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Real-Time Dance Pattern Recognition Invariant to Anthropometric and Temporal Differences Host Publication: the 14th international conference on Advanced Concepts for Intelligent Vision Systems Authors: M. Oveneke, V. Enescu and H. Sahli Publisher: Springer Verlag Publication Date: Sep. 2012 Number of Pages: 13 ISBN: 978-3-642-33139-8
Abstract: We present a cascaded real-time system that recognizes dance patterns from 3D motion capture data. In a first step, the body trajectory, relative to the motion capture sensor, is matched. In a second step, an angular representation of the skeleton is proposed to make the system invariant to anthropometric differences relative to the body trajectory. Coping with non-uniform speed variations and amplitude discrepancies between dance patterns is achieved via a sequence similarity measure based on Dynamic Time Warping (DTW). A similarity threshold for recognition is automatically determined. Using only one good motion exemplar (baseline) per dance pattern, the recognition system is able to find a matching candidate pattern in a continuous stream of data, without prior segmentation. Experiments show the proposed algorithm reaches a good trade-off between simplicity, speed and recognition rate. An average recognition rate of 86.8% is obtained in real-time. External Link.
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