Learning spectral descriptors for deformable shape correspondence

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 36, Issue 1, 2014, Pages 171-180

  Litman, R ^a   Bronstein, A M ^a  

^a TEL AVIV UNIVERSITY   (Israel)

Author keywords

Correspondence; Deformable shapes; Descriptor; Diffusion geometry; Heat kernel signature (HKS); Laplace Beltrami operator; Mahalanobis distance; Metric learning; Retrieval; Spectral methods; Wave kernel signature (WKS); Wiener filter

Indexed keywords

CORRESPONDENCE; DEFORMABLE SHAPES; DESCRIPTORS; DIFFUSION GEOMETRIES; HEAT KERNEL SIGNATURES; KERNEL SIGNATURES; LAPLACE-BELTRAMI OPERATOR; MAHALANOBIS DISTANCES; METRIC LEARNING; RETRIEVAL; SPECTRAL METHODS; WIENER FILTERS;

LAPLACE TRANSFORMS; OPTIMIZATION; SIGNAL PROCESSING;

DEFORMATION;

ANIMAL; ARTICLE; CAT; COMPUTER GRAPHICS; DOG; FEMALE; HORSE; HUMAN; IMAGE PROCESSING; MALE; METHODOLOGY; RECEIVER OPERATING CHARACTERISTIC; STATISTICAL MODEL;

ANIMALS; CATS; COMPUTER GRAPHICS; DOGS; FEMALE; HORSES; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MALE; MODELS, STATISTICAL; ROC CURVE;

EID: 84890362928     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2013.148     Document Type: Article

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