Surface and normal ensembles for surface reconstruction
SCIE
SCOPUS
- Title
- Surface and normal ensembles for surface reconstruction
- Authors
- Mincheol Yoon; Yunjin Lee; Lee, S; Ioannis Ivrissimtzis; Hans-Peter Seidel
- Date Issued
- 2007-05
- Publisher
- ELSEVIER SCI LTD
- Abstract
- The majority of the existing techniques for surface reconstruction and the closely related problem of normal reconstruction are deterministic. Their main advantages are the speed and, given a reasonably good initial input, the high quality of the reconstructed surfaces. Nevertheless, their deterministic nature may hinder them from effectively handling incomplete data with noise and outliers. An ensemble is a statistical technique which can improve the performance of deterministic algorithms by putting them into a statistics based probabilistic setting. In this paper, we study the suitability of ensembles in normal and surface reconstruction. We experimented with a widely used normal reconstruction technique [Hoppe H, DeRose T, Duchamp T, McDonald J, Stuetzle W. Surface reconstruction from unorganized points. Computer Graphics 1992;71-8] and Multi-level Partitions of Unity implicits for surface reconstruction [Ohtake Y, Belyaev A, Alexa M, Turk G, Seidel H-P Multi-level partition of unity implicits. ACM Transactions on Graphics 2003;22(3):463-70], showing that normal and surface ensembles can successfully be combined to handle noisy point sets. (c) 2007 Elsevier Ltd. All rights reserved.
- Keywords
- surface reconstruction; normal estimation; ensemble; probabilistic approach
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/23341
- DOI
- 10.1016/j.cad.2007.02.008
- ISSN
- 0010-4485
- Article Type
- Article
- Citation
- COMPUTER-AIDED DESIGN, vol. 39, no. 5, page. 408 - 420, 2007-05
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