import point_cloud_utils as pcu # v is a #v by 3 NumPy array of vertices # f is an #f by 3 NumPy array of face indexes into v v, f = pcu.load_mesh_vfc("my_model.ply") # Compute principal min/max curvature magnitudes (k1, k2) and directions (d1, d2) # using the one ...
(arXiv). The work adapts PointNet for local geometric properties (e.g. normal and curvature) estimation in noisy point clouds. VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection by Zhou et al. from Apple (arXiv) This work studies 3D object detection using LiDAR point...
point cloud (PC) data is the most common type of input data for constructing the geometric DT capturing as-built information. However, not all geometric DTs
Automatic building extraction and delineation from airborne LiDAR point cloud data of urban environments is still a challenging task due to the variety and complexity at which buildings appear. The Medial Axis Transform (MAT) is able to describe the geometric shape and topology of an object, but ...
It may be noticed, that this computation of the normal vectors for a point cloud is already implemented in some commercial software, e.g., in the Computer Vision System Toolbox of MATLAB or open3D for Python. Since the computation of the normals plays a crucial role in the computation of...
BIM-based reconstruction, Bridge point cloud, Scan-to-BIM BIM-to-FEM, Edge detection 1. Introduction Digital Twin technology which has been increasingly utilised in bridge engineering, has demonstrated significant potential to automate and streamline engineering tasks throughout the asset lifecycle [[1...
Segmentation of point cloud The segmentation of point cloud was conducted as Fig.6. After the preprocessing, the random sample consensus algorithm (RANSAC) was adopted to fit the sample stage plane29and separate the grain point clouds from the background. Then, based on curvature and normal angl...
(arXiv). The work adapts PointNet for local geometric properties (e.g. normal and curvature) estimation in noisy point clouds. VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection by Zhou et al. from Apple (arXiv) This work studies 3D object detection using LiDAR point...
(arXiv). The work adapts PointNet for local geometric properties (e.g. normal and curvature) estimation in noisy point clouds. VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection by Zhou et al. from Apple (arXiv) This work studies 3D object detection using LiDAR point...
Point cloud video delivery will be an important part of future immersive multimedia. In it, objects represented as sets of points are embedded within a video which is streamed and displayed to remote users. This opens possibilities towards remote presenc