Result: Surface Reconstruction with Enriched Reproducing Kernel Particle Approximation

Title:
Surface Reconstruction with Enriched Reproducing Kernel Particle Approximation
Authors:
Reuter, Patrick, Joyot, Pierre, Trunzler, Jean, Boubekeur, Tamy, Schlick, Christophe
Contributors:
Visualization and manipulation of complex data on wireless mobile devices (IPARLA), INRIA Futurs, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Sciences et Technologies - Bordeaux 1 (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Bordelais de Recherche en Informatique (LaBRI), Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS), ESTIA - Institute of technology (ESTIA)
Source:
EUROGRAPHICS Symposium on Point-Based Graphics, Jul 2005, New York, United States
Publisher Information:
CCSD, 2005.
Publication Year:
2005
Collection:
collection:CNRS
collection:INRIA
collection:ENSEIRB
collection:INRIA-FUTURS
collection:LABRI
collection:ESTIA
collection:UNIV-BORDEAUX
collection:TESTALAIN1
collection:TESTBORDEAUX
collection:INRIA2
collection:UNIVERSITE-BORDEAUX
Subject Terms:
Point-sampled surfaces, point set surfaces, point-based surfaces, meshless representation, sharp features, point-based graphics, ACM: I.: Computing Methodologies, I.3: COMPUTER GRAPHICS, I.3.5: Computational Geometry and Object Modeling, I.3.5.2: Curve, surface, solid, and object representations, [INFO.INFO-GR]Computer Science [cs], Graphics [cs.GR]
Subject Geographic:
New York, United States
Original Identifier:
HAL:
Document Type:
Conference conferenceObject<br />Conference papers
Language:
English
Access URL:
https://inria.hal.science/inria-00260890
https://inria.hal.science/inria-00260890v1/document
https://inria.hal.science/inria-00260890v1/file/erkpa.pdf
Rights:
info:eu-repo/semantics/OpenAccess
Accession Number:
edshal.inria.00260890v1
Database:
HAL

Further Information

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.