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.

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>

scholarly journals 3D THERMAL MAPPING OF BUILDING ROOFS BASED ON FUSION OF THERMAL AND VISIBLE POINT CLOUDS IN UAV IMAGERY

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 271-277
Author(s):  
M. Dahaghin ◽  
F. Samadzadegan ◽  
F. Dadras Javan
Keyword(s):  
Camera Calibration ◽  
Point Cloud ◽  
Point Clouds ◽  
Control Points ◽  
Thermal Camera ◽  
Dense Point ◽  
Normal Vectors ◽  
Projection Error ◽  
Orientation Parameters ◽  
Vegetation Layer

Abstract. Thermography is a robust method for detecting thermal irregularities on the roof of the buildings as one of the main energy dissipation parts. Recently, UAVs are presented to be useful in gathering 3D thermal data of the building roofs. In this topic, the low spatial resolution of thermal imagery is a challenge which leads to a sparse resolution in point clouds. This paper suggests the fusion of visible and thermal point clouds to generate a high-resolution thermal point cloud of the building roofs. For the purpose, camera calibration is performed to obtain internal orientation parameters, and then thermal point clouds and visible point clouds are generated. In the next step, both two point clouds are geo-referenced by control points. To extract building roofs from the visible point cloud, CSF ground filtering is applied, and the vegetation layer is removed by RGBVI index. Afterward, a predefined threshold is applied to the normal vectors in the z-direction in order to separate facets of roofs from the walls. Finally, the visible point cloud of the building roofs and registered thermal point cloud are combined and generate a fused dense point cloud. Results show mean re-projection error of 0.31 pixels for thermal camera calibration and mean absolute distance of 0.2 m for point clouds registration. The final product is a fused point cloud, which its density improves up to twice of the initial thermal point cloud density and it has the spatial accuracy of visible point cloud along with thermal information of the building roofs.

A new flexible laser beam profiler for the inspection of train wheels

2020 ◽  
pp. 095440972092200
Author(s):  
M Torabi ◽  
SM Mousavi G ◽  
D Younesian
Keyword(s):  
Laser Beam ◽  
Point Cloud ◽  
Three Dimensional ◽  
Point Clouds ◽  
Calibration Method ◽  
The Other ◽  
Geometrical Parameters ◽  
Prototype System ◽  
Perpendicular Plane ◽  
Wheel Profile

In this paper, a flexible laser beam profiler is proposed to easily measure the profile of a train wheel for railway inspection. It only requires two laser beams (together and in parallel) to obtain two three-dimensional point-clouds based on the laser triangulation principle. Either the laser beam profiler or the wheel can be freely moved. The motion need not be known. The wheel profile will be obtained in two steps. First, the wheel axis position and orientation are obtained by minimizing the distance between one of the point-clouds and the other translated point-cloud, and translation is defined as a rotation of any point on the point-cloud around the wheel axis until it lies on the other point-cloud's laser plane. In the second step, the wheel profile is extracted by selecting one of the point-clouds and rotating it about the wheel axis and by finding the intersection of rotating points and a perpendicular plane, the perpendicular plane is defined as any arbitrary plane which passes through the wheel axis. This method is useful particularly for obtaining geometrical parameters of a wheel such as flange height, flange slope and flange thickness. In order to commission the proposed method, a prototype system was designed and manufactured. The performance of the system, evaluated in different circumstances, shows a measurement error of up to 2%. Compared with classical methods utilizing a caliper or those which use expensive equipment or additional parts such as reference guides, the proposed method is easy to use and flexible. Also, a novel calibration method is utilized to calibrate the system accurately and freely.

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>

Quantification of erosion rate in crop field gullies from point clouds with two different methods  : the case study of Savigny crop field (North of Lausanne, Switzerland) 

2021 ◽  
Author(s):  
Wolff Charlotte ◽  
Choanji Tiggi ◽  
Derron Marc-Henri ◽  
Fei Li ◽  
Jaboyedoff Michel
Keyword(s):  
Data Acquisition ◽  
Point Cloud ◽  
Erosion Rate ◽  
Rainfall Intensity ◽  
Point Clouds ◽  
Prevention Measures ◽  
Small Stream ◽  
Crop Field ◽  
Dense Point

&lt;p&gt;The spreading use of remote techniques is in our daily life benefits to ease and/or speed up the acquisition and analysis of geographical data that can be meaningful for risk assessment or for taking decisions for prevention measures.&lt;/p&gt;&lt;p&gt;Here is presented one of the possible applications for the Unmanned Aerial Vehicle (UAV) acquisition, to evaluate the volume of eroded soils in a crop field due to washout after heavy rains. The case study is located North of Lausanne (Switzerland), in the village of Savigny. It is a crop field with a gentle slope where we can clearly see washout gullies appearing after rainfalls. A great number of small water streams disappeared for more intense agriculture which is the case here : According to topographical maps, a small stream was flowing in the past but disappeared&amp;#160; after 2004. It is interesting to see that after important rainfalls, gullies appear that could correspond to old small stream patterns.&amp;#160;&lt;/p&gt;&lt;p&gt;The data acquisition survey of October 30th, 2020 was done by means of a DJI Phantom 4 RTK flying at an altitude of about 20m and the Pix4d Capture planning mission application. To process the obtained 800 images, the new Pix4D Matic software was tested to get a fast dense point cloud with GSD ~1 cm accuracy, a DEM and an orthophoto. The dense point cloud was then analyzed with two compared methods to estimate the washout volumes, which are (1) inverse Sloping Local Base Level; and (2) Point cloud segmentation based on normal vectors and curvatures.&lt;/p&gt;&lt;p&gt;As a result, these two methods gave a first estimation of the eroded volume of around 15m3 over a surface of 9 hectares which corresponds to an erosion rate of 1,7m3/hectare. These remote and non-destructive techniques are fast and easy compared to conventional field surveys, and the data acquisition and processing could be automated. In conclusion, these techniques provide a relatively low-cost time-series datasets processing to monitor and quantify the ongoing gully erosion.&amp;#160;&lt;/p&gt;&lt;p&gt;Further investigation would be to keep recording the volume and erosion rate estimations after important rainfalls, when clear new gullies appear and to record in the meanwhile the rainfall intensity. This could help assess in a second step the relationship between the erosion rate and the rainfall intensity and control if this relation follows a power-law function. Such a study could also give some clues about the possible impact of climate changes on erosions in crop fields.&amp;#160;&lt;/p&gt;

scholarly journals Impact of UAV Surveying Parameters on Mixed Urban Landuse Surface Modelling

2020 ◽  
Vol 9 (11) ◽  
pp. 656
Author(s):  
Muhammad Hamid Chaudhry ◽  
Anuar Ahmad ◽  
Qudsia Gulzar
Keyword(s):  
Point Cloud ◽  
Large Scale ◽  
Accuracy Assessment ◽  
Computational Cost ◽  
Three Dimensional ◽  
Point Clouds ◽  
Ground Control ◽  
Control Points ◽  
Ground Control Points ◽  
High Computational Cost

Unmanned Aerial Vehicles (UAVs) as a surveying tool are mainly characterized by a large amount of data and high computational cost. This research investigates the use of a small amount of data with less computational cost for more accurate three-dimensional (3D) photogrammetric products by manipulating UAV surveying parameters such as flight lines pattern and image overlap percentages. Sixteen photogrammetric projects with perpendicular flight plans and a variation of 55% to 85% side and forward overlap were processed in Pix4DMapper. For UAV data georeferencing and accuracy assessment, 10 Ground Control Points (GCPs) and 18 Check Points (CPs) were used. Comparative analysis was done by incorporating the median of tie points, the number of 3D point cloud, horizontal/vertical Root Mean Square Error (RMSE), and large-scale topographic variations. The results show that an increased forward overlap also increases the median of the tie points, and an increase in both side and forward overlap results in the increased number of point clouds. The horizontal accuracy of 16 projects varies from ±0.13m to ±0.17m whereas the vertical accuracy varies from ± 0.09 m to ± 0.32 m. However, the lowest vertical RMSE value was not for highest overlap percentage. The tradeoff among UAV surveying parameters can result in high accuracy products with less computational cost.

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 FORMAP: A SIMPLE AND FAST PHOTOGRAMMETRY FRAMEWORK FOR DIRECT GEO-REFERENCING SYSTEMS

2019 ◽  
Vol XLII-2/W17 ◽  
pp. 385-391
Author(s):  
G. Truong Nguyen ◽  
N. Seube
Keyword(s):  
Point Cloud ◽  
A Priori ◽  
Control Points ◽  
A Priori Information ◽  
Ground Control Points ◽  
Dense Point ◽  
Priori Information ◽  
3D Scene ◽  
3D Scene Reconstruction ◽  
Test Result

Abstract. This paper presents FORMap (Fast Ortho Mapping) a simple, automatic, fast and accurate commercial photogrammetry processing software for Unmanned Aerial Vehicles (UAV) imagery equiped with Direct Georeferencing (DG) technology. DG technique allows user to directly geo-reference the acquisition without the use of Ground Control Points (GCP) by providing image external orientation (EO) parameters in a mapping frame. However, it requires a sensor of relatively high quality to provide an accurate EO with each image shot, which is somehow limited by the light weight of UAV payloads. FORMap makes use of EO information delivered by DG as an a priori information to accelerate its photogrammetric processing. We present the functionalities and some application of FORMap in the field of UAV mapping. We evaluate its accuracy and its robustness on several datasets. Test result shows that FORMap is robust for 3D scene reconstruction despite of inaccuracies of DG input data. It is also faster than standard digital photogrammetry solution based on SfM (Structure from Motion) approach and can provide orthophotos and dense point cloud in quasi real-time.

scholarly journals Visibility analysis of point cloud in close range photogrammetry

2014 ◽  
Vol II-5 ◽  
pp. 9-16 ◽  
Author(s):  
B. Alsadik ◽  
M. Gerke ◽  
G. Vosselman
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Point Clouds ◽  
Visibility Analysis ◽  
Close Range Photogrammetry ◽  
Visible Points ◽  
Dense Point ◽  
Close Range ◽  
Mathematical Techniques

The ongoing development of advanced techniques in photogrammetry, computer vision (CV), robotics and laser scanning to efficiently acquire three dimensional geometric data offer new possibilities for many applications. The output of these techniques in the digital form is often a sparse or dense point cloud describing the 3D shape of an object. Viewing these point clouds in a computerized digital environment holds a difficulty in displaying the visible points of the object from a given viewpoint rather than the hidden points. This visibility problem is a major computer graphics topic and has been solved previously by using different mathematical techniques. However, to our knowledge, there is no study of presenting the different visibility analysis methods of point clouds from a photogrammetric viewpoint. The visibility approaches, which are surface based or voxel based, and the hidden point removal (HPR) will be presented. Three different problems in close range photogrammetry are presented: camera network design, guidance with synthetic images and the gap detection in a point cloud. The latter one introduces also a new concept of gap classification. Every problem utilizes a different visibility technique to show the valuable effect of visibility analysis on the final solution.

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.

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