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Proceedings Paper

Estimating Gaussian curvatures from 3D meshes
Author(s): Jingliang Peng; Qing Li; C.-C. Jay Kuo; Manli Zhou
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Paper Abstract

A new approach to estimate the surface curvatures from 3D triangular mesh surfaces with Gaussian curvature's geometry interpretation is proposed in this work. Unlike previous work, the proposed method does not use local surface fitting, partial derivative computation, or oriented normal vector recovery. Instead, the Gaussian curvature is estimated at a vertex as the area of its small neighborhood under the Gaussian map divided by the area of that neighborhood. The proposed approach can handle vertices with the zero Gaussian curvature uniformly without localizing them as a separate process. The performance is further improved with the local Bezier curve approximation and subdivision. The effectiveness of the proposed approach for meshes with a large range of coarseness is demonstrated by experiments. The application of the proposed method to 3D surface segmentation and 3D mesh feature extraction is also discussed.

Paper Details

Date Published: 17 June 2003
PDF: 11 pages
Proc. SPIE 5007, Human Vision and Electronic Imaging VIII, (17 June 2003); doi: 10.1117/12.473938
Show Author Affiliations
Jingliang Peng, Univ. of Southern California (United States)
Qing Li, Univ. of Southern California (United States)
C.-C. Jay Kuo, Univ. of Southern California (United States)
Manli Zhou, Huazhong Univ. of Science and Technology (China)

Published in SPIE Proceedings Vol. 5007:
Human Vision and Electronic Imaging VIII
Bernice E. Rogowitz; Thrasyvoulos N. Pappas, Editor(s)

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