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3D Skeleton-Based Body Pose Recovery

Clément Ménier 1, 2, * Edmond Boyer 1 Bruno Raffin 2 
* Corresponding author
1 MOVI - Modeling, localization, recognition and interpretation in computer vision
GRAVIR - IMAG - Laboratoire d'informatique GRAphique, VIsion et Robotique de Grenoble, Inria Grenoble - Rhône-Alpes, CNRS - Centre National de la Recherche Scientifique : FR71
2 MOAIS - PrograMming and scheduling design fOr Applications in Interactive Simulation
ID-IMAG - Informatique et Distribution, Inria Grenoble - Rhône-Alpes, UJF - Université Joseph Fourier - Grenoble 1
Abstract : This paper presents an approach to recover body motions from multiple views using a 3D skeletal model. It takes, as input, foreground silhouette sequences from multiple viewpoints, and computes, for each frame, the skeleton pose which best fit the body pose. Skeletal models encode mostly motion information and allows therefore to separate motion estimation from shape estimation for which solutions exist; And focusing on motion parameters significantly reduces the dependancy on specific body shapes, yielding thus more flexible solutions for body motion capture. However, a problem generally faced with skeletal models is to find adequate measurements with which to fit the model. In this paper, we propose to use the medial axis of the body shape to this purpose. Such medial axis can be estimated from the visual hull, a shape approximation which is easily obtained from the silhouette information. Experiments show that this approach is robust to several perturbations in the model or in the input data, and also allows fast body motions or, equivalently, important motions between consecutive frames.
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Submitted on : Tuesday, May 3, 2011 - 9:38:18 AM
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Clément Ménier, Edmond Boyer, Bruno Raffin. 3D Skeleton-Based Body Pose Recovery. 3rd International Symposium on 3D Data Processing, Visualization and Transmission (DPVT '06), Jun 2006, Chapel Hill, United States. pp.389--396, ⟨10.1109/3DPVT.2006.7⟩. ⟨inria-00590212⟩



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