Abstract
Decomposing a shape into visually meaningful parts comes naturally to humans, but recreating this fundamental operation in computers has been shown to be difficult. Similar challenges have puzzled researchers in shape reconstruction for decades. In this paper, we recognize the strong connection between shape reconstruction and shape decomposition at a fundamental level and propose a method called α-decomposition. The α-decomposition generates a space of decompositions parameterized by α, the diameter of a circle convolved with the input polygon. As we vary the value of α, some structural features appear and disappear quickly while others persist. Therefore, by analyzing the persistence of the features, we can determine better decompositions that are more robust to both geometrical and topological noises. © 2012 Elsevier Ltd. All rights reserved.
Original language | English (US) |
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Pages (from-to) | 466-476 |
Number of pages | 11 |
Journal | Computers & Graphics |
Volume | 36 |
Issue number | 5 |
DOIs | |
State | Published - Aug 2012 |
Externally published | Yes |
Bibliographical note
KAUST Repository Item: Exported on 2020-10-01Acknowledged KAUST grant number(s): KUS-C1-016-04
Acknowledgements: This work of Lien and Lu is supported in part by NSF IIS-096053, Autodesk and FHWA. The work of Amato and Ghosh is supported in part by NSF awards CRI-0551685, CCF-0833199, CCF-0830753, IIS-096053, IIS-0917266, by THECB NHARP award 000512-0097-2009, by Chevron, IBM, Intel, Oracle/Sun and by Award KUS-C1-016-04, made by King Abdullah University of Science and Technology (KAUST). We also thank the anonymous reviewers for the constructive comments.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.