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Authors: Jun Yang 1 ; Alexander Obaseki 1 and Jim Chen 2

Affiliations: 1 School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou, Gansu 730070, China ; 2 Department of Computer Science, George Mason University, Fairfax, VA 22030-4444, U.S.A.

ISBN: 978-989-758-354-4

Keyword(s): Canonical Forms, Laplace-Beltrami Operator, Biharmonic Distance, Spectral Multidimensional Scaling (S-MDS).

Abstract: The spectral property of the Laplace-Beltrami operator has become relevant in shape analysis. One of the numerous methods that employ the strength of Laplace-Beltrami operator eigen-properties in shape analysis is the spectral multidimensional scaling which maps the MDS problem into the eigenspace of its Laplace-Beltrami operator. Using the biharmonic distance we show a further reduction in the complexities of the canonical form of shapes making similarities and dissimilarities of isometric shapes more efficiently computed. With the theoretical sound biharmonic distance we embed the intrinsic property of a given shape into a Euclidean metric space. Utilizing the farthest-point sampling strategy to select a subset of sampled points, we combine the potency of the spectral multidimensional scaling with global awareness of the biharmonic distance operator to propose an approach which embeds canonical forms images that shows further “resemblance” between isometric shapes. Experimental resu lt shows an efficient and effective approximation with both distinctive local features and yet a robust global property of both the model and probe shapes. In comparison to a recent state-of-the-art work, the proposed approach can achieve comparable or even better results and have practical computational efficiency as well. (More)

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Paper citation in several formats:
Yang, J.; Obaseki, A. and Chen, J. (2019). Spectral Multi-Dimensional Scaling using Biharmonic Distance.In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP, ISBN 978-989-758-354-4, pages 161-168. DOI: 10.5220/0007242901610168

@conference{grapp19,
author={Jun Yang. and Alexander Jesuorobo Obaseki. and Jim X. Chen.},
title={Spectral Multi-Dimensional Scaling using Biharmonic Distance},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP,},
year={2019},
pages={161-168},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007242901610168},
isbn={978-989-758-354-4},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP,
TI - Spectral Multi-Dimensional Scaling using Biharmonic Distance
SN - 978-989-758-354-4
AU - Yang, J.
AU - Obaseki, A.
AU - Chen, J.
PY - 2019
SP - 161
EP - 168
DO - 10.5220/0007242901610168

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