The pipeline to get the semi-regular mesh of a specific physical object is long and fastidious : physical acquisition (creating a dense point cloud), cleaning/meshing (creating an irregular triangle mesh), and semi-regular remeshing. Moreover, these three stages are generally independent, and processed successively by different tools. To overcome this issue, we propose in this paper a new frame...

We present a new framework for point cloud denoising by patch-collaborative spectral analysis. A collaborative generalization of each surface patch is defined, combining similar patches from the denoised surface. The Laplace–Beltrami operator of the collaborative patch is then used to selectively smooth the surface in a robust manner that can gracefully handle high levels of noise, yet preserve...

This paper presents adaptable methods for achieving fast collision detection using the GPU and Nvidia CUDA together with Octrees. Earlier related work have focused on serial methods, while this paper presents a parallel solution which shows that there is a great increase in time if the number of operations is large. Two different models of the environment and the industrial robot are presented,...

In the field of computer vision, over-segmentation, or super-pixels generation, has become a popular preliminary stage for high level image analysis processes (such as classification, registration, detection and recognition). New acquisition technologies, like RGBD or LiDAR cameras, enable the capturing of 3D point clouds containing both color and geometrical information. We propose a new gener...

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.

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...

In both ecology and forestry, there is a high demand for structural information of forest stands. Forest structures, due to their heterogeneity and density, are often difficult to assess. Hence, a variety of technologies are being applied to account for this ”difficult to come by” information. Common techniques are aerial images or groundand airborne-Lidar. In the present study we evaluate the ...