Detection of wheel-set size of rail vehicle using double 2D laser displacement sensors based on point cloud data registration in frequency domain

2017 ◽  
Vol 25 (3) ◽  
pp. 616-624
Author(s):  
王 华 WANG Hua ◽  
邢春齐 XING Chun-qi ◽  
高金刚 GAO Jin-gang ◽  
张 爽 ZHANG Shuang ◽  
朱可可 ZHU Ke-ke
Keyword(s):  
Frequency Domain ◽  
Point Cloud ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Data Registration ◽  
Set Size ◽  
Rail Vehicle ◽  
Displacement Sensors

METHOD OF REGISTRATION FOR 3D FACE POINT CLOUD DATA

2015 ◽  
Vol 75 (2) ◽  
Author(s):  
Mohd Kufaisal Mohd Sidik ◽  
Mohd Shahrizal Sunar ◽  
Muhamad Najib Zamri
Keyword(s):  
Point Cloud ◽  
Three Dimensional ◽  
Human Head ◽  
Point Of View ◽  
Front Face ◽  
Point Cloud Data ◽  
3D Face ◽  
Cloud Data ◽  
Data Registration ◽  
The Face

This paper analyzes the techniques that can be used to perform point cloud data registration for a human face. We found that there is a limitation in full scale viewing on the input data taken from 3D camera which is only represented the front face of a man as the point of view of a camera. This has caused a hole on the surface that is not filled with the point cloud data. This research is done by mapping the retrieved point cloud to the surface of the face template of the human head. By using Coherent Point Drift (CPD) algorithm which is one of the non-rigid registration techniques, the analysis has been done and it shows that the mapping of points for a three-dimensional (3D) face is not done properly where there are some surfaces work well and certain points spread into the wrong area. Consequently, it has resulted in registration failure occurrences due to the concentration of the points which is focusing on the face only.

Surface Reconstruction and Nc Simulation of Auto Rearview Mirror Based on Geomagic Studio

2012 ◽  
Vol 271-272 ◽  
pp. 515-518 ◽  
Author(s):  
Huan Lin ◽  
Dong Qiang Gao ◽  
Jiang Miao Yi
Keyword(s):  
Data Processing ◽  
Surface Reconstruction ◽  
Point Cloud ◽  
Laser Scanner ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Data Registration ◽  
Nc Simulation ◽  
Cnc Programming ◽  
Rearview Mirror

The key techniques of reverse engineering include data acquisition, data processing and model reconstruction.In this paper, with the automobile rearview mirror shell for example, scan the rearview mirror shell surface by laser scanner; then carries on the data processing to point cloud data(data processing include point cloud data registration, joining together and polygon stage processing). On the basis of data processing, fitting NURBS surface by Geomagic Studio software, thus completing surface reconstruction; Finally through the NC machining simulation, gets CNC programming, and to make the rearview mirror surface reconstruction and the numerical simulation.

A CAD Modeling Method of Dental Surface Based on Scanning Data

2012 ◽  
Vol 151 ◽  
pp. 111-115
Author(s):  
Li Cheng Fan ◽  
Feng Feng Zhang
Keyword(s):  
Point Cloud ◽  
Cnc Machining ◽  
Tooth Surface ◽  
Iteration Algorithm ◽  
Point Cloud Data ◽  
Scanning Method ◽  
Cad Modeling ◽  
Cloud Data ◽  
Data Registration ◽  
3D Data

The measurement of the teeth surface and the CAD modeling of the point cloud data are the key basics for the following CNC machining, and the complete data can only be obtained through multi-perspective scanning method. Using ICP iteration algorithm that based on point-to-line to the multi-perspective scanning data, specific to the features of layering scanning, retrograde the 3D data registration to 2D planar registration, and provide the cutting and splicing algorithm for registered tooth data, obtain precise and integrated tooth surface point cloud data, which serves as the CAD model for the following CNC machining.

Realization of a Prototype System for Point Cloud Data Processing in Reverse Engineering

2011 ◽  
Vol 421 ◽  
pp. 419-422 ◽  
Author(s):  
Yong Zhuo ◽  
Juan Peng ◽  
Yan Jun Wu
Keyword(s):  
Reverse Engineering ◽  
Point Cloud ◽  
Processing System ◽  
Prototype System ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Data Registration ◽  
Function Modules ◽  
Data Topology ◽  
And Function

In Reverse Engineering (RE), Point Cloud Data (PCD) processing is of great importance. But at present, a number of key issues about its algorithms are unresolved. This article mainly introduces the author who has done the research and put forward some specific algorithms on the aspects of data topology reconstruction, multi-view data registration and data reduction, and then developed a PCD processing system --3DPointshop, based on OpenGL and MFC. Through a series of instances of tests show that the prototype system which contains the algorithms and function modules will be able to implement on PCD processing well and could achieve the practical application level.

Registration and Fusion of UAV LiDAR System Sequence Images and Laser Point Clouds

2020 ◽  
Author(s):  
Jiayong Yu ◽  
Longchen Ma ◽  
Maoyi Tian, ◽  
Xiushan Lu
Keyword(s):  
Point Cloud ◽  
Image Data ◽  
Point Clouds ◽  
Optical Image ◽  
Point Cloud Data ◽  
Feature Points ◽  
Lidar System ◽  
Registration Accuracy ◽  
Cloud Data ◽  
Intensity Image

The unmanned aerial vehicle (UAV)-mounted mobile LiDAR system (ULS) is widely used for geomatics owing to its efficient data acquisition and convenient operation. However, due to limited carrying capacity of a UAV, sensors integrated in the ULS should be small and lightweight, which results in decrease in the density of the collected scanning points. This affects registration between image data and point cloud data. To address this issue, the authors propose a method for registering and fusing ULS sequence images and laser point clouds, wherein they convert the problem of registering point cloud data and image data into a problem of matching feature points between the two images. First, a point cloud is selected to produce an intensity image. Subsequently, the corresponding feature points of the intensity image and the optical image are matched, and exterior orientation parameters are solved using a collinear equation based on image position and orientation. Finally, the sequence images are fused with the laser point cloud, based on the Global Navigation Satellite System (GNSS) time index of the optical image, to generate a true color point cloud. The experimental results show the higher registration accuracy and fusion speed of the proposed method, thereby demonstrating its accuracy and effectiveness.

Sign in / Sign up

Export Citation Format

Share Document