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(mn2log(n)), wherem 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.

Efficient globally optimal 2D-to-3D deformable shape matching / Lähner, Zorah; Rodolà, Emanuele; Schmidt, Frank R.; Bronstein, Michael M.; Cremers, Daniel. - 2016:(2016), pp. 2185-2193. (Intervento presentato al convegno 2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016 tenutosi a Las Vegas; USA).

Efficient globally optimal 2D-to-3D deformable shape matching

Rodolà, Emanuele;
2016

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(mn2log(n)), wherem 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.
2016
2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016
Algorithms; Deformation; Image processing
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Efficient globally optimal 2D-to-3D deformable shape matching / Lähner, Zorah; Rodolà, Emanuele; Schmidt, Frank R.; Bronstein, Michael M.; Cremers, Daniel. - 2016:(2016), pp. 2185-2193. (Intervento presentato al convegno 2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016 tenutosi a Las Vegas; USA).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1228077
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