Captured Human Motion Segmentation Based on Dynamics and Principal Component Analysis

Shu-xu Jing, Qi Yuan
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Abstract

This paper proposes an approach for segmenting single actions from continuously captured motion sequences by examining the properties of active limbs. The target motions are related to sporting and dancing. In particular, two types of human sports motions are examined: 1) boxing and 2) hip hop dance. To segment continuous boxing motion sequences into single punches and combo punches, this paper employs the professional knowl- edge of boxing to compensate for the drawbacks of local minima or maxima detection based motion segmentation approaches. To segment continuous Hip-hop dance sequences into single actions, this papers explores a PCA(Principal Component Analysis) based approach by finding the proper start frame and segment length to perform PCA transformation. Experiments proves that the proposed approach works well.
基于动力学和主成分分析的捕获人体运动分割
本文提出了一种通过检测活动肢体的特性,从连续捕获的运动序列中分割单个动作的方法。目标动作与体育和舞蹈有关。特别地,研究了两种人类运动:1)拳击和2)街舞。为了将连续拳击运动序列分割为单拳和组合拳,本文利用拳击的专业知识来弥补基于局部极小值或最大值检测的运动分割方法的不足。为了将连续的街舞序列分割成单个动作,本文探索了一种基于主成分分析(PCA)的方法,通过寻找合适的起始帧和片段长度来进行PCA变换。实验证明了该方法的有效性。
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