Paper
17 March 2017 Semi-regular remeshing based trust region spherical geometry image for 3D deformed mesh used MLWNN
Naziha Dhibi, Akram Elkefi, Wajdi Bellil, Chokri Ben Amar
Author Affiliations +
Proceedings Volume 10341, Ninth International Conference on Machine Vision (ICMV 2016); 1034112 (2017) https://doi.org/10.1117/12.2268450
Event: Ninth International Conference on Machine Vision, 2016, Nice, France
Abstract
Triangular surface are now widely used for modeling three-dimensional object, since these models are very high resolution and the geometry of the mesh is often very dense, it is then necessary to remesh this object to reduce their complexity, the mesh quality (connectivity regularity) must be ameliorated. In this paper, we review the main methods of semi-regular remeshing of the state of the art, given the semi-regular remeshing is mainly relevant for wavelet-based compression, then we present our method for re-meshing based trust region spherical geometry image to have good scheme of 3d mesh compression used to deform 3D meh based on Multi library Wavelet Neural Network structure (MLWNN). Experimental results show that the progressive re-meshing algorithm capable of obtaining more compact representations and semi-regular objects and yield an efficient compression capabilities with minimal set of features used to have good 3D deformation scheme.
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Naziha Dhibi, Akram Elkefi, Wajdi Bellil, and Chokri Ben Amar "Semi-regular remeshing based trust region spherical geometry image for 3D deformed mesh used MLWNN", Proc. SPIE 10341, Ninth International Conference on Machine Vision (ICMV 2016), 1034112 (17 March 2017); https://doi.org/10.1117/12.2268450
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KEYWORDS
Spherical lenses

Wavelets

Image compression

3D image processing

3D modeling

Distortion

Detection and tracking algorithms

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