scholarly journals EFFICIENT IMPROVEMENT OF POINT CLOUD DATA ACQUISITION AND EXPANSION OF APPLICATION FIELDS INTO ICT PAVEMENT CONSTRUCTION

2019 ◽  
Vol 75 (2) ◽  
pp. I_77-I_85
Author(s):  
Kazushi MORIISHI ◽  
Kazuya TOMIYAMA
Keyword(s):  
Data Acquisition ◽  
Point Cloud ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Pavement Construction ◽  
Application Fields

3D Human Body Data Acquisition and Fit Evaluation of Clothing

2014 ◽  
Vol 989-994 ◽  
pp. 4161-4164 ◽  
Author(s):  
Zhen Wang ◽  
Yue Qi Zhong ◽  
Kai Jie Chen ◽  
Jia Yi Ruan ◽  
Jin Cheng Zhu
Keyword(s):  
Data Acquisition ◽  
Human Body ◽  
Point Cloud ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Clothing Design ◽  
Online Sales ◽  
Kinect Camera ◽  
Distribution Features ◽  
Residual Space

This paper presents the method of 3D human body data acquisition based on 3D scanning and the non-contact fit evaluation of clothing based on the distribution features of residual space between clothing and human body. A Kinect camera is employed to collect point cloud data. The points cloud is treated by Geomagic for noise reduction and surface reconstruction. By analyzing the residual space between clothing and human body, the fit distribution of scanned clothing can be achieved. The fit evaluation will make contributions to clothing design, online sales of clothing and virtual try-on.

Research on 3D Point Cloud Data Acquisition Technology Based on Linear Structured Light

2019 ◽  
Author(s):  
Zhiyi Zhang ◽  
Di Wang ◽  
Ni Liu ◽  
Xuemei Feng ◽  
Nan Geng ◽  
...  
Keyword(s):  
Data Acquisition ◽  
Point Cloud ◽  
Structured Light ◽  
3D Point Cloud ◽  
Point Cloud Data ◽  
Cloud Data

Point Cloud Data Acquisition Based on Reverse Engineering Technology

2012 ◽  
Vol 159 ◽  
pp. 186-190 ◽  
Author(s):  
Xian Sheng Ran ◽  
Li Lin ◽  
Han Bing Wei
Keyword(s):  
Reverse Engineering ◽  
Data Acquisition ◽  
Point Cloud ◽  
Three Dimensional ◽  
Point Cloud Data ◽  
Engineering Technology ◽  
Cloud Data ◽  
Cloud Processing ◽  
Optical Scanner ◽  
Point Cloud Processing

A reverse engineering based point cloud data acquisition method is addressed. The most critical part of reverse engineering (RE) is data acquisition of the digital model, the quality of design is determined by point cloud data acquisition, which is related to the accuracy of design. The measurement of relative position of different parts has been a difficulty of data acquisition. In this paper, the ATOS optical scanner was used as an example to illustrate the principle of three-dimensional scanner, the positioning methods and procedure of point cloud processing. A case study of point cloud data acquisition of car body was used to illustrate three-point positioning principle, which improves the accuracy of measurement compare with traditional method.

scholarly journals Cross-Section Deformation Analysis and Visualization of Shield Tunnel Based on Mobile Tunnel Monitoring System

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1006 ◽  
Author(s):  
Haili Sun ◽  
Shuang Liu ◽  
Ruofei Zhong ◽  
Liming Du
Keyword(s):  
Data Acquisition ◽  
Monitoring System ◽  
Point Cloud ◽  
Laser Scanning ◽  
Local Deformation ◽  
Shield Tunnel ◽  
Deformation Analysis ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Tunnel Monitoring

With the ongoing developments in laser scanning technology, applications for describing tunnel deformation using rich point cloud data have become a significant topic of investigation. This study describes the independently developed a mobile tunnel monitoring system called the second version of Tunnel Scan developed by Capital Normal University (CNU-TS-2) for data acquisition, which has an electric system to control its forward speed and is compatible with various laser scanners such as the Faro and Leica models. A comparison with corresponding data acquired by total station data demonstrates that the data collected by CNU-TS-2 is accurate. Following data acquisition, the overall and local deformation of the tunnel is determined by denoising and 360° deformation analysis of the point cloud data. To enhance the expression of the analysis results, this study proposes an expansion of the tunnel point cloud data into a two-dimensional image via cylindrical projection, followed by an expression of the tunnel deformation through color difference to visualize the deformation. Compared with the three-dimensional modeling method of visualization, this method is easier to implement and facilitates storage. In addition, it is conducive to the performance of comprehensive analysis of problems such as water leakage in the tunnel, thereby achieving the effect of multiple uses for a single image.

scholarly journals Ekstraksi Digital Surface Model (DSM) dari Data Unmanned Aerial Vehicle (UAV) Berbasis Point Cloud

2020 ◽  
Vol 3 (2) ◽  
Author(s):  
Indra Laksana ◽  
R Suharyadi ◽  
M. Pramono Hadi
Keyword(s):  
Data Acquisition ◽  
Point Cloud ◽  
Unmanned Aircraft ◽  
Surface Model ◽  
Digital Surface Model ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Key Points ◽  
Elevation Data ◽  
Data Point

<div class="WordSection1"><p><strong>Abstr</strong><strong>ak. </strong>Akuisisi data dengan menggunakan pesawat tanpa awak semakin sering dilakukan. Penelitian ini memodelkan data elevasi dari pengukuran lapangan dengan menggunakan pesawat tanpa awak. Tujuan dari penelitian ini :(1) untuk menguji kemampuan pesawat tanpa awak dalam mengakuisisi data elevasi, dan (2) untuk membandingkan data elevasi jika ditambahkan data point cloud dan data pengukuran batimetri. Metode pengolahan dengan menggunakan data point cloud dilakukan dengan pertama-tama mencocokkan titik kunci. Pencocokan titik kunci mengkaitkan seluruh hasil foto udara hingga membentuk satu kesatuan area yang telah difoto. Selanjutnya dilakukan penampalan titik ikat pada area yang telah terbentuk dari pencocokan titik kunci. Titik ikat berfungsi sebagai koreksi data pada saat pesawat tanpa awak melakukan pengambilan data. Foto udara yang telah dikoreksi kemudian diolah untuk mendapatkan data <em>point cloud</em>. <em>Point cloud</em> berguna sebagai data penyusun ortofoto dan data <em>Digital Surface Model</em> (DSM). Pengolahan data point cloud hingga menghasilkan DSM dilakukan dengan menggunakan software Pix4D dan Agisoft photoscan. Hasil yang diperoleh menunjukkan bahwa terjadi peningkatan kemampuan DSM ketika data pointcloud ditambahkan data titik ikat dan data pengukuran batimetri. Sehingga dapat disimpulkan bahwa akuisisi data menggunakan pesawat tanpa awak mampu menghasilkan data yang dapat dipercaya. Selain dapat dipercaya akuisisi data dengan pesawat tanpa awak lebih murah jika dibandingkan dengan akuisisi data dengan foto udara.</p><p>Keywords:  digital surface model, pesawat tanpa awak, titik ikat</p><p><strong> </strong></p><p><strong>Abstract. </strong><em>Data acquisition using unmanned aircraft is increasingly being done. This study models elevation data from field measurements using unmanned aircraft. The purpose of this study: (1) to test the ability of unmanned aircraft to acquire elevation data, and (2) to compare elevation data if added point cloud data and bathymetry measurement data. The processing method using point cloud data is done by first matching key points. Matching key points links all aerial photography results to forming a single unit area that has been photographed.</em><em> </em><em>Next, a tie point is carried out in the area formed from matching key points. Tie points function as data correction when unmanned aircraft take data. Corrected aerial photos are then processed to obtain point cloud data.</em><em> </em><em>Point cloud is useful as orthophoto compiler data and Digital Surface Model (DSM) data.</em><em> </em><em>Point cloud data processing to produce DSM is done using Pix4D and Agisoft photoscan software.</em><em>The results obtained showed that there was an increase in DSM capabilities when point cloud data was added to the tie point data and bathymetry measurement data. So, it can be concluded that data acquisition using unmanned aircraft is able to produce reliable data. Besides being reliable, data acquisition with unmanned aircraft is cheaper compared to data acquisition with aerial photography.</em></p></div><strong><em>Keywords:</em> </strong>u<em>nmanned aerial vehicle, ground c point, Digital surface model</em><p class="MsoNormal" style="margin-bottom: .0001pt; text-align: justify; text-justify: inter-ideograph;"> </p>

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.

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