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Conference Paper

Normal Based Estimation of the Curvature Tensor for Triangular Meshes

MPS-Authors
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Theisel,  Holger
Computer Graphics, MPI for Informatics, Max Planck Society;

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Rössl,  Christian
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

Theisel, H., Rössl, C., Zayer, R., & Seidel, H.-P. (2004). Normal Based Estimation of the Curvature Tensor for Triangular Meshes. In 12th Pacific Conference on Computer Graphics and Applications, PG 2004 (pp. 288-297). Los Alamitos, USA: IEEE.


Cite as: https://hdl.handle.net/11858/00-001M-0000-000F-2AE6-B
Abstract
We introduce a new technique for estimating the curvature tensor of a triangular mesh. The input of the algorithm is only a single triangle equipped with its (exact or estimated) vertex normals. This way we get a smooth function of the curvature tensor inside each triangle of the mesh. We show that the error of the new method is comparable with the error of a cubic fitting approach if the incorporated normals are estimated. If the exact normals of the underlying surface are available at the vertices, the error drops signifi- cantly. We demonstrate the applicability of the new estimation at a rather complex data set.