Efficient Globally Optimal 2D-To-3D Deformable Shape Matching

Zorah Lahner, Emanuele Rodola, Frank R. Schmidt, Michael M. Bronstein, Daniel Cremers; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, pp. 2185-2193

Abstract


We propose the first algorithm for non-rigid 2D-to-3D shape matching, where the input is a 2D query shape as well as a 3D target shape and the output is a continuous matching curve represented as a closed contour on the 3D shape. We cast the problem as finding the shortest circular path on the product 3-manifold of the two shapes. We prove that the optimal matching can be computed in polynomial time with a (worst-case) complexity of O(m*n^2*log(n)), where m and n denote the number of vertices on the 2D and the 3D shape respectively. Quantitative evaluation confirms that the method provides excellent results for sketch-based deformable 3D shape retrieval.

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[bibtex]
@InProceedings{Lahner_2016_CVPR,
author = {Lahner, Zorah and Rodola, Emanuele and Schmidt, Frank R. and Bronstein, Michael M. and Cremers, Daniel},
title = {Efficient Globally Optimal 2D-To-3D Deformable Shape Matching},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2016}
}