Publication details for Dr Ioannis IvrissimtzisYoon, Mincheol, Lee, Yunjin Lee, Seungyong Ivrissimtzis, Ioannis & Seidel, Hans-Peter (2007). Surface and normal ensembles for surface reconstruction. Computer-Aided Design 39(5): 408-420.
- Publication type: Journal Article
- ISSN/ISBN: 0010-4485
- DOI: 10.1016/j.cad.2007.02.008
- Keywords: Surface reconstruction; Normal estimation; Ensemble
- Further publication details on publisher web site
- Durham Research Online (DRO) - may include full text
Author(s) from Durham
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
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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.