Elastic net constraints for shape matching
Rodola E, Torsello A, Harada T, Kuniyoshi Y, Cremers D (2013)
Publication Type: Conference contribution
Publication year: 2013
Publisher: Institute of Electrical and Electronics Engineers Inc.
Pages Range: 1169-1176
Conference Proceedings Title: Proceedings of the IEEE International Conference on Computer Vision
Event location: AUS
ISBN: 9781479928392
Abstract
We consider a parametrized relaxation of the widely adopted quadratic assignment problem (QAP) formulation for minimum distortion correspondence between deformable shapes. In order to control the accuracy/sparsity trade-off we introduce a weighting parameter on the combination of two existing relaxations, namely spectral and game-theoretic. This leads to the introduction of the elastic net penalty function into shape matching problems. In combination with an efficient algorithm to project onto the elastic net ball, we obtain an approach for deformable shape matching with controllable sparsity. Experiments on a standard benchmark confirm the effectiveness of the approach. © 2013 IEEE.
Involved external institutions
University of Tokyo
Japan (JP)
Università Ca’ Foscari
Italy (IT)
Technische Universität München (TUM)
Germany (DE)
Japan (JP)
Università Ca’ Foscari
Italy (IT)
Technische Universität München (TUM)
Germany (DE)
How to cite
APA:
Rodola, E., Torsello, A., Harada, T., Kuniyoshi, Y., & Cremers, D. (2013). Elastic net constraints for shape matching. In Proceedings of the IEEE International Conference on Computer Vision (pp. 1169-1176). AUS: Institute of Electrical and Electronics Engineers Inc..
MLA:
Rodola, Emanuele, et al. "Elastic net constraints for shape matching." Proceedings of the 2013 14th IEEE International Conference on Computer Vision, ICCV 2013, AUS Institute of Electrical and Electronics Engineers Inc., 2013. 1169-1176.
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