A procedure for 3D surface reconstruction from range data in strict real-time is presented. The process is based on a connectionist model, the hierarchical radial basis function (HRBF) network, which has been proved to be effective in the reconstruction of smooth, space varying surfaces. An efficient data structure and locality assumptions allowed the derivation of a faster configuration algorithm, without degrading the approximation capabilities. Results show that computing time scales linearly with the number of neurons, and is comparable with the data acquisition time of most commercial scanners so that reconstruction can be performed in real time.
Real-time surface reconstruction through HRBF networks / N. A. Borghese, S. Ferrari, V. Piuri - In: HAVE 2002 : IEEE international workshop on haptic virtual environments and their applications : proceedings : Ottawa, Ontario, Canada, 17-18 November, 2002 / [a cura di] [s.n.]. - Piscataway : Institute of Electrical and Electronics Engineers, 2002. - ISBN 0780376358. - pp. 19-24 (( convegno IEEE International Workshop on Haptic Virtual Environments and their Applications (HAVE) tenutosi a Ottawa nel 2002.
Real-time surface reconstruction through HRBF networks
N. A. BorghesePrimo
;S. FerrariSecondo
;V. PiuriUltimo
2002
Abstract
A procedure for 3D surface reconstruction from range data in strict real-time is presented. The process is based on a connectionist model, the hierarchical radial basis function (HRBF) network, which has been proved to be effective in the reconstruction of smooth, space varying surfaces. An efficient data structure and locality assumptions allowed the derivation of a faster configuration algorithm, without degrading the approximation capabilities. Results show that computing time scales linearly with the number of neurons, and is comparable with the data acquisition time of most commercial scanners so that reconstruction can be performed in real time.Pubblicazioni consigliate
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