2015
DOI: 10.1016/j.cag.2014.09.018
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Automatic posing of a meshed human model using point clouds

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Cited by 12 publications
(5 citation statements)
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“…If two shapes are perfectly isometric, then there exists an isometry i.e., a distance-preserving mapping, between these shapes such that the geodesic distance between any two points on one shape is exactly the same as the geodesic distance between their correspondences on the other [36]. Different approaches are proposed to exploit isometry for shape correspondences [14,15,20,29,35]. One way is to embed shape into a different domain where geodesic distances are replaced by Euclidean distance so that isometric deviation can be measured and optimized in the embedding space [15].…”
Section: Related Workmentioning
confidence: 99%
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“…If two shapes are perfectly isometric, then there exists an isometry i.e., a distance-preserving mapping, between these shapes such that the geodesic distance between any two points on one shape is exactly the same as the geodesic distance between their correspondences on the other [36]. Different approaches are proposed to exploit isometry for shape correspondences [14,15,20,29,35]. One way is to embed shape into a different domain where geodesic distances are replaced by Euclidean distance so that isometric deviation can be measured and optimized in the embedding space [15].…”
Section: Related Workmentioning
confidence: 99%
“…One way is to embed shape into a different domain where geodesic distances are replaced by Euclidean distance so that isometric deviation can be measured and optimized in the embedding space [15]. Euclidean embedding can be achieved using various techniques such as classical MDS (Multidimensional Scaling) [20,35], least-squares MDS [15], and spectral analysis of the graph Laplacian [29] or of the Laplace-Beltrami operator [14]. However, when it comes to the meshes from low-cost scanners, the above isometry-based methods are not applicable as they usually require watertight meshes and suffer from self-symmetry of human body shape.…”
Section: Related Workmentioning
confidence: 99%
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