Probabilistic Deformable Surface Tracking from Multiple Videos

  • Cedric Cagniart
  • Edmond Boyer
  • Slobodan Ilic
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6314)

Abstract

In this paper, we address the problem of tracking the temporal evolution of arbitrary shapes observed in multi-camera setups. This is motivated by the ever growing number of applications that require consistent shape information along temporal sequences. The approach we propose considers a temporal sequence of independently reconstructed surfaces and iteratively deforms a reference mesh to fit these observations. To effectively cope with outlying and missing geometry, we introduce a novel probabilistic mesh deformation framework. Using generic local rigidity priors and accounting for the uncertainty in the data acquisition process, this framework effectively handles missing data, relatively large reconstruction artefacts and multiple objects. Extensive experiments demonstrate the effectiveness and robustness of the method on various 4D datasets.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Cedric Cagniart
    • 1
  • Edmond Boyer
    • 2
  • Slobodan Ilic
    • 1
  1. 1.Technische Universität München 
  2. 2.Grenoble Universités - INRIA Rhône-Alpes 

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