Point matching based on non-parametric model

Renfeng Liu; Cong Zhang; Jinwen Tian

doi:10.1117/12.2205409

14 December 2015 Point matching based on non-parametric model

Renfeng Liu, Cong Zhang, Jinwen Tian

Proceedings Volume 9813, MIPPR 2015: Pattern Recognition and Computer Vision; 98130X (2015) https://doi.org/10.1117/12.2205409
Event: Ninth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2015), 2015, Enshi, China

Abstract

Establishing reliable feature correspondence between two images is a fundamental problem in vision analysis and it is a critical prerequisite in a wide range of applications including structure-from-motion, 3D reconstruction, tracking, image retrieval, registration, and object recognition. The feature could be point, line, curve or surface, among which the point feature is primary and is the foundation of all features. Numerous techniques related to point matching have been proposed within a rich and extensive literature, which are typically studied under rigid/affine or non-rigid motion, corresponding to parametric and non-parametric models for the underlying image relations. In this paper, we provide a review of our previous work on point matching, focusing on nonparametric models. We also make an experimental comparison of the introduced methods, and discuss their advantages and disadvantages as well.

Citation Download Citation

Renfeng Liu, Cong Zhang, and Jinwen Tian "Point matching based on non-parametric model", Proc. SPIE 9813, MIPPR 2015: Pattern Recognition and Computer Vision, 98130X (14 December 2015); https://doi.org/10.1117/12.2205409

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