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International Conference on Scale Space and Variational Methods in Computer Vision

SSVM 2011: Scale Space and Variational Methods in Computer Vision pp 725–736Cite as

Group-Valued Regularization Framework for Motion Segmentation of Dynamic Non-rigid Shapes

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6667))

Abstract

Understanding of articulated shape motion plays an important role in many applications in the mechanical engineering, movie industry, graphics, and vision communities. In this paper, we study motion-based segmentation of articulated 3D shapes into rigid parts. We pose the problem as finding a group-valued map between the shapes describing the motion, forcing it to favor piecewise rigid motions. Our computation follows the spirit of the Ambrosio-Tortorelli scheme for Mumford-Shah segmentation, with a diffusion component suited for the group nature of the motion model. Experimental results demonstrate the effectiveness of the proposed method in non-rigid motion segmentation.

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Author information

Authors and Affiliations

  1. Dept. of Computer Science, Technion – Israel Institute of Technology, Haifa, 32000, Israel

    Guy Rosman & Ron Kimmel

  2. Institute of Computational Science, Faculty of Informatics, Universit della Svizzera italiana, CH - 6904, Lugano, Switzerland

    Michael M. Bronstein

  3. School of Electrical Engineering, Faculty of Engineering, Tel Aviv University, Ramat Aviv, 69978, Israel

    Alexander M. Bronstein

  4. Dept. of Mechanical Engineering, Technion – Israel Institute of Technology, Haifa, 32000, Israel

    Alon Wolf

  5. The Goldstein UAV and Satellite Center, Technion – Israel Institute of Technology, Haifa, 32000, Israel

    Alon Wolf & Ron Kimmel

Authors
  1. Guy Rosman
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  2. Michael M. Bronstein
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  3. Alexander M. Bronstein
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  4. Alon Wolf
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  5. Ron Kimmel
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Editor information

Editors and Affiliations

  1. Computer Science Department, Technion — Israel Institute of Technology, 718 Taub Building Technion, 32000, Haifa, Israel

    Alfred M. Bruckstein

  2. Department of Biomedical Engineering, Biomedical Image Analysis and Interpretation, Eindhoven University of Technology, Den Dolech 2 – WH 2.101, 5600 MB, Eindhoven, The Netherlands

    Bart M. ter Haar Romeny

  3. Faculaty of Engineering, School of Electrical Engineering, Tel Aviv University, Ramat Aviv, 69978, Israel

    Alexander M. Bronstein

  4. Institute of Computationa Science, Faculty of Informatics SI-109, Università della Svizzera Italiana, Via Giuseppe Buffi 13, 6904, Lugano, Switzerland

    Michael M. Bronstein

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Rosman, G., Bronstein, M.M., Bronstein, A.M., Wolf, A., Kimmel, R. (2012). Group-Valued Regularization Framework for Motion Segmentation of Dynamic Non-rigid Shapes. In: Bruckstein, A.M., ter Haar Romeny, B.M., Bronstein, A.M., Bronstein, M.M. (eds) Scale Space and Variational Methods in Computer Vision. SSVM 2011. Lecture Notes in Computer Science, vol 6667. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24785-9_61

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  • DOI: https://doi.org/10.1007/978-3-642-24785-9_61

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24784-2

  • Online ISBN: 978-3-642-24785-9

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