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Probabilistic Deformable Surface Tracking From Multiple Videos

Cedric Cagniart 1 Edmond Boyer 2 Slobodan Ilic 1 
2 PERCEPTION - Interpretation and Modelling of Images and Videos
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology
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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Submitted on : Wednesday, February 23, 2011 - 7:59:56 PM
Last modification on : Wednesday, May 4, 2022 - 9:56:04 AM
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Cedric Cagniart, Edmond Boyer, Slobodan Ilic. Probabilistic Deformable Surface Tracking From Multiple Videos. ECCV 2010 - 11th European Conference on Computer Vision, Sep 2010, Heraklion, Greece. pp.326-339, ⟨10.1007/978-3-642-15561-1_24⟩. ⟨inria-00568912⟩



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