简介概要

Relaxation labeling for non-rigid point matching under neighbor preserving

来源期刊:中南大学学报(英文版)2013年第11期

论文作者:YAN Xing-wei(晏行伟) WANG Wei(王玮) ZHAO Jian(赵键) HU Jie-min(胡杰民) 张军 WAN Jian-wei(万建伟)

文章页码:3077 - 3084

Key words:non-rigid; point matching; shape context; relaxation labeling

Abstract: Non-rigid point matching has received more and more attention. Recently, many works have been developed to discover global relationships in the point set which is treated as an instance of a joint distribution. However, the local relationship among neighboring points is more effective under non-rigid transformations. Thus, a new algorithm taking advantage of shape context and relaxation labeling technique, called SC-RL, is proposed for non-rigid point matching. It is a strategy that joints estimation for correspondences as well as the transformation. In this work, correspondence assignment is treated as a soft-assign process in which the matching probability is updated by relaxation labeling technique with a newly defined compatibility coefficient. The compatibility coefficient is one or zero depending on whether neighboring points preserving their relative position in a local coordinate system. The comparative analysis has been performed against four state-of-the-art algorithms including SC, ICP, TPS-RPM and RPM-LNS, and the results denote that SC-RL performs better in the presence of deformations, outliers and noise.

详情信息展示

Relaxation labeling for non-rigid point matching under neighbor preserving

YAN Xing-wei(晏行伟), WANG Wei(王玮), ZHAO Jian(赵键), HU Jie-min(胡杰民), ZHANG Jun(张军), WAN Jian-wei(万建伟)

(College of Electronic Science and Engineering, National University of Defense Technology,
Changsha 410073, China)

Abstract:Non-rigid point matching has received more and more attention. Recently, many works have been developed to discover global relationships in the point set which is treated as an instance of a joint distribution. However, the local relationship among neighboring points is more effective under non-rigid transformations. Thus, a new algorithm taking advantage of shape context and relaxation labeling technique, called SC-RL, is proposed for non-rigid point matching. It is a strategy that joints estimation for correspondences as well as the transformation. In this work, correspondence assignment is treated as a soft-assign process in which the matching probability is updated by relaxation labeling technique with a newly defined compatibility coefficient. The compatibility coefficient is one or zero depending on whether neighboring points preserving their relative position in a local coordinate system. The comparative analysis has been performed against four state-of-the-art algorithms including SC, ICP, TPS-RPM and RPM-LNS, and the results denote that SC-RL performs better in the presence of deformations, outliers and noise.

Key words:non-rigid; point matching; shape context; relaxation labeling

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