A procedure for the construction of 3D surfaces from range data in real-time is here described and discussed. The main goal is to observe the accuracy of the reconstruction through the phases of the 3D model reconstruction. The process is based on the connectionist model, named hierarchical radial basis functions networks (HRBF), which has been proved effective in the reconstruction of smooth surfaces from sparse noisy points. The network goal is to achieve a uniform reconstruction error, equal to measurement error, by stacking non-complete grids of Gaussians at decreasing scales. The HRBF properties allow reconstructing meshes from range data in real-time.
The accuracy of the HRBF networks / S. Ferrari, I. Frosio, V. Piuri, N.A. Borghese - In: Proceedings of the 21. IEEE instrumentation and measurement technology conference, 2004, IMTC'04, Como, Italy, May 18-20, 2004 : vol. 1 / Dario Petri. - [s.l] : IEEE (Institute of Electrical and Electronics Engineers), 2004. - ISBN 078038248X. - pp. 482-486 (( Intervento presentato al 21. convegno IEEE Instrumentation and Measurement Technology Conference (IMTC '2004) tenutosi a Como, Italy nel 2004 [10.1109/IMTC.2004.1351093].
The accuracy of the HRBF networks
S. FerrariPrimo
;I. FrosioSecondo
;V. PiuriPenultimo
;N.A. BorgheseUltimo
2004
Abstract
A procedure for the construction of 3D surfaces from range data in real-time is here described and discussed. The main goal is to observe the accuracy of the reconstruction through the phases of the 3D model reconstruction. The process is based on the connectionist model, named hierarchical radial basis functions networks (HRBF), which has been proved effective in the reconstruction of smooth surfaces from sparse noisy points. The network goal is to achieve a uniform reconstruction error, equal to measurement error, by stacking non-complete grids of Gaussians at decreasing scales. The HRBF properties allow reconstructing meshes from range data in real-time.
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