scholarly journals Three-Dimensional Reconstruction of Tunnel Face Based on Multiple Images

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Wenge Qiu ◽  
Liao Jian ◽  
Yunjian Cheng ◽  
Hengbin Bai
Keyword(s):  
Point Cloud ◽  
Good Practice ◽  
Three Dimensional ◽  
Railway Tunnel ◽  
Tunnel Face ◽  
Geological Conditions ◽  
Dimensional Reconstruction ◽  
Dense Point ◽  
Software And Hardware ◽  
Drawing Method

The current geological sketch in tunnel engineering is mainly based on sketches of workers. However, geological sketch drawn by workers always offers fundamental data purely due to its drawing mode. A novel drawing method for geological sketch has been introduced using multiview photos in this process. The images of tunnel faces are taken from multiple angles, and every two pictures have overlaps. By measuring the distance between the camera and the tunnel face using a laser range finder, the photographic scale of each photo can be confirmed. SpeededUp Robust Features (SURF) is a good practice for detecting feature points, and the sparse point cloud is reconstructed from multiview photos by structure from motion (SFM). However, the sparse point cloud is not suitable for analysis for structural planes due to its sparsity. Therefore, patch-based multiview stereo (PMVS) is used to reconstruct dense point cloud from the sparse point cloud. After 3D reconstruction, the details of the tunnel face are recorded. The proposed technique was applied to multiview photos acquired in the Xiaosanxia railway tunnel and Fengjie tunnel in Chongqing, China. In order to record the geological conditions of the tunnel face quickly and accurately, Chengdu Tianyou Tunnelkey has developed a set of software and hardware integration system called CameraPad. Besides, CameraPad was used to collect the multiview photos of the tunnel face in the No. 1 Xinan railway tunnel in Jilin, China. By comparing with traditional and existing methods, the proposed method offers a more reductive model for geological conditions of the tunnel face.

scholarly journals GEOREFERENCING AND REPROJECTION ERROR INVESTIGATION ON IMAGE BASED 3D DIGITIZATION AND MAPPING OF HISTORICAL BUILDINGS

2019 ◽  
Vol XLII-2/W11 ◽  
pp. 71-75
Author(s):  
C. Altuntas
Keyword(s):  
Point Cloud ◽  
Large Scale ◽  
Cloud Model ◽  
Low Cost ◽  
Three Dimensional ◽  
Control Points ◽  
Historical Buildings ◽  
Reprojection Error ◽  
Dense Point ◽  
Point Cloud Model

<p><strong>Abstract.</strong> Image based dense point cloud creation is easy and low-cost application for three dimensional digitization of small and large scale objects and surfaces. It is especially attractive method for cultural heritage documentation. Reprojection error on conjugate keypoints indicates accuracy of the model and keypoint localisation in this method. In addition, sequential registration of the images from large scale historical buildings creates big cumulative registration error. Thus, accuracy of the model should be increased with the control points or loop close imaging. The registration of point point cloud model into the georeference system is performed using control points. In this study historical Sultan Selim Mosque that was built in sixteen century by Great Architect Sinan was modelled via photogrammetric dense point cloud. The reprojection error and number of keypoints were evaluated for different base/length ratio. In addition, georeferencing accuracy was evaluated with many configuration of control points with loop and without loop closure imaging.</p>

Research on the Parameter Conversion of Mannequin Curve

2014 ◽  
Vol 543-547 ◽  
pp. 2656-2659
Author(s):  
Bo Ren ◽  
Ji Xin Yang ◽  
Peng Wan ◽  
Xue Heng Tao ◽  
Xue Jun Wang ◽  
...  
Keyword(s):  
Point Cloud ◽  
Three Dimensional ◽  
Measuring System ◽  
Reconstruction Method ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Engineering Software ◽  
Parameter Conversion ◽  
Dimensional Reconstruction ◽  
Design Software

In order to realize the reverse design of human bodys curve, the curves parameter conversion and reconstruction based on non-contact measuring system are studied in the paper. Firstly, obtain the model of point cloud data by the non-contact measurement system, and then import the data into reverse the engineering software Geomagic. Second, process the point cloud data with the method of human characteristic curves and surfaces division, structure fitting surface, and get the three-dimensional reconstruction model of human bodys point cloud data. Lastly, import the model into the forward design software Solidworks with different methods and edit it. Then finish the parameter conversion from Geomagic to the forward design software. The reconstruction method has a good value in reverse design of the mold.

scholarly journals Design and Implementation of Substation Operation Safety Monitoring and Management System Based on Three-Dimensional Reconstruction

2020 ◽  
Author(s):  
Yingyi Yang ◽  
Hao Wu ◽  
Fan Yang ◽  
Xiaoming Mai ◽  
Hui Chen
Keyword(s):  
Management System ◽  
Point Cloud ◽  
Control Level ◽  
Three Dimensional ◽  
Safety Monitoring ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Operational Risks ◽  
Dimensional Reconstruction ◽  
3D Scene

In order to reduce operational risks and to improve the risk management and control level in substation, a substation operation safety monitoring and management system (3D2S2M) has been structured based on three-dimensional (3D) laser modeling technology. In this paper, we introduce how to build such a system and to describe its implementation details. A 3D lidar scanning technology is used to perform a holographic scan of the whole internal area in a substation to obtain color point cloud data of buildings and all equipment. Then, a novel 3D visualization safety monitoring and management system, named 3D2S2M, is developed by performing a 3D reconstruction of the point cloud data. Based on the real 3D scene model of 3D2S2M, the method of 3D distance measurement is used to replace manual on-site investigation for improving operation and maintenance efficiency. In addition, a real-time high-accuracy localization method is proposed, in order to identify and analyze the positioning and the behavior of the personnel, and the movement trajectory of the equipment. By combining positioning information and the electronic fence that used in 3D2S2M, risk levels of the personnel (or equipment) are evaluated and the corresponding alarm is issued to prevent dangerous behavior, thereby the operation risk is reduced in substation.

scholarly journals 3D MODELING FOR ROCK ART DOCUMENTATION USING LIGHTWEIGHT MULTISPECTRAL CAMERA

2019 ◽  
Vol XLII-2/W9 ◽  
pp. 787-793 ◽  
Author(s):  
K. Zainuddin ◽  
Z. Majid ◽  
M. F. M. Ariff ◽  
K. M. Idris ◽  
M. A. Abbas ◽  
...  
Keyword(s):  
Point Cloud ◽  
3D Model ◽  
Rock Art ◽  
Three Dimensional ◽  
Laser Scanner ◽  
3D Point Cloud ◽  
Short Period ◽  
Dense Point ◽  
Close Range ◽  
Multispectral Camera

<p><strong>Abstract.</strong> This paper discusses the use of the lightweight multispectral camera to acquire three-dimensional data for rock art documentation application. The camera consists of five discrete bands, used for taking the motifs of the rock art paintings on a big structure of a cave based on the close-range photogrammetry technique. The captured images then processed using commercial structure-from-motion photogrammetry software, which automatically extracts the tie point. The extracted tie points were then used as input to generate a dense point cloud based on the multi-view stereo (MVS) and produced the multispectral 3D model, and orthophotos in a different wavelength. For comparison, the paintings and the wall surface also observed by using terrestrial laser scanner which capable of recording thousands of points in a short period of time with high accuracy. The cloud-to-cloud comparison between multispectral and TLS 3D point cloud show a sub-cm discrepancy, considering the used of the natural features as control target during 3D construction. Nevertheless, the processing also provides photorealistic orthophoto, indicates the advantages of the multispectral camera in generating dense 3D point cloud as TLS, photorealistic 3D model as RGB optic camera, and also with the multiwavelength output.</p>

Three-Dimensional Reconstruction of Single Input Image Based on Point Cloud

2021 ◽  
Vol 87 (7) ◽  
pp. 479-484
Author(s):  
Yu Hou ◽  
Ruifeng Zhai ◽  
Xueyan Li ◽  
Junfeng Song ◽  
Xuehan Ma ◽  
...  
Keyword(s):  
Point Cloud ◽  
Large Scale ◽  
Three Dimensional ◽  
Data Sets ◽  
Point Cloud Data ◽  
Three Dimensional Reconstruction ◽  
Data Set ◽  
Cloud Data ◽  
Dimensional Reconstruction ◽  
Institute Of Technology

Three-dimensional reconstruction from a single image has excellent future prospects. The use of neural networks for three-dimensional reconstruction has achieved remarkable results. Most of the current point-cloud-based three-dimensional reconstruction networks are trained using nonreal data sets and do not have good generalizability. Based on the Karlsruhe Institute of Technology and Toyota Technological Institute at Chicago ()data set of large-scale scenes, this article proposes a method for processing real data sets. The data set produced in this work can better train our network model and realize point cloud reconstruction based on a single picture of the real world. Finally, the constructed point cloud data correspond well to the corresponding three-dimensional shapes, and to a certain extent, the disadvantage of the uneven distribution of the point cloud data obtained by light detection and ranging scanning is overcome using the proposed method.

scholarly journals Rail Track Detection and Projection-Based 3D Modeling from UAV Point Cloud

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5220
Author(s):  
Shima Sahebdivani ◽  
Hossein Arefi ◽  
Mehdi Maboudi
Keyword(s):  
3D Modeling ◽  
Point Cloud ◽  
3D Model ◽  
Three Dimensional ◽  
Point Clouds ◽  
Rail Track ◽  
Three Dimensional Modeling ◽  
Railway Industry ◽  
Dense Point ◽  
Uav Images

The expansion of the railway industry has increased the demand for the three-dimensional modeling of railway tracks. Due to the increasing development of UAV technology and its application advantages, in this research, the detection and 3D modeling of rail tracks are investigated using dense point clouds obtained from UAV images. Accordingly, a projection-based approach based on the overall direction of the rail track is proposed in order to generate a 3D model of the railway. In order to extract the railway lines, the height jump of points is evaluated in the neighborhood to select the candidate points of rail tracks. Then, using the RANSAC algorithm, line fitting on these candidate points is performed, and the final points related to the rail are identified. In the next step, the pre-specified rail piece model is fitted to the rail points through a projection-based process, and the orientation parameters of the model are determined. These parameters are later improved by fitting the Fourier curve, and finally a continuous 3D model for all of the rail tracks is created. The geometric distance of the final model from rail points is calculated in order to evaluate the modeling accuracy. Moreover, the performance of the proposed method is compared with another approach. A median distance of about 3 cm between the produced model and corresponding point cloud proves the high quality of the proposed 3D modeling algorithm in this study.

scholarly journals Suitability of Automatic Photogrammetric Reconstruction Configurations for Small Archaeological Remains

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2936 ◽  
Author(s):  
Manuel Rodríguez-Martín ◽  
Pablo Rodríguez-Gonzálvez
Keyword(s):  
Data Acquisition ◽  
Point Cloud ◽  
Three Dimensional ◽  
The Other ◽  
Control Points ◽  
Archaeological Remains ◽  
Automated Data Collection ◽  
Acquisition Protocol ◽  
Spatial Reference ◽  
Dense Point

Three-dimensional (3D) reconstruction is a useful technique for the documentation, characterization, and evaluation of small archeological objects. In this research, a comparison among different photogrammetric setups that use different lenses (macro and standard zoom) and dense point cloud generation calibration processes for real specific objects of archaeological interest with different textures, geometries, and materials is raised using an automated data collection. The data acquisition protocol is carried out from a platform with control points referenced with a metrology absolute arm to accurately define a common spatial reference system. The photogrammetric reconstruction is performed considering a camera pre-calibration as well as a self-calibration. The latter is common for most data acquisition situations in archaeology. The results for the different lenses and calibration processes are compared based on a robust statistical analysis, which entails the estimation of both standard Gaussian and non-parametric estimators, to assess the accuracy potential of different configurations. As a result, 95% of the reconstructed points show geometric discrepancies lower than 0.85 mm for the most unfavorable case and less than 0.35 mm for the other cases.

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