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IEEE International Conference on Image Processing (ICIP)

Contribution To Book Anthology

Abstract 

In this paper we present a remeshing algorithm which drastically reduces the aliasing artifacts inherent in regularly-sampled remeshed objects. Starting from a semi-regular mesh, the proposed algorithm reduces the remeshing error and avoids aliasing by displacing vertices such that most samples of the original mesh are present in the remeshed model as well. Computational efficiency is provided by using a search-tree, which efficiently gathers vertices near a given point in a 3D space. Compared to the state-of-the-art semi-regular remesher, the proposed remesher drastically improves the visual quality of the high-frequency regions in remeshed objects. Additionally, the proposed algorithm yields a lower remeshing error, which is reflected by a significantly increased PSNR upper-bound in wavelet-based compression of such meshes.

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