Action Recognition using Dynamics Features

摘要：

In this paper, we propose a method of action recognition using dynamics features based on physics model. The dynamics features are composed of torques from knee and hip joints of both legs and implicitly include the gravity, ground reaction forces, and the pose of the remaining body parts. These features are more discriminative than the kinematics features, and they result in a low dimensional representation of a human action which preserves much information of the original high dimensional pose. This low dimensional feature allows us to achieve a good classification performance even with a relatively small training data in a simple classification framework such as HMM. The effectiveness of the proposed method is demonstrated through experiments on the CMU motion capture dataset with various actions.

作者: Al Mansur Yasushi Makihara Yasushi Yagi

作者单位: The Institute of Scientific and Industrial Research,Osaka University,8-1 Mihogaoka,Ibaraki,Osaka,567-0047 Japan

会议类型: 国际会议

会议名称: 2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)

会议地点: 上海

会议语种:英文

页码: 4020-4025

在线出版日期: 2011-05-09（万方平台首次上网日期，不代表论文的发表时间）