Capturing Motion Skills with Silhouette-Based Numerical Pose Estimation
Fraunhofer IGD, Germany
(‡) University of Applied Science Giessen-Friedberg
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The capturing of human movements is an important step for the analysis of human skills, e.g. for sports analysis or for learning-by-demonstration tasks. In this paper we introduce a new markerless pose estimation method which estimates human poses from silhouettes. The presented numerical pose estimation algorithm adapts a non-deterministical annealing schedule for silhouette based motion capturing. The pose is estimated by numerically minimizing the differences between the silhouettes of synthesized views of a 3D avatar and the silhouettes of the real person in the camera images. The evaluation results of simulation experiments quantify the trade-off between the accuracy and the execution time of the presented algorithm.
© Owned by the authors, published by EDP Sciences, 2011