期刊
NEUROCOMPUTING
卷 275, 期 -, 页码 1160-1176出版社
ELSEVIER
DOI: 10.1016/j.neucom.2017.09.067
关键词
Partial shape matching; Shape descriptor; Shape similarity
资金
- NSFC Project [61375122, 61771146]
- Shanghai Science and Technology Development Funds [13dz2260200, 13511504300]
There are two categories of partial shape matching problem: whole-to-part matching and part-to-part matching. The first establishes the best match between an open curve and a part of a closed curve, while the second is to find a part of the first input closed curve that can be well aligned with a part of the second input closed curve. In this paper, we present a novel approach to solve these two categories of the partial shape matching problem. First, we propose a novel shape descriptor, triangular centroid distances (TCDs), for shape representation; the TCDs shape descriptor is invariant to translation, rotation, scaling, and considerable shape deformations. Then, using the TCDs shape descriptor, we present a method to deal with the whole-to-part partial shape matching problem. Finally, we extend our work to part-topart partial shape matching. Here, we propose a new approach, again using the TCDs shape descriptor, to solve the part-to-part partial shape matching problem. Experimental results demonstrate that our method outperforms existing methods in 2D nonrigid partial shape matching. (C) 2017 Elsevier B.V. All rights reserved.
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