Human Motion Retrieval With Time-squence Features Based on Data-driven Decision Tree Analysis
基于改进的数据驱动决策树分析的3维人体运动检索

With the development of motion capture techniques,more 3D motion libraries become available.In this paper,space transformation property and time property are extracted from human motion capture data,which compose 3D motion time sequence features.Given the assumption of the features of each joint is independent,a revised data-driven decision tree of anytime induction is automatically constructed to present the influence of each point during the comparison of motion similarity.Experiment results show that our approaches are effective for motion data retrieval.