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Article Dans Une Revue IEEE Transactions on Pattern Analysis and Machine Intelligence Année : 2009

Human Motion Tracking by Registering an Articulated Surface to 3-D Points and Normals

Résumé

We address the problem of human motion tracking by registering a surface to 3-D data. We propose a method that iteratively computes two things: Maximum likelihood estimates for both the kinematic and free-motion parameters of a kinematic human-body representation, as well as probabilities that the data are assigned either to a body part, or to an outlier cluster. We introduce a new metric between observed points and normals on one side, and a parameterized surface on the other side, the latter being defined as a blending over a set of ellipsoids. We claim that this metric is well suited when one deals with either visual-hull or visual-shape observations. We illustrate the method by tracking human motions using sparse visual-shape data (3-D surface points and normals) gathered from imperfect silhouettes.
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inria-00446898 , version 1 (13-01-2010)

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Radu Horaud, Matti Niskanen, Guillaume Dewaele, Edmond Boyer. Human Motion Tracking by Registering an Articulated Surface to 3-D Points and Normals. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009, 31 (1), pp.158-163. ⟨10.1109/TPAMI.2008.108⟩. ⟨inria-00446898⟩
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