利用运动子空间从运动中恢复非刚性结构的关节估计和利用

J-HGBU '11 Pub Date : 2011-12-01 DOI:10.1145/2072572.2072587
M. Rohith, C. Kambhamettu
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引用次数: 3

摘要

基于运动的非刚性结构估计(NRSFM)通常作为基形状的线性组合进行。然而,当处理包含人类关节运动的场景时(特别是在有衣服的情况下),基本形状的数量会妨碍准确的结果。我们将变形建模为关节和非刚性表面变形的组合。我们提出了一种新的运动分割算法来寻找关节构件,并提出了一种分层NRSFM算法来分别估计关节和非刚性结构。我们的方法试图从观测矩阵中移除关节运动,只留下可以用更少的基表示的非刚性分量。结果表明,我们的方法成功地分割了各种情况下的运动,并且使用分层框架改进了结构重建。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimation and utilization of articulations in recovering non-rigid structure from motion using motion subspaces
Estimation of non-rigid structure from motion (NRSFM) has often been performed as a linear combination of basis shapes. However, when dealing with scenes containing human articulated motion (especially in presence of clothing), the number of basis shapes precludes accurate results. We model deformation as a combination of articulated and non-rigid surface deformation. We propose a novel algorithm for segmenting motion to find articulated components and a hierarchical NRSFM algorithm which estimates articulated and non-rigid structure separately. Our method attempts to remove the articulated motion from the observation matrix leaving behind only the non-rigid component which can be represented with fewer bases. Results show that our method successfully segments motion in a variety of cases and structure reconstruction is improved using the hierarchical framework.
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