TY - GEN
T1 - Paretian similarity for partial comparison of non-rigid objects
AU - Bronstein, Alexander M.
AU - Bronstein, Michael M.
AU - Bruckstein, Alfred M.
AU - Kimmel, Ron
PY - 2007
Y1 - 2007
N2 - In this paper, we address the problem of partial comparison of non-rigid objects. We introduce a new class of set-valued distances, related to the concept of Pareto optimality in economics. Such distances allow to capture intrinsic geometric similarity between parts of non-rigid objects, obtaining semantically meaningful comparison results. The numerical implementation of our method is computationally efficient and is similar to GMDS, a multidimensional scaling-like continuous optimization problem.
AB - In this paper, we address the problem of partial comparison of non-rigid objects. We introduce a new class of set-valued distances, related to the concept of Pareto optimality in economics. Such distances allow to capture intrinsic geometric similarity between parts of non-rigid objects, obtaining semantically meaningful comparison results. The numerical implementation of our method is computationally efficient and is similar to GMDS, a multidimensional scaling-like continuous optimization problem.
UR - http://www.scopus.com/inward/record.url?scp=37249092651&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-72823-8_23
DO - 10.1007/978-3-540-72823-8_23
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AN - SCOPUS:37249092651
SN - 9783540728221
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 264
EP - 275
BT - Scale Space and Variational Methods in Computer Vision, First International Conference, SSVM 2007, Proceedings
PB - Springer Verlag
T2 - 1st International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2007
Y2 - 30 May 2007 through 2 June 2007
ER -