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作者:

Xue, Juan (Xue, Juan.) | Zhang, Juan (Zhang, Juan.) | Kong, Dehui (Kong, Dehui.) (学者:孔德慧) | Yin, Baocai (Yin, Baocai.) (学者:尹宝才)

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摘要:

Geometry image is a kind of mesh representation method which presents a three-dimensional geometric model with a regular structure. Because of such a uniform representation, geometry image has become an important tool to effectively deal with complex three-dimensional models. Unfortunately, details of the input mesh are missing or incorrectly reconstructed because of the large stretch of the parametrized vertices. To solve this problem, we propose a new geometry image method adaptively by subdividing particular regions of the mesh via an area stretching metric. We find such regions with larger distortion by calculating the area stretching metric for each triangle, and determine the region to be subdivided. After dealing with the mesh locally, we can obtain a more accurate parametrization, which will produce higher quality reconstructions. Experiments show that, our method can produce reconstruction models with better quality and achieves better PSNR values. 1548-7741/Copyright © 2014 Binary Information Press.

关键词:

Mathematical techniques Algorithms Geometry

作者机构:

  • [ 1 ] [Xue, Juan]Beijing Key Laboratory of Multimedia and Intelligent Software Technology, College of Computer Science and Technology, Beijing University of Technology, Beijing 100124, China
  • [ 2 ] [Zhang, Juan]Beijing Key Laboratory of Multimedia and Intelligent Software Technology, College of Computer Science and Technology, Beijing University of Technology, Beijing 100124, China
  • [ 3 ] [Kong, Dehui]Beijing Key Laboratory of Multimedia and Intelligent Software Technology, College of Computer Science and Technology, Beijing University of Technology, Beijing 100124, China
  • [ 4 ] [Yin, Baocai]Beijing Key Laboratory of Multimedia and Intelligent Software Technology, College of Computer Science and Technology, Beijing University of Technology, Beijing 100124, China

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来源 :

Journal of Information and Computational Science

ISSN: 1548-7741

年份: 2014

期: 10

卷: 11

页码: 3291-3298

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