Detecting Reflectional Symmetries in 3D Data Through Symmetrical Fitting

被引：23

作者：

Ecins, Aleksandrs ^{[1
]}

Fermuller, Cornelia ^{[1
]}

Aloimonos, Yiannis ^{[1
]}

机构：

[1] Univ Maryland, Dept Comp Sci, College Pk, MD 20742 USA

来源：

2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW 2017) | 2017年

关键词：

D O I：

10.1109/ICCVW.2017.210

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Symmetry is ubiquitous in both natural and man-made environments. It reveals redundancies in the structure of the world around us and thus can be used in a variety of visual processing tasks. This paper presents a simple and robust approach to detecting symmetric objects and extracting their symmetries from three-dimensional data. Given a 3D mesh of an object, a set of candidate symmetries are proposed first and are then refined, so that they reflect the complete mesh onto itself. We show how our method can be used to detect symmetric objects in scenes consisting of synthetic 3D models, as well as 3D scans of real environments.

引用

页码：1779 / 1783

页数：5

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