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Tytuł artykułu

3-D surface reconstruction by the means of evolutionary algorithms

Identyfikatory
Warianty tytułu
Konferencja
Evolutionary Computation and Global Optimization (10; Krajowa Konferencja Algorytmy Ewolucyjne i Optymalizacja Globalna; 11-13.06.2007; Będlewo, Poland)
Języki publikacji
EN
Abstrakty
EN
In the paper we propose a new method for an isosurface construction from unorganized points in 3-D. The aim is to combine evolutionary algorithms with a recursive subdivision scheme. the algorithm starts from a base population where each individual represents an N-level surface approximation of an input object. next the population is evaluated and an offspring generation is created with a denser subdivision of surface. The method is illustrated by a set of samples.
Rocznik
Tom
Strony
107--114
Opis fizyczny
Bibliogr. 16 poz., rys., tab.
Twórcy
autor
Bibliografia
  • [1] Aggarwal, A., and Suri, S. Surface approximation and geometric partitions. In Proceedings of the fifth annual ACM-SIAM symposium on Discrete algorithms, 24-33, 1994.
  • [2] Amenta, N., Bern, M., and Kamvysselis, M., "A New Voronoi-Based Surface Reconstruction Algorithm", Proceedings of Siggraph, 415-421, 1998.
  • [3] Cotta C., Scheafer R. (Eds.) Evolutionary Computation. Int. J. Appl. Math. Comp. Special issue, Vol. 14, No. 3, 2004.
  • [4] Hoppe, H. et al. Piecewise smooth surface reconstruction, Proceedings of Siggraph'94, 71-8, 1994.
  • [5] Jeong, W-K., Ivrissimtzis, I. and Seidel, H-P. Neural Meshes: Statistical Learning based on Normals, Proceedings of 11th Pacific Conference on Computer Graphics and Applications, 404-408, 2003.
  • [6] Kodama, T., et al. Evolutionary computation applied to the reconstruction of 3-D surface topography in the SEM, Journal of Electron Microscopy 54 (5), 429-435, 2005.
  • [7] Levoy, M., et. al. The Digital Michelangelo Project: 3D Scanning of Large Statues. Proceedings of Siggraph, 131-144, 2000.
  • [8] Lorensen, W., Cline, H. Marching cubes: a high resolution 3D surface reconstruction algorithm, Proceedings of Siggraph, 163-169, 1987.
  • [9] Michalewicz Z. Genetic Algorithms + Data Structures = Evolutionary Programs. Springer Verlag, Berlin 1996.
  • [10] Nikiel, S., Goinski, A. A recursive subdivision scheme for isosurface construction, Computers and Graphics Vol. 29(1), 155-164, 2005.
  • [11] Obuchowicz A. Evolutionary Algorithms for Global Optimization and Dynamic Systems Diagnosis. Lubuskie Scientific Society, Zielona Góra 2003.
  • [12] Savchenko, V. and Schmitt, L. Reconstructing occlusal surfaces of teeth using a genetic algorithm with simulated annealing type selection. Proceedings of the sixth ACM symposium on Solid modeling and applications, 39-46, 2001.
  • [13] Weinert, K., Mehnen, J., Albersmann, F. and Drerup, P. New Solutions For Surface Reconstruction From Discrete Point Data By Means Of Computational Intelligence, Proceedings of Intelligent Computation in Manufacturing Engineering (ICME'98), 431-438, 1998.
  • [14] Weinert, K., Surmann, T. and Mehnen, J. Evolutionary Surface Reconstruction Using {CSG}-{NURBS}-Hybrids, Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2001), 1456, 2001.
  • [15] Won, K-J., Chang, H-K. Direct reconstruction of displaced subdivision surface from unorganized points, Journal of Graphical Models 64(2), 78-93, 2003.
  • [16] Yu, Y. Surface Reconstruction from Unorganized Points Using Self-Organizing Neural Networks, Proceedings of IEEE Visualization 99, 61-64, 1999.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-PWA6-0040-0013
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