A Part-aware Surface Metric for Shape Analysis

The notion of parts in a shape plays an important role in many geometry problems, including segmentation, correspondence, recognition, editing, and animation. As the fundamental geometric representation of 3D objects in computer graphics is surface‐based, solutions of many such problems utilize a su...

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Vydané v:	Computer graphics forum Ročník 28; číslo 2; s. 397 - 406
Hlavní autori:	Liu, Rong, Zhang, Hao, Shamir, Ariel, Cohen-Or, Daniel
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Oxford, UK Blackwell Publishing Ltd 01.04.2009
Predmet:	3-D graphics and systems Computer graphics Computer Graphics [I.3.5]: Computational Geometry and Object Modeling-Boundary representations Computer Graphics [I.3.5]: Computational Geometry and Object Modeling—Boundary representations, Geometric algorithms, languages, and systems Geometric algorithms languages Studies
ISSN:	0167-7055, 1467-8659
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Popis
Shrnutí:	The notion of parts in a shape plays an important role in many geometry problems, including segmentation, correspondence, recognition, editing, and animation. As the fundamental geometric representation of 3D objects in computer graphics is surface‐based, solutions of many such problems utilize a surface metric, a distance function defined over pairs of points on the surface, to assist shape analysis and understanding. The main contribution of our work is to bring together these two fundamental concepts: shape parts and surface metric. Specifically, we develop a surface metric that is part‐aware. To encode part information at a point on a shape, we model its volumetric context – called the volumetric shape image (VSI) – inside the shape's enclosed volume, to capture relevant visibility information. We then define the part‐aware metric by combining an appropriate VSI distance with geodesic distance and normal variation. We show how the volumetric view on part separation addresses certain limitations of the surface view, which relies on concavity measures over a surface as implied by the well‐known minima rule. We demonstrate how the new metric can be effectively utilized in various applications including mesh segmentation, shape registration, part‐aware sampling and shape retrieval.
Bibliografia:	ark:/67375/WNG-929ZV4M7-5 ArticleID:CGF1379 istex:10A94517D85556F4A44A53283A1565DAF40ADC1D SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-2 content type line 23
ISSN:	0167-7055 1467-8659
DOI:	10.1111/j.1467-8659.2009.01379.x