Deep Points Consolidation

Wu, Shihao; Huang, Hui; Gong, Minglun; Zwicker, Matthias; Cohen-Or, Daniel (2015). Deep Points Consolidation. ACM transactions on graphics, 34(6), p. 176. Association for Computing Machinery 10.1145/2816795.2818073

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In this paper, we present a consolidation method that is based on a new representation of 3D point sets. The key idea is to augment each surface point into a deep point by associating it with an inner point that resides on the meso-skeleton, which consists of a mixture of skeletal curves and sheets. The deep points representation is a result of a joint optimization applied to both ends of the deep points. The optimization objective is to fairly distribute the end points across the surface and the meso-skeleton, such that the deep point orientations agree with the surface normals. The optimization converges where the inner points form a coherent meso-skeleton, and the surface points are consolidated with the missing regions completed. The strength of this new representation stems from the fact that it is comprised of both local and non-local geometric information. We demonstrate the advantages of the deep points consolidation technique by employing it to consolidate and complete noisy point-sampled geometry with large missing parts.

Item Type:

Journal Article (Original Article)

Division/Institute:

08 Faculty of Science > Institute of Computer Science (INF) > Computer Graphics Group (CGG)
08 Faculty of Science > Institute of Computer Science (INF)

UniBE Contributor:

Wu, Shihao, Zwicker, Matthias

Subjects:

000 Computer science, knowledge & systems
500 Science > 510 Mathematics

ISSN:

0730-0301

Publisher:

Association for Computing Machinery

Language:

English

Submitter:

Matthias Zwicker

Date Deposited:

08 Jun 2016 12:53

Last Modified:

05 Dec 2022 14:55

Publisher DOI:

10.1145/2816795.2818073

BORIS DOI:

10.7892/boris.81116

URI:

https://boris.unibe.ch/id/eprint/81116

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