The Community for Technology Leaders
Proceedings Eurographics/IEEE VGTC Symposium Point-Based Graphics (2005)
Stony Brook, NY, USA
June 20, 2005 to June 21, 2005
ISSN: 1511-7813
ISBN: 3-905673-20-7
pp: 79-87
P. Reuter , LIPSI, ESTIA, Bidart, France
J. Trunzler , LIPSI, ESTIA, Bidart, France
P. Joyot , LIPSI, ESTIA, Bidart, France
There are many techniques that reconstruct continuous 3D surfaces from scattered point data coming from laser range scanners. One of the most commonly used representations are point set surfaces (PSS) defined as the set of stationary points of a moving least squares (MLS) projection operator. One interesting property of the MLS projection is to automatically filter out high frequency noise, that is usually present in raw data due to scanning errors. Unfortunately, the MLS projection also smoothes out any high frequency feature, such as creases or corners, that may be present in the scanned geometry, and does not offer any possibility to distinguish between such feature and noise. The main contribution of this paper, is to present an alternative projection operator for surface reconstruction, based on the enriched reproducing kernel particle approximation (ERKPA), which allows the reconstruction process to account for high frequency features, by letting the user explicitly tag the corresponding areas of the scanned geometry.
scanned geometry, surface reconstruction, enriched reproducing kernel particle approximation, scattered point data, laser range scanner, point set surface, moving least square projection operator
P. Reuter, T. Boubekeur, C. Schlick, J. Trunzler, P. Joyot, "Surface reconstruction with enriched reproducing kernel particle approximation", Proceedings Eurographics/IEEE VGTC Symposium Point-Based Graphics, vol. 00, no. , pp. 79-87, 2005, doi:10.1109/PBG.2005.194068
732 ms
(Ver 3.3 (11022016))