论文信息 - GNG3D - A Software Tool for Mesh Optimization Based on Neural Networks

GNG3D - A Software Tool for Mesh Optimization Based on Neural Networks

A new software tool-denoted as GNG3D for mesh optimization is presented. This tool has been implemented taking as a basis a new method which is based on neural networks and consists on two differentiated phases: an optimization phase and a reconstruction phase. The optimization phase is developed applying an optimization algorithm based on the Growing Neural Gas model, which constitutes an unsupervised incremental clustering algorithm. The primary goal of this phase is to obtain a simplified set of vertices representing the best approximation of the original 3D object. In the reconstruction phase we use the information provided by the optimization algorithm to reconstruct the faces obtaining in such a way the optimized mesh. Finally, we will report some experimental results and examples for some 3D models using the different options implemented in the GNG3D tool.

[1] Bernd Fritzke,et al. Growing cell structures--A self-organizing network for unsupervised and supervised learning , 1994, Neural Networks.

[2] Yizhou Yu. Surface Reconstruction from Unorganized Points Using Self-Organizing Neural Networks , 1999 .

[3] Greg Turk,et al. Re-tiling polygonal surfaces , 1992, SIGGRAPH.

[4] Hugues Hoppe,et al. Progressive meshes , 1996, SIGGRAPH.

[5] T. Kohonen. Self-Organized Formation of Correct Feature Maps , 1982 .

[6] T. Martínez,et al. Competitive Hebbian Learning Rule Forms Perfectly Topology Preserving Maps , 1993 .

[7] Heekuck Oh,et al. Neural Networks for Pattern Recognition , 1993, Adv. Comput..

[8] B Fritzke,et al. A growing neural gas network learns topologies. G. Tesauro, DS Touretzky, and TK Leen, editors , 1995, NIPS 1995.

[9] Markus H. Gross,et al. Efficient Triangular Surface Approximations Using Wavelets and Quadtree Data Structures , 1996, IEEE Trans. Vis. Comput. Graph..

[10] Hans-Peter Seidel,et al. Using growing cell structures for surface reconstruction , 2003, 2003 Shape Modeling International..

[11] Jarek Rossignac,et al. Multi-resolution 3D approximations for rendering complex scenes , 1993, Modeling in Computer Graphics.

[12] Teuvo Kohonen,et al. The self-organizing map , 1990 .

[13] T. Kohonen. Self-organized formation of topology correct feature maps , 1982 .

[14] William E. Lorensen,et al. Decimation of triangle meshes , 1992, SIGGRAPH.