TY - GEN
T1 - Regularized partial matching of rigid shapes
AU - Bronstein, Alexander M.
AU - Bronstein, Michael M.
PY - 2008
Y1 - 2008
N2 - Matching of rigid shapes is an important problem in numerous applications across the boundary of computer vision, pattern recognition and computer graphics communities. A particularly challenging setting of this problem is partial matching, where the two shapes are dissimilar in general, but have significant similar parts. In this paper, we show a rigorous approach allowing to find matching parts of rigid shapes with controllable size and regularity. The regularity term we use is similar to the spirit of the Mumford-Shah functional, extended to non-Euclidean spaces. Numerical experiments show that the regularized partial matching produces better results compared to the non-regularized one.
AB - Matching of rigid shapes is an important problem in numerous applications across the boundary of computer vision, pattern recognition and computer graphics communities. A particularly challenging setting of this problem is partial matching, where the two shapes are dissimilar in general, but have significant similar parts. In this paper, we show a rigorous approach allowing to find matching parts of rigid shapes with controllable size and regularity. The regularity term we use is similar to the spirit of the Mumford-Shah functional, extended to non-Euclidean spaces. Numerical experiments show that the regularized partial matching produces better results compared to the non-regularized one.
UR - http://www.scopus.com/inward/record.url?scp=56749104121&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-88688-4_11
DO - 10.1007/978-3-540-88688-4_11
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AN - SCOPUS:56749104121
SN - 3540886850
SN - 9783540886853
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 143
EP - 154
BT - Computer Vision - ECCV 2008 - 10th European Conference on Computer Vision, Proceedings
PB - Springer Verlag
T2 - 10th European Conference on Computer Vision, ECCV 2008
Y2 - 12 October 2008 through 18 October 2008
ER -