LiDAR (Light Detection And Ranging) technology is an important means to obtain three-dimensional information of trees and vegetation. However, due the influence scanning mode, environmental occlusion mutual between tree canopies other factors, a point cloud often has different degrees data loss, which affects high-precision quantitative extraction vegetation parameters. Aiming at problem laser ...

In the past few years, many efficient rendering and surface reconstruction algorithms for point clouds have been developed. However, collision detection of point clouds has not been considered until now, although this is a prerequisite to use them for interactive or animated 3D graphics. We present a novel approach for time-critical collision detection of point clouds. Based solely on the point...

Modelling and visualisation methods working directly with point-sampled geometry have developed into attractive alternatives to more traditional mesh-based surface processing. In this paper, we consider a vital step in any point-based surface processing pipeline, point cloud simplification. Building upon the intrinsic point cloud simplification idea put forward in [14], we obtain a simplificati...

We present a new method for point cloud denoising. We introduce a robust smoothing operator Q(r) = r + t∗n∗, inspired in moving least squares and M-estimators robust statistics theory. Our algorithm can be seen as a generalization and improvement of the Fleishman et al algorithm for mesh denoising.

The high pulse frequencies of today’s airborne, mobile and terrestrial laser scanners enable the acquisition of point clouds with densities from some 20-50 points/m for airborne scanners to several thousands points/m for mobile and terrestrial scanners. For the (semi-)automated extraction of geo-information from point clouds these high point densities are very beneficial. The large number of po...

In this paper, we propose a novel surface reconstruction technique based on Bayesian statistics: The measurement process as well as prior assumptions on the measured objects are modeled as probability distributions and Bayes’ rule is used to infer a reconstruction of maximum probability. The key idea of this paper is to define both measurements and reconstructions as point clouds and describe a...