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2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Tracking articulated bodies using Generalized Expectation Maximization
Anchorage, AK, USA
June 23-June 28
ISBN: 978-1-4244-2339-2
A. Fossati, CVLab, EPFL, Switzerland
E. Arnaud, Université Joseph Fourier, INRIA Rhone-Alpes, France
R. Horaud, Perception Group, INRIA Rhone-Alpes, France
P. Fua, CVLab, EPFL, Switzerland
A Generalized Expectation Maximization (GEM) algorithm is used to retrieve the pose of a person from a monocular video sequence shot with a moving camera. After embedding the set of possible poses in a low dimensional space using Principal Component Analysis, the configuration that gives the best match to the input image is held as estimate for the current frame. This match is computed iterating GEM to assign edge pixels to the correct body part and to find the body pose that maximizes the likelihood of the assignments.
Citation:
A. Fossati, E. Arnaud, R. Horaud, P. Fua, "Tracking articulated bodies using Generalized Expectation Maximization," cvprw, pp.1-6, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008
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