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The current means of locating specific movements in film necessitate hours of viewing, making the task of conducting research into movement characteristics and patterns tedious and difficult. This is particularly problematic for the research and analysis of complex movement systems such as sports and dance. While some systems have been developed to manually annotate film, to date no automated way of identifying complex, full body movement exists. With pattern recognition technology and knowledge of joint locations, automatically describing filmed movement using computer software is possible. This study used various forms of lower body kinematic analysis to identify codified dance movements. We created an algorithm that compares an unknown move with a specified start and stop against known dance moves. Our recognition method consists of classification and template correlation using a database of model moves. This system was optimized to include nearly 90 dance and Tai Chi Chuan movements, producing accurate name identification in over 97% of trials. In addition, the program had the capability to provide a kinematic description of either matched or unmatched moves obtained from classification recognition
Travis T. Simpson is with the Department of Mechanical and Aerospace Engineering, University of Virginia, Charlottesville, VA. Susan L. Wiesner is with the Department of Drama, University of Virginia, Charlottesville, VA. Bradford C. Bennett (Corresponding Author) is with the Department of Mechanical and Aerospace Engineering and with the Department of Orthopaedic Surgery, University of Virginia, Charlottesville, VA.