Group-Valued Regularization for Analysis of Articulated Motion

  • Guy Rosman
  • Alex M. Bronstein
  • Michael M. Bronstein
  • Xue-Cheng Tai
  • Ron Kimmel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7583)


We present a novel method for estimation of articulated motion in depth scans. The method is based on a framework for regularization of vector- and matrix- valued functions on parametric surfaces.

We extend augmented-Lagrangian total variation regularization to smooth rigid motion cues on the scanned 3D surface obtained from a range scanner. We demonstrate the resulting smoothed motion maps to be a powerful tool in articulated scene understanding, providing a basis for rigid parts segmentation, with little prior assumptions on the scene, despite the noisy depth measurements that often appear in commodity depth scanners.


Parameteric Surfaces Motion Segmentation Articulated Motion 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Guy Rosman
    • 1
  • Alex M. Bronstein
    • 2
  • Michael M. Bronstein
    • 3
  • Xue-Cheng Tai
    • 4
  • Ron Kimmel
    • 1
  1. 1.Dept. of Computer ScienceTechnion - IITHaifaIsrael
  2. 2.School of Electrical Engineering Faculty of EngineeringTel Aviv UniversityRamat AvivIsrael
  3. 3.Institute of Computational Science, Faculty of InformaticsUniversitá della Svizzera ItalianaLuganoSwitzerland
  4. 4.Dept. of MathematicsUniversity of BergenBergenNorway

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