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Contour-based surface reconstruction using MPU implicit models
Journal article   Open access

Contour-based surface reconstruction using MPU implicit models

Ilya Braude, Jeffrey Marker, Ken Museth, Jonathan Nissanov and David E. Breen 1960-
Drexel University. College of Engineering. Department of Computer Science. Faculty Research and Publications (Comp Sci)
15 Aug 2007
DOI: https://doi.org/10.1016/j.gmod.2006.09.007
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Abstract

Surface reconstruction Contours Implicit models Multi-level Partition of Unity Normal estimation
This paper presents a technique for creating a smooth, closed surface from a set of 2D contours, which have been extracted from a 3D scan. The technique interprets the pixels that make up the contours as points in R3 and employs Multi-level Partition of Unity (MPU) implicit models to create a surface that approximately fits to the 3D points. Since MPU implicit models additionally require surface normal information at each point, an algorithm that estimates normals from the contour data is also described. Contour data frequently contains noise from the scanning and delineation process. MPU implicit models provide a superior approach to the problem of contour-based surface reconstruction, especially in the presence of noise, because they are based on adaptive implicit functions that locally approximate the points within a controllable error bound.We demonstrate the effectiveness of our technique with a number of example datasets, providing images and error statistics generated from our results.

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29 citations in Web of Science
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Domestic collaboration
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Computer Science, Software Engineering
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