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Estimating surface normals in noisy point cloud data
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Source Annual Symposium on Computational Geometry archive
Proceedings of the nineteenth annual symposium on Computational geometry table of contents
San Diego, California, USA
SESSION: Curve and surface reconstruction table of contents
Pages: 322 - 328  
Year of Publication: 2003
ISBN:1-58113-663-3
Authors
Niloy J. Mitra  Stanford University, CA
An Nguyen  Stanford University, CA
Sponsors
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 31,   Downloads (12 Months): 147,   Citation Count: 10
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ABSTRACT

In this paper we describe and analyze a method based on local least square fitting for estimating the normals at all sample points of a point cloud data (PCD) set, in the presence of noise. We study the effects of neighborhood size, curvature, sampling density, and noise on the normal estimation when the PCD is sampled from a smooth curve in R2 or a smooth surface in R3 and noise is added. The analysis allows us to find the optimal neighborhood size using other local information from the PCD. Experimental results are also provided.


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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N. Amenta, S. Choi, T. K. Dey, and N. Leekha. A simple algorithm for homeomorphic surface reconstruction. International Journal of Computational Geometry and Applications, 12(1-2):125--141, 2002.
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S. Funke and E. Ramos. Smooth-surface reconstruction in near-linear time, 2002.
 
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S. Gumhold, X. Wang, and R. MacLeod. Feature extraction from point clouds. In 10th International Meshing Roundtable, Sandia National Laboratories, pages 293--305, October 2001.
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A. Leon-Garcia. Probability and Random Processes for Electrical Engineering. Addison Wesley, 1994.
 
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CITED BY  11
 
 
 
 
 
 
 
 
 
 

Collaborative Colleagues:
Niloy J. Mitra: colleagues
An Nguyen: colleagues

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