Article

Variational shape approximation

Authors:

David Cohen-Steiner,

Mathieu DesbrunAuthors Info & Claims

SIGGRAPH '04: ACM SIGGRAPH 2004 Papers

Pages 905 - 914

https://doi.org/10.1145/1186562.1015817

Published: 01 August 2004 Publication History

Abstract

A method for concise, faithful approximation of complex 3D datasets is key to reducing the computational cost of graphics applications. Despite numerous applications ranging from geometry compression to reverse engineering, efficiently capturing the geometry of a surface remains a tedious task. In this paper, we present both theoretical and practical contributions that result in a novel and versatile framework for geometric approximation of surfaces. We depart from the usual strategy by casting shape approximation as a variational geometric partitioning problem. Using the concept of geometric proxies, we drive the distortion error down through repeated clustering of faces into best-fitting regions. Our approach is entirely discrete and error-driven, and does not require parameterization or local estimations of differential quantities. We also introduce a new metric based on normal deviation, and demonstrate its superior behavior at capturing anisotropy.

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cover image ACM Conferences

SIGGRAPH '04: ACM SIGGRAPH 2004 Papers

August 2004

684 pages

ISBN:9781450378239

DOI:10.1145/1186562

Editor:
Joe Marks
Mitsubishi Electric Research Laboratories (MERL)

Copyright © 2004 ACM.

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Published: 01 August 2004

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SIGGRAPH '04 Paper Acceptance Rate 83 of 478 submissions, 17%;

Overall Acceptance Rate 1,822 of 8,601 submissions, 21%

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