A robust point set registration algorithm based on information geometry

Xiaoqiang Hua; Ping Wang; Kefeng Ji; Yinghui Gao; Ruigang Fu

doi:10.1117/12.2070836

24 November 2014 A robust point set registration algorithm based on information geometry

Xiaoqiang Hua, Ping Wang, Kefeng Ji, Yinghui Gao, Ruigang Fu

Proceedings Volume 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition; 930110 (2014) https://doi.org/10.1117/12.2070836
Event: International Symposium on Optoelectronic Technology and Application 2014, 2014, Beijing, China

Abstract

Point set registration is a key component in many computer vision tasks. This paper proposes a point set registration algorithm based on information geometry. Point sets to be registration are converting to the statistical manifolds by Gaussian mixture model. The component of mixture model represents the dimension of statistical manifold and point set is a point on manifold. Through conversion, point set registration is reformulated as searching the shortest path between two manifold and we can use the em algorithm which defined by information geometry to get the optimization solution. Experimental results show that the proposed algorithm is robust to noise and outliers, and achieved very good accuracy.

Citation Download Citation

Xiaoqiang Hua, Ping Wang, Kefeng Ji, Yinghui Gao, and Ruigang Fu "A robust point set registration algorithm based on information geometry", Proc. SPIE 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930110 (24 November 2014); https://doi.org/10.1117/12.2070836

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available