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Efficient Articulated Trajectory Reconstruction Using Dynamic Programming and Filters

  • Jack Valmadre
  • Yingying Zhu
  • Sridha Sridharan
  • Simon Lucey
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7572)

Abstract

This paper considers the problem of reconstructing the motion of a 3D articulated tree from 2D point correspondences subject to some temporal prior. Hitherto, smooth motion has been encouraged using a trajectory basis, yielding a hard combinatorial problem with time complexity growing exponentially in the number of frames. Branch and bound strategies have previously attempted to curb this complexity whilst maintaining global optimality. However, they provide no guarantee of being more efficient than exhaustive search. Inspired by recent work which reconstructs general trajectories using compact high-pass filters, we develop a dynamic programming approach which scales linearly in the number of frames, leveraging the intrinsically local nature of filter interactions. Extension to affine projection enables reconstruction without estimating cameras.

Keywords

Basis Size Perspective Camera Articulation Constraint Trajectory Reconstruction Trajectory Basis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Jack Valmadre
    • 1
    • 3
  • Yingying Zhu
    • 2
    • 3
  • Sridha Sridharan
    • 1
  • Simon Lucey
    • 1
    • 3
  1. 1.Queensland University of TechnologyAustralia
  2. 2.University of QueenslandAustralia
  3. 3.Commonwealth Scientific and Industrial Research OrganisationAustralia

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