Semi-regular remeshing based trust region spherical geometry image for 3D deformed mesh used MLWNN
| Autor: | Akram Elkefi, Wajdi Bellil, Naziha Dhibi, Chokri Ben Amar |
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| Rok vydání: | 2017 |
| Předmět: |
Surface (mathematics)
Trust region Artificial neural network business.industry 020207 software engineering 02 engineering and technology Image (mathematics) Set (abstract data type) Spherical geometry Wavelet Compression (functional analysis) 0202 electrical engineering electronic engineering information engineering Computer vision Artificial intelligence business Algorithm ComputingMethodologies_COMPUTERGRAPHICS Mathematics |
| Zdroj: | ICMV |
| ISSN: | 0277-786X |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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