\( \newcommand{\E}{\mathrm{E}} \) \( \newcommand{\A}{\mathrm{A}} \) \( \newcommand{\R}{\mathrm{R}} \) \( \newcommand{\N}{\mathrm{N}} \) \( \newcommand{\Q}{\mathrm{Q}} \) \( \newcommand{\Z}{\mathrm{Z}} \) \( \def\ccSum #1#2#3{ \sum_{#1}^{#2}{#3} } \def\ccProd #1#2#3{ \sum_{#1}^{#2}{#3} }\)
CGAL 4.4 - Triangulated Surface Mesh Segmentation
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Bibliographic References
[1]

David Arthur and Sergei Vassilvitskii. k-means++: the advantages of careful seeding. In Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms, SODA '07, pages 1027–1035, Philadelphia, PA, USA, 2007. Society for Industrial and Applied Mathematics.

[2]

Yuri Boykov, Olga Veksler, and Ramin Zabih. Fast approximate energy minimization via graph cuts. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23:2001, 2001.

[3]

Ariel Shamir. A survey on mesh segmentation techniques. Computer Graphics Forum, 27(6):1539–1556, 2008.

[4]

L. Shapira, A. Shamir, and D. Cohen-Or. Consistent mesh partitioning and skeletonisation using the shape diameter function. The Visual Computer, 24(4):249–259, 2008.

[5]

C. Tomasi and R. Manduchi. Bilateral filtering for gray and color images. In Proceedings of the Sixth International Conference on Computer Vision, ICCV '98, pages 839–, Washington, DC, USA, 1998. IEEE Computer Society.