3D-SUSAN: A Robust Extension of 2D SUSAN Operator for 3D Interest Points Detection

被引：0

作者：

Zhou, Wenhui ^{[1
]}

Wang, Yu ^{[1
]}

Zhang, Hua ^{[1
]}

Dai, Guojun ^{[1
]}

机构：

[1] Hangzhou Dianzi Univ, Sch Comp Sci & Technol, Hangzhou, Zhejiang, Peoples R China

来源：

2017 10TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, BIOMEDICAL ENGINEERING AND INFORMATICS (CISP-BMEI) | 2017年

基金：

中国国家自然科学基金;

关键词：

3D mesh; interest point; 3D-SUSAN; mean curvature;

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Three dimension model is widely used in industrial design, cultural relic protection, education, animation and entertainment. Many 3D interest point detection algorithms have been developed in recent years. In this paper, we proposes a new 3D interest point detection inspired by the idea of 2D SUSAN operator. Our main contributions is proposing a robust USAN volume estimation method based on the mean curvature analysis of vertices. More specifically, a 3D sphere neighborhood is defined firstly, and an adaptive threshold based on the standard deviation of the mean curvatures is used for USAN volume estimation. Then a set of candidate interest points are extracted according to the 3D-SUSAN responses. Finally, the ambiguous or pseudo interest points are removed by the proposed pseudo interest point elimination and the non-maximum suppression. Visual comparison results and the quantitative comparison results demonstrate the effectiveness and robustness of our 3D-SUSAN.

引用

页数：6