Andrew Blake

  4. Institut für Informatik III, Universität Bonn, Römerstraße 164, 53117, Bonn, Germany

    Frank R. Schmidt

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© 2009 Springer-Verlag Berlin Heidelberg

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Engel, K., Toennies, K.D. (2009). Hierarchical Vibrations: A Structural Decomposition Approach for Image Analysis. In: Cremers, D., Boykov, Y., Blake, A., Schmidt, F.R. (eds) Energy Minimization Methods in Computer Vision and Pattern Recognition. EMMCVPR 2009. Lecture Notes in Computer Science, vol 5681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03641-5_24

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  • DOI: https://doi.org/10.1007/978-3-642-03641-5_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03640-8

  • Online ISBN: 978-3-642-03641-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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