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Neural network methods for NURBS curve and surface interpolation

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Abstract

New algorithms based on artificial neural network models are presented for cubic NURBS curve and surface interpolation. When all the knot spans are identical, the NURBS curve interpolation procedure degenerates into that of uniform rational B-spline curves. If all the weights of data points are identical, then the NURBS curve interpolation procedure degenerates into the integral B-spline curve interpolation.

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Authors and Affiliations

  1. Department of Computer Science & Technology, Tsinghua University, 100084, Beijing

    Kaihuai Qin

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  1. Kaihuai Qin
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Additional information

This project is supported by the National Natural Science Foundation of China.

Qin Kaihuai obtained his Ph.D. degree in computer-aided manufacturing from Huazhong University of Science and Technology in 1990. He is now an Associate Profess at Tsinghua University. His research areas include computer graphics, geometric modeling, spline curves and surfaces, neural network, scientific visualization, virtual reality and CAD/CAM.

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Qin, K. Neural network methods for NURBS curve and surface interpolation. J. of Comput. Sci. & Technol. 12, 76–89 (1997). https://doi.org/10.1007/BF02943147

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  • DOI: https://doi.org/10.1007/BF02943147

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