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Proceedings Paper

Grassmann manifold based shape matching and retrieval under partial occlusions
Author(s): Chenxi Li; Zelin Shi; Yunpeng Liu; Baoshu Xu
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Paper Abstract

Shape matching and recognition is a challenging task due to geometric distortions and occlusions. A novel shape matching approach based on Grassmann manifold is proposed that affine transformations and partial occlusions are both considered. An affine invariant Grassmann shape descriptor is employed which projects one shape contour to a point on Grassmann manifold and gives the similarity measurement between two contours based on the geodesic distance on the manifold. At first, shape contours are parameterized by affine length and accordingly divided into local affine-invariant shape segments, which are represented by the Grassmann shape descriptor, according to their curvature scale space images. Then the Smith-Waterman algorithm is employed to find the common parts of two shapes’ segment sequences, and get the local similarity of shapes. The global similarity is given by the found common parts, and finally the shape recognition accomplished by the weighted sum of local similarity and global similarity. The robustness of the Grassmann shape descriptor is analyzed through subspace perturbation analysis theory. Retrieval experiments show that our approach is effective and robust under affine transformations and partial occlusions.

Paper Details

Date Published: 24 November 2014
PDF: 6 pages
Proc. SPIE 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012O (24 November 2014); doi: 10.1117/12.2072864
Show Author Affiliations
Chenxi Li, Shenyang Institute of Automation (China)
Univ. of Chinese Academy of Sciences (China)
Zelin Shi, Shenyang Institute of Automation (China)
Yunpeng Liu, Shenyang Institute of Automation (China)
Baoshu Xu, Shenyang Institute of Automation (China)

Published in SPIE Proceedings Vol. 9301:
International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition
Gaurav Sharma; Fugen Zhou; Jennifer Liu, Editor(s)

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