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Durham University

Computer Science

Profile

Publication details for Dr Ioannis Ivrissimtzis

Yoon, 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.

Author(s) from Durham

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, StuetzleW. 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.