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Conference Paper

Recovering Structural Information from Triangulated Surfaces

MPS-Authors
http://pubman.mpdl.mpg.de/cone/persons/resource/persons45303

Rössl,  Christian
Computer Graphics, MPI for Informatics, Max Planck Society;

Kobbelt,  Leif
Max Planck Society;

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

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

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Citation

Rössl, C., Kobbelt, L., & Seidel, H.-P. (2001). Recovering Structural Information from Triangulated Surfaces. In T. Lyche, & L. L. Schumaker (Eds.), Mathematical Methods for Curves and Surfaces: Oslo 2000 (pp. 423-432). Nashville, USA: Vanderbilt University.


Cite as: http://hdl.handle.net/11858/00-001M-0000-000F-32C5-8
Abstract
We present a technique for recovering structural information from triangular meshes that can then be used for segmentation, e.g. in reverse engineering applications. In a preprocessing step, we detect feature regions on the surface by classifying the vertices according to some discrete curvature measure. Then we apply a skeletonization algorithm for extracting feature lines from these regions. To achieve this, we generalize the concept of morphological operators to unorganized triangle meshes, providing techniques for noise reduction on the binary feature classification and for skeletonization. The necessary operations are easy to implement, robust, and can be executed efficiently on a mesh data structure.