scholarly journals 3D DATA ACQUISITION BASED ON OPENCV FOR CLOSE-RANGE PHOTOGRAMMETRY APPLICATIONS

2017 ◽  
Vol XLII-1/W1 ◽  
pp. 377-382 ◽  
Author(s):  
L. Jurjević ◽  
M. Gašparović
Keyword(s):  
Traffic Management ◽  
Point Cloud ◽  
3D Model ◽  
Point Clouds ◽  
Model Reconstruction ◽  
Close Range Photogrammetry ◽  
3D Data ◽  
3D Model Reconstruction ◽  
Close Range ◽  
Real Time Application

Development of the technology in the area of the cameras, computers and algorithms for 3D the reconstruction of the objects from the images resulted in the increased popularity of the photogrammetry. Algorithms for the 3D model reconstruction are so advanced that almost anyone can make a 3D model of photographed object. The main goal of this paper is to examine the possibility of obtaining 3D data for the purposes of the close-range photogrammetry applications, based on the open source technologies. All steps of obtaining 3D point cloud are covered in this paper. Special attention is given to the camera calibration, for which two-step process of calibration is used. Both, presented algorithm and accuracy of the point cloud are tested by calculating the spatial difference between referent and produced point clouds. During algorithm testing, robustness and swiftness of obtaining 3D data is noted, and certainly usage of this and similar algorithms has a lot of potential in the real-time application. That is the reason why this research can find its application in the architecture, spatial planning, protection of cultural heritage, forensic, mechanical engineering, traffic management, medicine and other sciences.

3D Model Reconstruction Based on Close-Range Photogrammetry

2012 ◽  
Vol 263-266 ◽  
pp. 2393-2398
Author(s):  
Wei Zeng ◽  
Si Dong Zhong ◽  
Yuan Yao ◽  
Zhen Feng Shao
Keyword(s):  
High Precision ◽  
3D Model ◽  
Three Dimensional ◽  
Light Detection And Ranging ◽  
Model Reconstruction ◽  
Close Range Photogrammetry ◽  
Object Distance ◽  
3D Model Reconstruction ◽  
Key Technologies ◽  
Close Range

Close-range photogrammetry is a technique of calculating the location, size and shape of measured object by photography whose object distance is generally not greater than 300 meters. Three-dimensional (3D) model reconstruction based on close-range photogrammetry has higher efficiency than that based on Light Detection And Ranging (LiDAR) technique since acquiring texture data simultaneously. This technology reduces the consuming time of 3D model reconstruction, while ensuring high precision. In this paper, processes and key technologies of 3D model reconstruction based on portable close-range photogrammetry are provided, and it feasibility of the technology is verified via taking Taizhou TV Tower as an example.

Integration of Image and Laser Scanning Data Based on Selected Example

2014 ◽  
Vol 19 (2-3) ◽  
pp. 37-44 ◽  
Author(s):  
Sławomir Mikrut ◽  
Agnieszka Moskal ◽  
Urszula Marmol
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
3D Model ◽  
Image Data ◽  
Point Clouds ◽  
Model Reconstruction ◽  
Railway Line ◽  
3D Model Reconstruction ◽  
Conducting Research ◽  
The Village

Abstract The paper aims at presentation of results of research on integration of image and laser data based on selected example. Since a few years the authors have been conducting research on processing image data, and those obtained from laser scanning in the form of the so-called point cloud. In experiments data from terrestrial and mobile laser scanning gained for two different objects were compared: a parish house from Goźlice located in the open-air ethnographic museum at the village of Tokarnia, Poland, and part of the Cracow-Warsaw railway line. The results of those experiments proved that data in the form of point cloud were not always sufficient for a precise 3D model reconstruction. Supplementing point clouds with photogrammetric images seems to be the best solution.

Application of close range photogrammetry in structural health monitoring by processing generated point cloud datasets

2021 ◽  
Author(s):  
Ali Mirzazade ◽  
Cosmin Popescu ◽  
Thomas Blanksvärd ◽  
Björn Täljsten
Keyword(s):  
Health Monitoring ◽  
Point Cloud ◽  
Laser Scanning ◽  
Point Clouds ◽  
Optical Data ◽  
Small Scale ◽  
Relevant Parameter ◽  
Bridge Inspection ◽  
Close Range Photogrammetry ◽  
Close Range

<p>In bridge inspection, vertical displacement is a relevant parameter for both short and long-term health monitoring. Assessing change in deflections could also simplify the assessment work for inspectors. Recent developments in digital camera technology and photogrammetry software enables point cloud with colour information (RGB values) to be generated. Thus, close range photogrammetry offers the potential of monitoring big and small-scale damages by point clouds. The current paper aims to monitor geometrical deviations in Pahtajokk Bridge, Northern Sweden, using an optical data acquisition technique. The bridge in this study is scanned two times by almost one year a part. After point cloud generation the datasets were compared to detect geometrical deviations. First scanning was carried out by both close range photogrammetry (CRP) and terrestrial laser scanning (TLS), while second scanning was performed by CRP only. Analyzing the results has shown the potential of CRP in bridge inspection.</p>

scholarly journals Combined Use of Terrestrial Laser Scanning and UAV Photogrammetry in Mapping Alpine Terrain

2019 ◽  
Vol 11 (18) ◽  
pp. 2154 ◽  
Author(s):  
Ján Šašak ◽  
Michal Gallay ◽  
Ján Kaňuk ◽  
Jaroslav Hofierka ◽  
Jozef Minár
Keyword(s):  
High Resolution ◽  
Point Cloud ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Mutual Orientation ◽  
Close Range Photogrammetry ◽  
Combined Use ◽  
Wide Range ◽  
Close Range

Airborne and terrestrial laser scanning and close-range photogrammetry are frequently used for very high-resolution mapping of land surface. These techniques require a good strategy of mapping to provide full visibility of all areas otherwise the resulting data will contain areas with no data (data shadows). Especially, deglaciated rugged alpine terrain with abundant large boulders, vertical rock faces and polished roche-moutones surfaces complicated by poor accessibility for terrestrial mapping are still a challenge. In this paper, we present a novel methodological approach based on a combined use of terrestrial laser scanning (TLS) and close-range photogrammetry from an unmanned aerial vehicle (UAV) for generating a high-resolution point cloud and digital elevation model (DEM) of a complex alpine terrain. The approach is demonstrated using a small study area in the upper part of a deglaciated valley in the Tatry Mountains, Slovakia. The more accurate TLS point cloud was supplemented by the UAV point cloud in areas with insufficient TLS data coverage. The accuracy of the iterative closest point adjustment of the UAV and TLS point clouds was in the order of several centimeters but standard deviation of the mutual orientation of TLS scans was in the order of millimeters. The generated high-resolution DEM was compared to SRTM DEM, TanDEM-X and national DMR3 DEM products confirming an excellent applicability in a wide range of geomorphologic applications.

3D Model Reconstruction of the Broken Aeroengine Blade Based on the Laplacian of Guassian Detection

2012 ◽  
Vol 490-495 ◽  
pp. 143-146
Author(s):  
Miao Gong ◽  
Hao Wang ◽  
Li Wen Wang
Keyword(s):  
Point Cloud ◽  
Measuring Equipment ◽  
3D Model ◽  
Digital Model ◽  
Point Cloud Data ◽  
Model Reconstruction ◽  
Cloud Data ◽  
3D Model Reconstruction ◽  
Reduced Time ◽  
3D Digital Model

This paper made the 3D model reconstruction of the J34 turban blade. First, collected rough points cloud data by using visual measuring equipment. Then, smoothed and filtered the point cloud data, took the rational simplification, finished pre-processing the point cloud data. Finally, the Laplacian of Guassian Detection was used for fitting the edge of turban blade, and reconstructed the 3D digital model. The results proved that this method improved smoothness of the model, and reduced time and cost of modeling and machining.

Technology of Mobile Phone 3D Model Reconstruction Based on the Geomagic Studio

2014 ◽  
Vol 971-973 ◽  
pp. 1357-1360
Author(s):  
Hong Mei Yu ◽  
Zi Qi Wang
Keyword(s):  
Mobile Phone ◽  
Point Cloud ◽  
3D Model ◽  
Data Access ◽  
Cad Model ◽  
Point Cloud Data ◽  
Model Reconstruction ◽  
Cloud Data ◽  
3D Model Reconstruction ◽  
Modeling Strategy

Studied the modeling strategy and application features of rapid surfacing reconstruction system. The 3D digital model reconstruction of real mobile phone as an example, using non-contact optical 3D scanning point cloud data access to mobile phone, get the mobile phone CAD model through data processing by point stage, polygon stage and shape stage, and the various stages of the process and the target are discussed in this paper.

scholarly journals A novel no-sensors 3D model reconstruction from monocular video frames for a dynamic environment

2021 ◽  
Vol 7 ◽  
pp. e529
Author(s):  
Ghada M. Fathy ◽  
Hanan A. Hassan ◽  
Walaa Sheta ◽  
Fatma A. Omara ◽  
Emad Nabil
Keyword(s):  
Point Cloud ◽  
3D Model ◽  
Dynamic Environment ◽  
Video Frame ◽  
Depth Camera ◽  
Model Reconstruction ◽  
Video Frames ◽  
3D Model Reconstruction ◽  
Realistic Interaction ◽  
Camera Pose

Occlusion awareness is one of the most challenging problems in several fields such as multimedia, remote sensing, computer vision, and computer graphics. Realistic interaction applications are suffering from dealing with occlusion and collision problems in a dynamic environment. Creating dense 3D reconstruction methods is the best solution to solve this issue. However, these methods have poor performance in practical applications due to the absence of accurate depth, camera pose, and object motion.This paper proposes a new framework that builds a full 3D model reconstruction that overcomes the occlusion problem in a complex dynamic scene without using sensors’ data. Popular devices such as a monocular camera are used to generate a suitable model for video streaming applications. The main objective is to create a smooth and accurate 3D point-cloud for a dynamic environment using cumulative information of a sequence of RGB video frames. The framework is composed of two main phases. The first uses an unsupervised learning technique to predict scene depth, camera pose, and objects’ motion from RGB monocular videos. The second generates a frame-wise point cloud fusion to reconstruct a 3D model based on a video frame sequence. Several evaluation metrics are measured: Localization error, RMSE, and fitness between ground truth (KITTI’s sparse LiDAR points) and predicted point-cloud. Moreover, we compared the framework with different widely used state-of-the-art evaluation methods such as MRE and Chamfer Distance. Experimental results showed that the proposed framework surpassed the other methods and proved to be a powerful candidate in 3D model reconstruction.

3D Model Reconstruction System Development Based on Laser-Vision Technology

2016 ◽  
Vol 10 (5) ◽  
pp. 813-820 ◽  
Author(s):  
Huu-Cuong Nguyen ◽  
◽  
Byung-Ryong Lee
Keyword(s):  
Point Cloud ◽  
3D Model ◽  
Scanning System ◽  
3D Point Cloud ◽  
Point Cloud Data ◽  
Model Reconstruction ◽  
Cloud Data ◽  
3D Model Reconstruction ◽  
Rotary Mechanism ◽  
Laser Vision

We propose a three-dimensional (3D) scanning system based on laser-vision technique and rotary mechanism combination for automatic 3D model reconstruction. The proposed scanning system consists of a laser projector, camera, and turntable. For laser-camera calibration, a new and simple method is applied. The 3D point cloud data of the surface of the scanned object are fully collected by integrating the extracted laser profiles from the laser stripe images corresponding to the rotary angles of the rotary mechanism. The obscured laser profile problem is solved by an additional camera at another viewpoint. From the collected 3D point cloud data, the 3D model of the scanned object is reconstructed based on the facet-representation method. The reconstructed 3D models showed the effectiveness and applicability of the proposed 3D scanning system in many 3D model-based applications.

3D Model Reconstruction of the Broken Aero Engine Blade Based on the Detection Operator

2016 ◽  
Vol 693 ◽  
pp. 1289-1293
Author(s):  
Hao Wang ◽  
Guo Jun Tong ◽  
Tao Wang ◽  
Li Wen Wang
Keyword(s):  
Point Cloud ◽  
3D Model ◽  
Digital Model ◽  
Point Cloud Data ◽  
Model Reconstruction ◽  
Cloud Data ◽  
3D Model Reconstruction ◽  
Aero Engine ◽  
Engine Blade ◽  
Reduced Time

This paper made the digital model reconstruction of the RB211 high pressure turban blade. First, collected rough points cloud data by using visual measuring equipment. Then, finished pre-processing the point cloud data, took the rational simplification. Finally, a new algorithm was used to reconstructing the 3D digital model. The results proved that this method improved smoothness of the model, and reduced time and cost of modeling and machining.

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