Elastic Net Constraints for Shape Matching

Emanuele Rodola, Andrea Torsello, Tatsuya Harada, Yasuo Kuniyoshi, Daniel Cremers; The IEEE International Conference on Computer Vision (ICCV), 2013, pp. 1169-1176


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

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author = {Rodola, Emanuele and Torsello, Andrea and Harada, Tatsuya and Kuniyoshi, Yasuo and Cremers, Daniel},
title = {Elastic Net Constraints for Shape Matching},
booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
month = {December},
year = {2013}