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Eigenspace-based surface completeness

Yu, Hongchuan, Qin, Yipeng ORCID: and Zhang, Jian J. 2015. Eigenspace-based surface completeness. Journal of Electronic Imaging 24 (2) , 023037. 10.1117/1.JEI.24.2.023037

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We present a surface completeness algorithm that is capable of denoising, removing outliers, and filling in missing patches on point clouds or surfaces. The main advantages of the proposed algorithm include its ability to remove outliers while preserving the details and ability to recover large missing patches. Additionally, our algorithm is a global method, whereby linear programming results are applied to a global optimization problem. This is advantageous because it yields a sparse solution and avoids local minima. Experiments further demonstrate the effectiveness of our algorithm through applications to point clouds where noise, outliers, and large missing patches exist.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Publisher: Society of Photo-optical Instrumentation Engineers (SPIE)
ISSN: 1017-9909
Last Modified: 04 Nov 2022 12:31

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