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Journal Article

Mesh Segmentation Driven by Gaussian Curvature

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Yamauchi,  Hitoshi
Computer Graphics, MPI for Informatics, Max Planck Society;

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Gumhold,  Stefan
Computer Graphics, MPI for Informatics, Max Planck Society;

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Zayer,  Rhaleb
Computer Graphics, MPI for Informatics, Max Planck Society;

/persons/resource/persons45449

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

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Citation

Yamauchi, H., Gumhold, S., Zayer, R., & Seidel, H.-P. (2005). Mesh Segmentation Driven by Gaussian Curvature. The Visual Computer, 21, 649-658.


Cite as: https://hdl.handle.net/11858/00-001M-0000-000F-270A-F
Abstract
Mesh parameterization is a fundamental problem in computer graphics as it allows for texture mapping and facilitates a lot of mesh processing tasks. Although there exists a variety of good parameterization methods for meshes that are topologically equivalent to a disc, the segmentation into nicely parameterizable charts of higher genus meshes has been studied less. In this paper we propose a new segmentation method for the generation of charts that can be flattened efficiently. The integrated Gaussian curvature is used to measure the developability of a chart and a robust and simple scheme is proposed to integrate the Gaussian curvature. The segmentation approach evenly distributes Gaussian curvature over the charts and automatically ensures disc-like topology of each chart. For numerical stability, we use area on the Gauss map to represent Gaussian curvature. Resulting parameterization shows that charts generated in this way have less distortion compared to charts generated by other methods.