Medial axis approximation from inner Voronoi balls

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Medial axis approximation from inner Voronoi balls: a demo of the Mesecina tool

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Annual Symposium on Computational Geometry archive
Proceedings of the twenty-third annual symposium on Computational geometry table of contents

Gyeongju, South Korea

SESSION: Session 4A: video session table of contents

Pages: 123 - 124

Year of Publication: 2007

ISBN:978-1-59593-705-6

Authors

Balint Miklos	ETH, Zürich, Switzerland
Joachim Giesen	Max-Planck Institut für Informatik, Saarbrücken, Germany
Mark Pauly	ETH, Zürich, Switzerland

Sponsors

SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
ACM: Association for Computing Machinery
SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques

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ACM New York, NY, USA

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ABSTRACT

We illustrate a simple algorithm for approximating the medial axis of a 2D shape with smooth boundary from a sample of this boundary. The algorithm is compared to a more general approximation method that builds on the same idea, namely, to approximate the shape by a union of balls. While not as general, our algorithm is simpler, faster and numerically more stable. Both algorithms are visualized using the Mesecina tool, which is also described.

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.

	1	Computational Geometry Algorithms Library. http://www.cgal.org/.
	2	CORE library. http://cs.nyu.edu/exact/core/.
	3	Nina Amenta , Marshall Bern , David Eppstein, The crust and the &Bgr;-Skeleton: combinatorial curve reconstruction, Graphical Models and Image Processing, v.60 n.2, p.125-135, March 1, 1998 [doi>10.1006/gmip.1998.0465]
	4	Nina Amenta, Sunghee Choi, and Ravi Kolluri. The power crust, unions of balls, and the medial axis transform. Computational Geometry: Theory and Applications, 19(2--3):127--153, 2001.
	5	Nina Amenta , Ravi Krishna Kolluri, The Medial axis of a union of balls, Computational Geometry: Theory and Applications, v.20 n.1-2, p.25-37, October 2001 [doi>10.1016/S0925-7721(01)00033-5]
	6	Dominique Attali , Annick Montanvert, Computing and simplifying 2D and 3D continuous skeletons, Computer Vision and Image Understanding, v.67 n.3, p.261-273, Sept. 1997 [doi>10.1006/cviu.1997.0536]
	7	André Lieutier, Any open bounded subset of Rⁿ has the same homotopy type than its medial axis, Proceedings of the eighth ACM symposium on Solid modeling and applications, June 16-20, 2003, Seattle, Washington, USA [doi>10.1145/781606.781620]