scholarly journals Geodesics on Point Clouds

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Hongchuan Yu ◽  
Jian J. Zhang ◽  
Zheng Jiao

We present a novel framework to compute geodesics on implicit surfaces and point clouds. Our framework consists of three parts, particle based approximate geodesics on implicit surfaces, Cartesian grid based approximate geodesics on point clouds, and geodesic correction. The first two parts can effectively generate approximate geodesics on implicit surfaces and point clouds, respectively. By introducing the geodesic curvature flow, the third part produces smooth and accurate geodesic solutions. Differing from most of the existing methods, our algorithms can converge to a given tolerance. The presented computational framework is suitable for arbitrary implicit hypersurfaces or point clouds with high genus or high curvature.

2012 ◽  
Vol 12 (04) ◽  
pp. 1250029
Author(s):  
WUSHOUR SLAMU ◽  
JUMING CAO ◽  
XINHUI YAO

As sharp feature manipulation plays an important role in point clouds processing, a novel mean curvature flow-based framework for sharp feature extraction from point clouds is presented in this paper. That is, for input point clouds, a general purpose mean curvature flow-based point clouds smoothing operator is applied on them, thereby, obtaining a smoothing version of the original point clouds. The sharp feature points are labeled as points whose displacements between original point clouds and their smoothing version get local extreme. Implementation of our method on both synthesized and real scanned point clouds show that our methods are effective and robust for the purpose of sharp features extraction tasks.


Sign in / Sign up

Export Citation Format

Share Document