The reconstruction of 3D models of human body parts from range data is different with respect to that of general objects as they do not exhibit sharp discontinuities. Following this consideration, HRBF models which implement locally adapted filters are here introduced. They are based on stacking grids of Gaussians one over the other, where each grid operates at a different scale. The grids are not filled with Gaussians but these are inserted only in those crossings where the residual error is greater than the digitising noise. This allows to achieve a uniform reconstruction error. It results a very efficient and fast tool which can operate in real-time. Results on scanning a woman face are reported and discussed.

Scanning and reconstruction of human body parts / N.A. Borghese, S. Ferrari - In: Eurographics '98 : 19. Annual conference of the European association for computer graphics : Lisboa, Portugal, August 31-September 4, 1998 / [a cura di] M. Gobel, F. Nunes Ferreira. - Oxford : Blackwell, 1998. (( Intervento presentato al 19. convegno Eurographics '98 tenutosi a Lisbona nel 1998.

Scanning and reconstruction of human body parts

N.A. Borghese
Primo
;
S. Ferrari
Ultimo
1998

Abstract

The reconstruction of 3D models of human body parts from range data is different with respect to that of general objects as they do not exhibit sharp discontinuities. Following this consideration, HRBF models which implement locally adapted filters are here introduced. They are based on stacking grids of Gaussians one over the other, where each grid operates at a different scale. The grids are not filled with Gaussians but these are inserted only in those crossings where the residual error is greater than the digitising noise. This allows to achieve a uniform reconstruction error. It results a very efficient and fast tool which can operate in real-time. Results on scanning a woman face are reported and discussed.
1998
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/23096
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