Local Geometry Inclusive Global Shape Representation
July 20, 2017 Β· Declared Dead Β· π 2017 IEEE International Conference on Computer Vision Workshops (ICCVW)
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Authors
Somenath Das, Suchendra M. Bhandarkar
arXiv ID
1707.06699
Category
cs.CV: Computer Vision
Citations
2
Venue
2017 IEEE International Conference on Computer Vision Workshops (ICCVW)
Last Checked
4 months ago
Abstract
Knowledge of shape geometry plays a pivotal role in many shape analysis applications. In this paper we introduce a local geometry-inclusive global representation of 3D shapes based on computation of the shortest quasi-geodesic paths between all possible pairs of points on the 3D shape manifold. In the proposed representation, the normal curvature along the quasi-geodesic paths between any two points on the shape surface is preserved. We employ the eigenspectrum of the proposed global representation to address the problems of determination of region-based correspondence between isometric shapes and characterization of self-symmetry in the absence of prior knowledge in the form of user-defined correspondence maps. We further utilize the commutative property of the resulting shape descriptor to extract stable regions between isometric shapes that differ from one another by a high degree of isometry transformation. We also propose various shape characterization metrics in terms of the eigenvector decomposition of the shape descriptor spectrum to quantify the correspondence and self-symmetry of 3D shapes. The performance of the proposed 3D shape descriptor is experimentally compared with the performance of other relevant state-of-the-art 3D shape descriptors.
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