Learning coherent vector fields for robust point matching under manifold regularization

Neurocomputing

Volumn 216, Issue , 2016, Pages 393-401

  Wang, Gang ^a,b   Wang, Zhicheng ^b   Chen, Yufei ^b   Liu, Xianhui ^b   Ren, Yingchun ^b   Peng, Lei ^c  

^a SHANGHAI UNIVERSITY OF FINANCE AND ECONOMICS   (China)

^b TONGJI UNIVERSITY   (China)

^c TAISHAN MEDICAL UNIVERSITY   (China)

Author keywords

Kernel; Manifold regularization; Mismatch removal; Point matching; Vector field learning

Indexed keywords

IMAGE MATCHING; ITERATIVE METHODS; LAPLACE TRANSFORMS; MAXIMUM PRINCIPLE; OPTIMIZATION; STATISTICS;

EXPECTATION MAXIMIZATION; KERNEL; MANIFOLD REGULARIZATIONS; POINT-MATCHING; REGULARIZED LEAST SQUARES; REPRODUCING KERNEL HILBERT SPACES; STATE-OF-THE-ART METHODS; VECTOR FIELDS;

VECTORS;

ALGORITHM; ARTICLE; CALCULATION; CONTROLLED STUDY; DATA ANALYSIS; INFORMATION PROCESSING; LEARNING ALGORITHM; LEAST SQUARE ANALYSIS; MANIFOLD LEARNING COHERENT VECTOR FIELD; MATHEMATICAL COMPUTING; POINT MATCHING PROBLEM; PRIORITY JOURNAL; PROCESS OPTIMIZATION; STATISTICAL PARAMETERS; VECTOR FIELD LEARNING;

EID: 84994403232     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2016.08.009     Document Type: Article

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