A procedure for real-time 3D meshing reconstruction from sparse data is presented. The approach is based on hierarchical radial basis functions networks, which allow for an effective reconstruction of multi-scale surfaces. This model is extended to provide not only the continuous surface description, but also real-time operation. To this purpose, the HRBF network differential properties have been exploited to produce a denser mesh in regions where geometry is more detailed.
Real-time surface meshing through HRBF networks / N.A. Borghese, S. Ferrari, V. Piuri - In: Proceedings of the international joint conference on neural networks, 2003 / Don Wunsch. - Piscataway : IEEE (Institute of Electrical and Electronics Engineers), 2003 Jul. - ISBN 0780378989. - pp. 1361-1366 (( convegno International Joint Conference on Neural Networks (IJCNN 2003) tenutosi a Portland, USA nel 2003 [10.1109/IJCNN.2003.1223894].
Real-time surface meshing through HRBF networks
N.A. BorghesePrimo
;S. FerrariSecondo
;V. PiuriUltimo
2003
Abstract
A procedure for real-time 3D meshing reconstruction from sparse data is presented. The approach is based on hierarchical radial basis functions networks, which allow for an effective reconstruction of multi-scale surfaces. This model is extended to provide not only the continuous surface description, but also real-time operation. To this purpose, the HRBF network differential properties have been exploited to produce a denser mesh in regions where geometry is more detailed.
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