The calculation of parametric NURBS surface interval values using neural networks

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3992 LNCS - II, Issue , 2006, Pages 247-254

  Ülker, Erkan ^a   Arslan, Ahmet ^a  

^a SELCUK UNIVERSITY   (Turkey)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; COSTS; IMAGING TECHNIQUES; NEURAL NETWORKS; PARAMETER ESTIMATION; THREE DIMENSIONAL COMPUTER GRAPHICS;

DIMENSIONAL PARAMETERS; NON-UNIFORM RATIONAL B-SPLINES; PARAMETRIC NURBS SURFACE INTERVAL; THREE DIMENSIONAL OBJECT SIMULATIONS;

COMPUTATION THEORY;

EID: 33746616869     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11758525_33     Document Type: Conference Paper

References (28)

1. Zeid, Ibrahim, CAD/CAM Theory and Practice, McGraw-Hill, (1991).
2. Hyunbo Shim and Euikwon Suh, Contact treatment algorithm for the trimmed NURBS surface Journal of Materials Processing Technology, Vol. 104, p. 200-206, (2000).
3. Hearn, Donald, Computer graphics, Prentice Hall, New Jersey, (1994).
4. Aziguli W., Goetting M. And Zeckzer D., Approximation of NURBS curves and surfaces using adaptive equidistant parameterizations, Tsinghua Science&Technology, Vol. 10, pp. 316-322, (2005).
5. Che X., Liang X., and Li Q., GI continuity conditions of adjacent NURBS surfaces, Computer Aided Geometric Design, Vol. 22, pp. 285-298, (2005).
6. Yang J., and Abdel-Malek K., Approximate swept volumes of NURBS surfaces or solids, Computer Aided Geometric Design, Vol. 22, pp. 1-26, (2004).
7. Ma W., But W.-C., and He P., NURBS based adaptive slicing for efficient rapid prototyping, Computer Aided Geometric Design, Vol. 36, pp. 1309-1325, (2004).
8. Yau H.-T., Kuo M.-J., NURBS machining and feed rate adjustment for high-speed cutting of complex sculptured surfaces, International Journal of Production Research, Taylor & Francis, Vol. 39, (2001).
9. Kumar S., Manocha D., Lastra A., Interactive display of large NURBS models, Visualization and Computer Graphics, IEEE Transactions on Vol. 2, pp. 323-336, (1996).
10. Wang Q, Hua W., Li G., Bao H., Generalized NURBS curves and surfaces, Geometric Modeling and Processing, Proceedings p 365-368, (2004).
11. Hatna A., Grieve B., Cartesian machining versus parametric machining: a comparative study, International Journal of Production Research, Taylor & Francis, Vol 38, (2000).
12. L. Piegl, W. Tiller: Geometry-based triangulation of trimmed NURBS Surfaces. Computer Aided Design, Vol. 30(1), pp. 11-18, (1998).
13. E. Castillo, A. Iglesias, J.M. Gutiérrez, E. Alvarez, J.I., Functional Networks. An application to fitting surfaces, World Multiconference on Systemics, Cybernetics and Informatics, Proceedings of the ISAS-98 Fourth International Conference on Information Systems, Analysis and Synthesis Vol. 2, pp. 579-586, (1998).
14. A. Iglesias, A. Galvez, Applying Functional Networks to CAGD: the Tensor Product Surface Problem, Fourth International Conference on Computer Graphics and Artificial Intelligence, pp. 105-115, (2000).
15. A. Iglesias, A. Galvez, Fitting 3D data points by extending the neural networks paradigm, Computational Methods and Experimental Measurements, WIT Press /Computational Mechanics Publications, Southampton-Boston (Series: Computational Engineering) Vol. 3, 809-818., (2001).
16. A. Iglesias, A. Galvez, Applying Functional Networks to Fit Data Points From B-spline Surfaces, Fitting 3D data points by extending the neural networks paradigm, Proceedings of the Computer Graphics International, CGI'2001, Hong-Kong (China), IEEE Computer Society Press, Los Alamitos, California 329-332, (2001).
17. G. Echevarria, A. Iglesias, A. Galvez, Extending Neural Networks for B-spline Surface Reconstruction, Computational Science-ICCS'2002, Springer-Verlag (Series: Lectures Notes in Computer Science), Berlin Heidelberg, Vol. 2330, pp. 305-314 (2002).
18. A. Iglesias, G. Echevarria, A. Galvez, Functional Networks for B-spline Surface Reconstruction, Future Generation Computer Systems, Special Issue on "Computer Graphics and Geometric Modeling", Vol. 20, Issue 8, pp. 1337-1353, (2004).
19. Barhak, J.,Fischer, A.: Parameterization and reconstruction from 3D scattered points based on neural network and PDE techniques. IEEE Trans. on Visualization and Computer Graphics, 7(1), pp 1-16, (2001).
20. Mishkoff H. C. Understanding Artificial Intelligence, Radio Shack, (1986).
21. Gevarter W. B. Intelligence Machines: An Introductory, Prentice-Hall, (1985).
22. Hoffman, M., Varady, L.: Free-form surfaces for scattered data by neural networks. Journal for Geometry and Graphics, 2, pp. 1-6, (1998).
23. Iglesias, A., Galvez, A.: A new Artificial Intelligence paradigm for Computer-Aided Geometric Design. Lecture Notes in Artificial Intelligence, Vol. 1930, pp. 200-213, (2001).
24. Piegl Les, On NURBS: A Survey, IEEE Computer Graphics and Applications, Vol. 11, No. 1, pp. 55-71, (1991).
25. Rogers David F., Rae A. Earnshaw (editors), State of the Art in Computer Graphics -Visualization and Modeling, New York, Springer-Verlag, pp. 225-269, (1991).
26. C. deBoor, A Practical Guide to Splines, New York, Springer-Verlag, (1978).
27. Watt Alan, Watt Mark, Advanced Animation and Rendering Techniques, New York, AMC press Addision-Wesley, (1992).
28. Foley James D. et al, Introduction to Computer Graphics, Addision-Wesley, (1994).