A Neural Network Model for Objects with Freeform Surfaces

Article type: Research Article

Authors: Cao, En^a | Toh, Peng Seng^{b; *}

Affiliations: [a] Vital Technology Pte. Ltd., 206 Innovation Center, Nanyang Avenue, Singapore 2263 | [b] Nanyang Technological University, School of EEE, Nanyang Avenue, Singapore 2263

Correspondence: [*] Author to whom all correspondence should be addressed.

Abstract: A two-layer neural network is proposed for modeling objects with freeform surfaces in computer graphics and computer vision. The parametric form describes not only geometric shapes and normal vectors but also texture and other optical features of arbitrary topology. It also facilitates animation. The implicit form models any convex surfaces and can be used for ray tracing. The algorithm is “neuronal” and suitable for parallel and distributed implementation. Using a well-trained network, the model can be used in computer-aided geometric design and model-based vision.

DOI: 10.3233/ICA-1995-2403

Journal: Integrated Computer-Aided Engineering, vol. 2, no. 4, pp. 281-289, 1995