Affine Invariant Geometry for Non-rigid Shapes

Shape recognition deals with the study geometric structures. Modern surface processing methods can cope with non-rigidity—by measuring the lack of isometry, deal with similarity or scaling—by multiplying the Euclidean arc-length by the Gaussian curvature, and manage equi-affine transformations—by re...

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Main Authors: Raviv, Dan, Kimmel, Ron
Other Authors: Massachusetts Institute of Technology. Media Laboratory
Format: Article
Language:English
Published: Springer US 2016
Online Access:http://hdl.handle.net/1721.1/103333
https://orcid.org/0000-0003-3254-2050
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author Raviv, Dan
Kimmel, Ron
author2 Massachusetts Institute of Technology. Media Laboratory
author_facet Massachusetts Institute of Technology. Media Laboratory
Raviv, Dan
Kimmel, Ron
author_sort Raviv, Dan
collection MIT
description Shape recognition deals with the study geometric structures. Modern surface processing methods can cope with non-rigidity—by measuring the lack of isometry, deal with similarity or scaling—by multiplying the Euclidean arc-length by the Gaussian curvature, and manage equi-affine transformations—by resorting to the special affine arc-length definition in classical equi-affine differential geometry. Here, we propose a computational framework that is invariant to the full affine group of transformations (similarity and equi-affine). Thus, by construction, it can handle non-rigid shapes. Technically, we add the similarity invariant property to an equi-affine invariant one and establish an affine invariant pseudo-metric. As an example, we show how diffusion geometry can encapsulate the proposed measure to provide robust signatures and other analysis tools for affine invariant surface matching and comparison.
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spelling mit-1721.1/1033332022-10-01T04:55:45Z Affine Invariant Geometry for Non-rigid Shapes Raviv, Dan Kimmel, Ron Massachusetts Institute of Technology. Media Laboratory Raviv, Dan Shape recognition deals with the study geometric structures. Modern surface processing methods can cope with non-rigidity—by measuring the lack of isometry, deal with similarity or scaling—by multiplying the Euclidean arc-length by the Gaussian curvature, and manage equi-affine transformations—by resorting to the special affine arc-length definition in classical equi-affine differential geometry. Here, we propose a computational framework that is invariant to the full affine group of transformations (similarity and equi-affine). Thus, by construction, it can handle non-rigid shapes. Technically, we add the similarity invariant property to an equi-affine invariant one and establish an affine invariant pseudo-metric. As an example, we show how diffusion geometry can encapsulate the proposed measure to provide robust signatures and other analysis tools for affine invariant surface matching and comparison. United States. Office of Naval Research (award N00014-12-1-0517) Israel Science Foundation (Grant Number 1031/120 2016-06-24T18:30:36Z 2016-06-24T18:30:36Z 2014-06 2012-02 2016-05-23T12:14:36Z Article http://purl.org/eprint/type/JournalArticle 0920-5691 1573-1405 http://hdl.handle.net/1721.1/103333 Raviv, Dan, and Ron Kimmel. “Affine Invariant Geometry for Non-Rigid Shapes.” Int J Comput Vis 111, no. 1 (June 14, 2014): 1–11. https://orcid.org/0000-0003-3254-2050 en http://dx.doi.org/10.1007/s11263-014-0728-2 International Journal of Computer Vision Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. Springer Science+Business Media New York application/pdf Springer US Springer US
spellingShingle Raviv, Dan
Kimmel, Ron
Affine Invariant Geometry for Non-rigid Shapes
title Affine Invariant Geometry for Non-rigid Shapes
title_full Affine Invariant Geometry for Non-rigid Shapes
title_fullStr Affine Invariant Geometry for Non-rigid Shapes
title_full_unstemmed Affine Invariant Geometry for Non-rigid Shapes
title_short Affine Invariant Geometry for Non-rigid Shapes
title_sort affine invariant geometry for non rigid shapes
url http://hdl.handle.net/1721.1/103333
https://orcid.org/0000-0003-3254-2050
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