Efficient deformable shape correspondence via kernel matching
Vestner M, Laehner Z, Boyarski A, Litany O, Slossberg R, Remez T, Rodola E, Bronstein A, Bronstein M, Kimmel R, Cremers D (2018)
Publication Type: Conference contribution
Publication year: 2018
Publisher: Institute of Electrical and Electronics Engineers Inc.
Pages Range: 517-526
Conference Proceedings Title: Proceedings - 2017 International Conference on 3D Vision, 3DV 2017
Event location: Qingdao, CHN
ISBN: 9781538626108
Abstract
We present a method to match three dimensional shapes under non-isometric deformations, topology changes and partiality. We formulate the problem as matching between a set of pair-wise and point-wise descriptors, imposing a continuity prior on the mapping, and propose a projected descent optimization procedure inspired by difference of convex functions (DC) programming.
Involved external institutions
Technische Universität München (TUM)
Germany (DE)
Technion - Israel Institute of Technology
Israel (IL)
Tel Aviv University
Israel (IL)
Università degli studi "La Sapienza"
Italy (IT)
Germany (DE)
Technion - Israel Institute of Technology
Israel (IL)
Tel Aviv University
Israel (IL)
Università degli studi "La Sapienza"
Italy (IT)
How to cite
APA:
Vestner, M., Laehner, Z., Boyarski, A., Litany, O., Slossberg, R., Remez, T.,... Cremers, D. (2018). Efficient deformable shape correspondence via kernel matching. In Proceedings - 2017 International Conference on 3D Vision, 3DV 2017 (pp. 517-526). Qingdao, CHN: Institute of Electrical and Electronics Engineers Inc..
MLA:
Vestner, Matthias, et al. "Efficient deformable shape correspondence via kernel matching." Proceedings of the 7th IEEE International Conference on 3D Vision, 3DV 2017, Qingdao, CHN Institute of Electrical and Electronics Engineers Inc., 2018. 517-526.
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