期刊论文

Wan, Lili;Zou, Changqing

英文

VISUAL COMPUTER

0178-2789

2017

33

12

1497-1509

10.1007/s00371-016-1293-1

China Scholarship CouncilChina Scholarship Council; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [61572064, 61502153]; Fundamental Research Funds for the Central Universities of ChinaFundamental Research Funds for the Central Universities [2014JBM027]; Natural Science Foundation of Hunan Province of ChinaNatural Science Foundation of Hunan Province [2016JJ3031]; National 973 ProgramNational Basic Research Program of China [2011CB302203]; NSERCNatural Sciences and Engineering Research Council of Canada (NSERC) [611370]

本校为通讯机构

We introduce a novel approach to measuring similarity between two shapes based on sparse reconstruction of shape descriptors. The main feature of our approach is its applicability in situations where either of the two shapes may have moderate to significant portions of its data missing. Let the two shapes be A and B. Without loss of generality, we characterize A by learning a sparse dictionary from its local descriptors. The similarity between A and B is defined by the error incurred when reconstructing B's descriptor set using the basis signals from A's dictionary. Benefits of using sparse di...