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Learning smooth objects by probing
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Source Annual Symposium on Computational Geometry archive
Proceedings of the twenty-first annual symposium on Computational geometry table of contents
Pisa, Italy
SESSION: Video/multimedia presentations table of contents
Pages: 364 - 365  
Year of Publication: 2005
ISBN:1-58113-991-8
Authors
Jean-Daniel Boissonnat  INRIA, Sophia-Antipolis
Leonidas J. Guibas  Stanford University, Stanford, CA
Steve Oudot  INRIA, Sophia-Antipolis
Sponsors
ACM: Association for Computing Machinery
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
Publisher
ACM  New York, NY, USA
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ABSTRACT

This video considers the problem of discovering the boundary S of an unknown smooth object O. The discovery process consists of moving a point probing device in the free space around O so that it repeatedly comes in contact with S. We present a probing strategy for generating a sequence of sample points of S, from which a PL-approximation of S can be constructed, within any desired accuracy. This strategy can be applied in any dimension, although its output is guaranteed only for objects embedded in the plane or in 3-space. For pedagogical purpose, the video focuses on the planar case.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Jean-Daniel Boissonnat and Mariette Yvinec. Probing a scene of non-convex polyhedra. Algorithmica, 8:321--342, 1992.
 
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The CGAL Library. Release 3.1 (http://www.cgal.org).
 
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M. Lindenbaum and A. M. Bruckstein. Blind approximation of planar convex sets. IEEE Trans. Robot. Autom., 10(4):517--529, August 1994.
 
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Qt for X11. By Trolltech (http://www.trolltech.com/products/qt/x11.html).
 
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T. J. Richardson. Approximation of planar convex sets from hyperplanes probes. Discrete and Computational Geometry, 18:151--177, 1997.
 
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Collaborative Colleagues:
Jean-Daniel Boissonnat: colleagues
Leonidas J. Guibas: colleagues
Steve Oudot: colleagues