Adaptive Geometry Images for Remeshing

Geometry images are a kind of completely regular remeshing methods for mesh representation. Traditional geometry images have difficulties in achieving optimal reconstruction errors and preserving manually selected geometric details, due to the limitations of parametrization methods. To solve two iss...

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Bibliographic Details
Main Authors: Lina Shi, Dehui Kong, Shaofan Wang, Baocai Yin
Format: Article
Language:English
Published: Wiley 2017-01-01
Series:International Journal of Digital Multimedia Broadcasting
Online Access:http://dx.doi.org/10.1155/2017/2724184
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Summary:Geometry images are a kind of completely regular remeshing methods for mesh representation. Traditional geometry images have difficulties in achieving optimal reconstruction errors and preserving manually selected geometric details, due to the limitations of parametrization methods. To solve two issues, we propose two adaptive geometry images for remeshing triangular meshes. The first scheme produces geometry images with the minimum Hausdorff error by finding the optimization direction for sampling points based on the Hausdorff distance between the original mesh and the reconstructed mesh. The second scheme produces geometry images with higher reconstruction precision over the manually selected region-of-interest of the input mesh, by increasing the number of sampling points over the region-of-interest. Experimental results show that both schemes give promising results compared with traditional parametrization-based geometry images.
ISSN:1687-7578
1687-7586