Technical Section: Meshless quadrangulation by global parameterization

  • Authors:
  • Er Li;Bruno LéVy;Xiaopeng Zhang;Wujun Che;Weiming Dong;Jean-Claude Paul

  • Affiliations:
  • LIAMA-National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China;INRIA-ALICE, France;LIAMA-National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China;LIAMA-National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China;LIAMA-National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China and INRIA-ALICE, France;INRIA-ALICE, France and Tsinghua University, Beijing, China

  • Venue:
  • Computers and Graphics
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

Point cloud is a basic description of discrete shape information. Parameterization of unorganized points is important for shape analysis and shape reconstruction of natural objects. In this paper we present a new algorithm for global parameterization of an unorganized point cloud and its application to the meshing of the cloud. Our method is guided by principal directions so as to preserve the intrinsic geometric properties. After initial estimation of principal directions, we develop a kNN(k-nearest neighbor) graph-based method to get a smooth direction field. Then the point cloud is cut to be topologically equivalent to a disk. The global parameterization is computed and its gradients align well with the guided direction field. A mixed integer solver is used to guarantee a seamless parameterization across the cut lines. The resultant parameterization can be used to triangulate and quadrangulate the point cloud simultaneously in a fully automatic manner, where the shape of the data is of any genus.