Human Motion Data Retrieval Based on Dynamic Time Warping Optimization Algorithm
LIU Xian-Mei1,2, ZHAO Dan2, HAO Ai-Min1
1. State Key Laboratory of Virtual Reality Technology and System,Beihang University,Beijing 100083 2.School of Computer and Information Technology,Northeast Petroleum University,Daqing 163318
Abstract：With the emergence of many large-scale three-dimensional human motion databases, content-based retrieval of 3D human motion faces many difficulties. A human motion data retrieval technology based on improved dynamic time warping optimization algorithm is proposed, by which logically similar motions can be found effectively. Firstly, the coordinates of two motion sequences are aligned and a distance matrix based on window of frames is constructed. Then, using an optimization algorithm based on global and local constraints, a similarity matching is processed to describe corresponding relationship between two motions. Finally, similar motions are retrieved by two-phase approach with normalization similarity and DTW average distance. The experimental results show that by two-phase DTW optimization approach, better retrieval results for motions which are not aligned in time axis are obtained and the efficiency is improved.
刘贤梅，赵丹，郝爱民. 基于优化的DTW算法的人体运动数据检索[J]. 模式识别与人工智能, 2012, 25(2): 352-360.
LIU Xian-Mei, ZHAO Dan, HAO Ai-Min. Human Motion Data Retrieval Based on Dynamic Time Warping Optimization Algorithm. , 2012, 25(2): 352-360.
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