NDLI: Robust non-rigid point set registration method based on asymmetric Gaussian and structural feature

Content Provider	IET Digital Library
Author	Dou, Jun Niu, Dongmei Feng, Zhiquan Zhao, Xiuyang
Abstract	Point set registration is a fundamental problem in many domains of computer vision. In previous work on the registration, the point sets are often represented using Gaussian mixture models and the registration process is represented as a form of a probabilistic solution. For non-rigid point set registration, however, the asymmetric Gaussian (AG) model can capture spatially asymmetric distributions compared with symmetric Gaussian, and the structural feature of the point sets reserve relatively complete and has important significance in registration. In this work, the authors designed a new shape context (SC) descriptor which combines the local and global structures of the point set. Meanwhile, they proposed a non-rigid point set registration algorithm which formulates a registration process as the mixture probability density estimation of the AG mixture model, and the method introduce the structural feature by the new SC. Extensive experiments show that the proposed algorithm has a clear improvement over the state-of-the-art methods.
Starting Page	806
Ending Page	816
Page Count	11
ISSN	17519632
Volume Number	12
e-ISSN	17519640
Issue Number	Issue 6, Sep (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/12/6
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2017.0550
Journal	IET Computer Vision
Publisher Date	2018-04-04
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	AG Mixture Model Asymmetric Gaussian Model Computer Vision Computer Vision And Image Processing Technique Gaussian Distribution Gaussian Mixture Model Global Structure Image Registration Image Representation Local Structure Mixture Model Mixture Probability Density Estimation Optical, Image And Video Signal Processing Probability Robust Nonrigid Point Set Registration Method Shape Context Descriptor Spatially Asymmetric Distribution Statistics Structural Feature
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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