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Proceedings ArticleDOI

Zippered polygon meshes from range images

Greg Turk, +1 more
- pp 311-318
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TLDR
A method for combining a collection of range images into a single polygonal mesh that completely describes an object to the extent that it is visible from the outside is presented.
Abstract
Range imaging offers an inexpensive and accurate means for digitizing the shape of three-dimensional objects. Because most objects self occlude, no single range image suffices to describe the entire object. We present a method for combining a collection of range images into a single polygonal mesh that completely describes an object to the extent that it is visible from the outside.The steps in our method are: 1) align the meshes with each other using a modified iterated closest-point algorithm, 2) zipper together adjacent meshes to form a continuous surface that correctly captures the topology of the object, and 3) compute local weighted averages of surface positions on all meshes to form a consensus surface geometry.Our system differs from previous approaches in that it is incremental; scans are acquired and combined one at a time. This approach allows us to acquire and combine large numbers of scans with minimal storage overhead. Our largest models contain up to 360,000 triangles. All the steps needed to digitize an object that requires up to 10 range scans can be performed using our system with five minutes of user interaction and a few hours of compute time. We show two models created using our method with range data from a commercial rangefinder that employs laser stripe technology.

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Citations
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References
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Journal ArticleDOI

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Proceedings ArticleDOI

Surface reconstruction from unorganized points

TL;DR: A general method for automatic reconstruction of accurate, concise, piecewise smooth surfaces from unorganized 3D points that is able to automatically infer the topological type of the surface, its geometry, and the presence and location of features such as boundaries, creases, and corners.
Journal ArticleDOI

Object modelling by registration of multiple range images

TL;DR: A new approach is proposed which works on range data directly and registers successive views with enough overlapping area to get an accurate transformation between views and is performed by minimizing a functional which does not require point-to-point matches.
Proceedings ArticleDOI

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TL;DR: An application independent algorithm that uses local operations on geometry and topology to reduce the number of triangles in a triangle mesh and results from two different geometric modeling applications illustrate the strengths of the algorithm.