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Fully Automatic Registration of Multiple 3D Data Sets

Daniel Huber and Martial Hebert
Carnegie Mellon University, IEEE Computer Society Workshop on Computer Vision Beyond the Visible Spectrum(CVBVS 2001), December, 2001

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Abstract

This paper presents a method for automatically registering multiple three dimensional (3D) data sets. Previous approaches required manual specification of initial pose estimates or relied on external pose measurement systems. In contrast, our method does not assume any knowledge of initial poses or even which data sets overlap. Our automatic registration algorithm begins by converting the input data into surface meshes, which are pair-wise registered using a surface matching engine. The resulting matches are tested for surface consistency, but some incorrect matches may be locally undetectable. A global optimization process searches a graph constructed from these potentially faulty pair-wise matches for a connected sub-graph containing only correct matches, employing a global consistency measure to detect incorrect, but locally consistent matches. From this sub-graph, the final poses of all views can be computed directly. We apply our algorithm to the problem of 3D digital reconstruction of real world objects and show results for a collection of automatically digitized objects.

BibTeX Reference
@conference{Huber-2001-8369,
title = {Fully Automatic Registration of Multiple 3D Data Sets},
author = {Daniel Huber and Martial Hebert},
booktitle = {IEEE Computer Society Workshop on Computer Vision Beyond the Visible Spectrum(CVBVS 2001)},
keyword = {registration, 3D modeling, visibility consistency, range images},
sponsor = {Eastman Kodak Company},
school = {Robotics Institute , Carnegie Mellon University},
month = {December},
year = {2001},
address = {Pittsburgh, PA},
}
2017-09-13T10:45:27+00:00