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Diffusion pruning for rapidly and robustly selecting global correspondences using local isometry

Tam, Gary K. L., Martin, Ralph Robert, Rosin, Paul L. and Lai, Yukun 2014. Diffusion pruning for rapidly and robustly selecting global correspondences using local isometry. ACM Transactions on Graphics 33 (1) , 4. 10.1145/2517967

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Abstract

Finding correspondences between two surfaces is a fundamental operation in various applications in computer graphics and related fields. Candidate correspondences can be found by matching local signatures, but as they only consider local geometry, many are globally inconsistent. We provide a novel algorithm to prune a set of candidate correspondences to those most likely to be globally consistent. Our approach can handle articulated surfaces, and ones related by a deformation which is globally nonisometric, provided that the deformation is locally approximately isometric. Our approach uses an efficient diffusion framework, and only requires geodesic distance calculations in small neighbourhoods, unlike many existing techniques which require computation of global geodesic distances. We demonstrate that, for typical examples, our approach provides significant improvements in accuracy, yet also reduces time and memory costs by a factor of several hundred compared to existing pruning techniques. Our method is furthermore insensitive to holes, unlike many other methods.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Additional Information: Pdf uploaded in accordance with the publisher’s policy at http://www.sherpa.ac.uk/romeo/issn/0730-0301/ (accessed 31/07/2014) © ACM, 2014. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Transactions on Graphics, {VOL 33, ISSUE 1, 2014} http://doi.acm.org/10.1145/2517967
Publisher: Association for Computing Machinery
ISSN: 0730-0301
Funders: Welsh Government, EPSRC
Date of First Compliant Deposit: 30 March 2016
Last Modified: 17 Oct 2019 12:22
URI: http://orca-mwe.cf.ac.uk/id/eprint/57387

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