Motion Retrieval Based on Energy Morphing

G. Tam, Qingzheng Zheng, M. Corbyn, Rynson W. H. Lau
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引用次数: 8

Abstract

Matching and retrieval of motion sequences has become an important research area in recent years, due to the increasing availability and popularity of motion capture data. The main challenge in matching two motion sequences is the diversity of the captured motions, including variable length, local shifting, local and global scaling. Most existing methods employ Dynamic Time Warping (DTW) or Uniform Scaling to handle these problems. In this paper, we propose a novel content-based method for matching of this human motion captured data. We convert the matching problem of motion capture data into a transportation problem. To solve this problem efficiently, we employ Earth Mover's Distance (EMD) as the matching framework. To penalize any strayed matching, we provide a ground distance that works similar to Sakoe- Chiba band of DTW. Empirical results obtained are encouraging.
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基于能量变形的运动检索
近年来,随着运动捕捉数据的日益普及和普及,运动序列的匹配与检索已成为一个重要的研究领域。匹配两个运动序列的主要挑战是捕获运动的多样性,包括可变长度、局部移动、局部和全局缩放。现有的方法大多采用动态时间翘曲(DTW)或均匀缩放来处理这些问题。在本文中,我们提出了一种新的基于内容的方法来匹配这些人体运动捕获数据。我们将运动捕捉数据的匹配问题转化为运输问题。为了有效地解决这一问题,我们采用了土动器距离(EMD)作为匹配框架。为了防止任何误匹配,我们提供了一个与DTW的Sakoe- Chiba波段相似的地面距离。得到的实证结果令人鼓舞。
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