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Fast and Robust Detection of Crest Lines on Meshes

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons45777

Yoshizawa,  Shin
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44112

Belyaev,  Alexander
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45449

Seidel,  Hans-Peter
Computer Graphics, MPI for Informatics, Max Planck Society;

Kobbelt,  Leif
Max Planck Society;

Shapiro,  Vadim
Max Planck Society;

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Zitation

Yoshizawa, S., Belyaev, A., & Seidel, H.-P. (2005). Fast and Robust Detection of Crest Lines on Meshes. In Proceedings of the Ninth ACM Symposium on Solid and Physical Modeling 2005 (pp. 227-232). New York, USA: ACM.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000F-2686-E
Zusammenfassung
We propose a fast and robust method for detecting crest lines on surfaces approximated by dense triangle meshes. The crest lines, salient surface features defined via first- and second-order curvature derivatives, are widely used for shape matching and interrogation purposes. Their practical extraction is difficult because it requires good estimation of high-order surface derivatives. Our approach to the crest line detection is based on estimating the curvature tensor and curvature derivatives via local polynomial fitting. Since the crest lines are not defined in the surface regions where the surface focal set (caustic) degenerates, we introduce a new thresholding scheme which exploits interesting relationships between curvature extrema, the so-called MVS functional of Moreton and Sequin, and Dupin cyclides, An application of the crest lines to adaptive mesh simplification is also considered.