Sciweavers

Share
VIS
2004
IEEE

Surface Reconstruction of Noisy and Defective Data Sets

9 years 11 months ago
Surface Reconstruction of Noisy and Defective Data Sets
We present a novel surface reconstruction algorithm that can recover high-quality surfaces from noisy and defective data sets without any normal or orientation information. A set of new techniques are introduced to afford extra noise tolerability, robust orientation alignment, reliable outlier removal, and satisfactory feature recovery. In our algorithm, sample points are first organized by an octree. The points are then clustered into a set of monolithically singlyoriented groups. The inside/outside orientation of each group is determined through a robust voting algorithm. We locally fit an implicit quadric surface in each octree cell. The locally fitted implicit surfaces are then blended to produce a signed distance field using the modified Shepard's method. We develop sophisticated iterative fitting algorithms to afford improved noise tolerance both in topology recognition and geometry accuracy. Furthermore, this iterative fitting algorithm, coupled with a local model selectio...
Hui Xie, Kevin T. McDonnell, Hong Qin
Added 05 Nov 2009
Updated 05 Nov 2009
Type Conference
Year 2004
Where VIS
Authors Hui Xie, Kevin T. McDonnell, Hong Qin
Comments (0)
books