Title
Efficient spherical parametrization using progressive optimization
Document Type
Conference Proceeding
Publication Date
11-8-2012
Abstract
Spherical mapping is a key enabling technology in modeling and processing genus-0 close surfaces. A closed genus-0 surface can be seamless parameterized onto a unit sphere. We develop an effective progressive optimization scheme to compute such a parametrization, minimizing a nonlinear energy balancing angle and area distortions. Among all existing state-of-the-art spherical mapping methods, the main advantage of our spherical mapping are two-folded: (1) the algorithm converges very efficiently, therefore it is suitable for handling huge geometric models, and (2) it generates bijective and lowly distorted mapping results. © 2012 Springer-Verlag.
Publication Source (Journal or Book title)
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
First Page
170
Last Page
177
Recommended Citation
Wan, S., Ye, T., Li, M., Zhang, H., & Li, X. (2012). Efficient spherical parametrization using progressive optimization. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7633 LNCS, 170-177. https://doi.org/10.1007/978-3-642-34263-9_22