scholarly journals APPLICATION OF RAIL TRACK GEOMETRY MEASURING TROLLEYS FOR GEOREFERENCING OF UAV IMAGES

2021 ◽  
Vol XLIII-B2-2021 ◽  
pp. 101-107
Author(s):  
V. V. Shcherbakov ◽  
M. A. Altyntsev ◽  
M. A. Altyntseva
Keyword(s):  
Low Cost ◽  
Control Point ◽  
Point Clouds ◽  
Aerial Survey ◽  
Control Points ◽  
Data Types ◽  
Track Geometry ◽  
Rail Track ◽  
Uav Images ◽  
The Cost

Abstract. Rail track geometry measuring trolleys are widely used in the railway industry. They can collect information about the state of rails with high accuracy. Nowadays there are a lot of trolleys. Principles of measurements in different trolleys may vary greatly. The trolleys that can use the absolute method of measuring coordinates have advantages. Coordinates of rails and rail track axis can be used as control points for georeferencing of any other surveying data. UAV images are one of these data types. In railways aerial survey using UAVs is mostly used for mapping, gathering data for creation of profiles and some other measurements. UAVs allow reducing the volume of field surveying works. The cost of UAVs is very different. Application of low-cost UAVs imposes increased requirements to distribution of control points. As distribution of control points taken from a trolley trajectory is poor, the issue of such control point application emerges. The study of opportunity to use the trolley trajectory for georeferencing of UAV images is carried out. Accuracy estimation of generating photogrammetric models and image-based point clouds using control point coordinates measured with the trolley is given. Accuracy of measuring obstruction clearances with the help of image-based point clouds is estimated.

scholarly journals ASSESSING THE RELIABILITY AND THE ACCURACY OF ATTITUDE EXTRACTED FROM VISUAL ODOMETRY FOR LIDAR DATA GEOREFERENCING

2017 ◽  
Vol XLII-2/W6 ◽  
pp. 201-208
Author(s):  
B. Leroux ◽  
J. Cali ◽  
J. Verdun ◽  
L. Morel ◽  
H. He
Keyword(s):  
Test Bench ◽  
Low Cost ◽  
Control Point ◽  
Visual Odometry ◽  
Airborne Lidar ◽  
Measurement Unit ◽  
Navigation Systems ◽  
Control Points ◽  
Ground Control Points ◽  
Orientation Parameters

Airborne LiDAR systems require the use of Direct Georeferencing (DG) in order to compute the coordinates of the surveyed point in the mapping frame. An UAV platform does not derogate to this need, but its payload has to be lighter than this installed onboard so the manufacturer needs to find an alternative to heavy sensors and navigation systems. For the georeferencing of these data, a possible solution could be to replace the Inertial Measurement Unit (IMU) by a camera and record the optical flow. The different frames would then be processed thanks to photogrammetry so as to extract the External Orientation Parameters (EOP) and, therefore, the path of the camera. The major advantages of this method called Visual Odometry (VO) is low cost, no drifts IMU-induced, option for the use of Ground Control Points (GCPs) such as on airborne photogrammetry surveys. In this paper we shall present a test bench designed to assess the reliability and accuracy of the attitude estimated from VO outputs. The test bench consists of a trolley which embeds a GNSS receiver, an IMU sensor and a camera. The LiDAR is replaced by a tacheometer in order to survey the control points already known. We have also developped a methodology applied to this test bench for the calibration of the external parameters and the computation of the surveyed point coordinates. Several tests have revealed a difference about 2–3 centimeters between the control point coordinates measured and those already known.

scholarly journals ASSESSING THE ACCURACY AND PRECISION OF IMPERFECT POINT CLOUDS FOR 3D INDOOR MAPPING AND MODELING

2018 ◽  
Vol IV-4/W6 ◽  
pp. 3-10
Author(s):  
J. Chen ◽  
O. E. Mora ◽  
K. C. Clarke
Keyword(s):  
Low Cost ◽  
Random Noise ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Point Clouds ◽  
Accuracy And Precision ◽  
Wide Range ◽  
Sharp Edges ◽  
The Cost ◽  
Indoor Spaces

<p><strong>Abstract.</strong> In recent years, growing public interest in three-dimensional technology has led to the emergence of affordable platforms that can capture 3D scenes for use in a wide range of consumer applications. These platforms are often widely available, inexpensive, and can potentially find dual use in taking measurements of indoor spaces for creating indoor maps. Their affordability, however, usually comes at the cost of reduced accuracy and precision, which becomes more apparent when these instruments are pushed to their limits to scan an entire room. The point cloud measurements they produce often exhibit systematic drift and random noise that can make performing comparisons with accurate data difficult, akin to trying to compare a fuzzy trapezoid to a perfect square with sharp edges. This paper outlines a process for assessing the accuracy and precision of these imperfect point clouds in the context of indoor mapping by integrating techniques such as the extended Gaussian image, iterative closest point registration, and histogram thresholding. A case study is provided at the end to demonstrate use of this process for evaluating the performance of the Scanse Sweep 3D, an ultra-low cost panoramic laser scanner.</p>

scholarly journals Modelling and Visualization of Three Dimensional Objects Using Inexpensive Digital Cameras

2018 ◽  
Author(s):  
Ismail Elkhrachy
Keyword(s):  
Low Cost ◽  
Three Dimensional ◽  
Point Clouds ◽  
3D Models ◽  
Bundle Adjustment ◽  
Control Points ◽  
Digital Cameras ◽  
Three Dimensional Objects ◽  
Spatial Positioning ◽  
And Control

This paper analyses and evaluate the precision and the accuracy the capability of low-cost terrestrial photogrammetry by using many digital cameras to construct a 3D model of an object. To obtain the goal, a building façade has imaged by two inexpensive digital cameras such as Canon and Pentax camera. Bundle adjustment and image processing calculated by using Agisoft PhotScan software. Several factors will be included during this study, different cameras, and control points. Many photogrammetric point clouds will be generated. Their accuracy will be compared with some natural control points which collected by the laser total station of the same building. The cloud to cloud distance will be computed for different comparison 3D models to investigate different variables. The practical field experiment showed a spatial positioning reported by the investigated technique was between 2-4cm in the 3D coordinates of a façade. This accuracy is optimistic since the captured images were processed without any control points.

scholarly journals EXPERIENCES OF UAV SURVEYS APPLIED TO ENVIRONMENTAL RISK MANAGEMENT

2016 ◽  
Vol XLI-B1 ◽  
pp. 797-801
Author(s):  
M. Caprioli ◽  
R. Trizzino ◽  
F. Mazzone ◽  
M. Scarano
Keyword(s):  
Environmental Risk ◽  
Low Cost ◽  
Total Error ◽  
Point Clouds ◽  
Environmental Risks ◽  
Time Intervals ◽  
Mobile Mapping ◽  
Risk Levels ◽  
Uav Images ◽  
Photogrammetric Measurement

In this paper the results of some surveys carried out in an area of Apulian territory affected by serious environmental hazard are presented. Unmanned Aerial Vehicles (UAV) are emerging as a key engineering tool for future environmental survey tasks. UAVs are increasingly seen as an attractive low-cost alternative or supplement to aerial and terrestrial photogrammetry due to their low cost, flexibility, availability and readiness for duty. In addition, UAVs can be operated in hazardous or temporarily inaccessible locations, that makes them very suitable for the assessment and management of environmental risk conditions. In order to verify the reliability of these technologies an UAV survey and A LIDAR survey have been carried outalong about 1 km of coast in the Salento peninsula, near the towns of San Foca, Torre dellOrso and SantAndrea( Lecce, Southern Italy). This area is affected by serious environmental risks due to the presence of dangerous rocky cliffs named falesie. The UAV platform was equipped with a photogrammetric measurement system that allowed us to obtain a mobile mapping of the fractured fronts of dangerous rocky cliffs. UAV-images data have been processed using dedicated software (AgisoftPhotoscan). The point clouds obtained from both the UAV and LIDAR surveys have been processed using Cloud Compare software, with the aim of testing the UAV results with respect to the LIDAR ones. The total error obtained was of centimeter-order that is a very satisfactory result. The environmental information has been arranged in an ArcGIS platform in order to assess the risk levels. The possibility to repeat the survey at time intervals more or less close together depending on the measured levels of risk and to compare the output allows following the trend of the dangerous phenomena. In conclusion, for inaccessible locations of dangerous rocky bodies the UAV survey coupled with GIS methodology proved to be a key engineering tool for the management of environmental risks.

scholarly journals Non-Rigid Vehicle-Borne LiDAR-Assisted Aerotriangulation

2019 ◽  
Vol 11 (10) ◽  
pp. 1188
Author(s):  
Li Zheng ◽  
Yuhao Li ◽  
Meng Sun ◽  
Zheng Ji ◽  
Manzhu Yu ◽  
...  
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Point Clouds ◽  
Necessary Condition ◽  
Control Points ◽  
The Road ◽  
Aerial Vehicle ◽  
Joint Mapping ◽  
Close Range ◽  
Uav Images

VLS (Vehicle-borne Laser Scanning) can easily scan the road surface in the close range with high density. UAV (Unmanned Aerial Vehicle) can capture a wider range of ground images. Due to the complementary features of platforms of VLS and UAV, combining the two methods becomes a more effective method of data acquisition. In this paper, a non-rigid method for the aerotriangulation of UAV images assisted by a vehicle-borne light detection and ranging (LiDAR) point cloud is proposed, which greatly reduces the number of control points and improves the automation. We convert the LiDAR point cloud-assisted aerotriangulation into a registration problem between two point clouds, which does not require complicated feature extraction and match between point cloud and images. Compared with the iterative closest point (ICP) algorithm, this method can address the non-rigid image distortion with a more rigorous adjustment model and a higher accuracy of aerotriangulation. The experimental results show that the constraint of the LiDAR point cloud ensures the high accuracy of the aerotriangulation, even in the absence of control points. The root-mean-square error (RMSE) of the checkpoints on the x, y, and z axes are 0.118 m, 0.163 m, and 0.084m, respectively, which verifies the reliability of the proposed method. As a necessary condition for joint mapping, the research based on VLS and UAV images in uncontrolled circumstances will greatly improve the efficiency of joint mapping and reduce its cost.

Reducing the Size of NURBs Controls Nets Using Genetic Algorithms and CUDA

2011 ◽  
Author(s):  
Matthew J. O’Neal ◽  
Cameron J. Turner
Keyword(s):  
Search Algorithm ◽  
Low Cost ◽  
Control Point ◽  
Parallel Architecture ◽  
Global Error ◽  
Local Error ◽  
Optimal Size ◽  
Control Points ◽  
Desktop Computer ◽  
Control Net

The typical goals for defining a control net for a Non-Uniform Rations B-spline (NURBs) based metamodel from a given set of data the desired result is the smallest set of control points in the least possible time while minimizing local and/or global error. Current metamodel fitting algorithms iteratively find and eliminate the largest sources of local error, thus creating a very accurate control net with sub-optimal size. Since, control net size is directly related to the speed the control net can be searched for global optima, the size must be reduced as much as possible without increasing local or global error. Current algorithms can model discontinuous portions of data by clustering numerous control points close together. This is both inefficient to search and may cause the search algorithm to become numerically unstable and crash because of control points placed too closely together. Furthermore, many current algorithms do not take advantage of the weight property of each control point. In this paper, a Genetic Algorithm (GA) is used to optimize existing control nets as well as create new control nets from data sets. In order to offer a comparable creation time for the control net, parallel programming techniques are used incorporating the CUDA GPU Architecture. CUDA was chosen because it is low cost, highly parallel architecture available on millions of computers. The code is intended for a single desktop computer, running a maximum of 4 CUDA devices, not a CUDA cluster. This approach may have fitting applications to both metamodels and geometric fitting of NURBs objects.

scholarly journals Suitability Study of Structure-from-Motion for the Digitisation of Architectural (Heritage) Spaces to Apply Divergent Photograph Collection

Symmetry ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 1981
Author(s):  
Juan Moyano ◽  
Juan E. Nieto-Julián ◽  
Daniel Antón ◽  
Elena Cabrera ◽  
David Bienvenido-Huertas ◽  
...  
Keyword(s):  
Structure From Motion ◽  
Laser Scanning ◽  
Low Cost ◽  
Point Clouds ◽  
Control Points ◽  
Architectural Heritage ◽  
High Definition ◽  
Symmetrical Configuration ◽  
Architectural Spaces

The digitisation of architectural heritage has experienced a great development of low-cost and high-definition data capture technologies, thus enabling the accurate and effective modelling of complex heritage assets. Accordingly, research has identified the best methods to survey historic buildings, but the suitability of Structure-from-Motion/Multi-view-Stereo (SfM/MVS) for interior square symmetrical architectural spaces is unexplored. In contrast to the traditional SfM surveying for which the camera surrounds the object, the photograph collection approach is divergent in courtyards. This paper evaluates the accuracy of SfM point clouds against Terrestrial Laser Scanning (TLS) for these large architectural spaces with a symmetrical configuration, with the main courtyard of Casa de Pilatos in Seville, Spain, as a case study. Two different SfM surveys were conducted: (1) Without control points, and (2) referenced using a total station. The first survey yielded unacceptable results: A standard deviation of 0.0576 m was achieved in the northwest sector of the case study, mainly because of the difficulty of aligning the SfM and TLS data due to the way they are produced. This value could be admissible depending on the purpose of the photogrammetric model.

scholarly journals Short Communication: A simple workflow for robust low-cost UAV-derived change detection without ground control points

2019 ◽  
Author(s):  
Kristen L. Cook ◽  
Michael Dietze
Keyword(s):  
Change Detection ◽  
Low Cost ◽  
Point Clouds ◽  
Standard Approach ◽  
Ground Control ◽  
Control Points ◽  
Ground Control Points ◽  
3D Point Clouds ◽  
Tectonically Active ◽  
Comparative Accuracy

Abstract. High quality 3D point clouds generated from repeat camera-equipped unmanned aerial vehicle (UAV) surveys are increasingly being used to investigate landscape changes and geomorphic processes. Point cloud quality can be expressed as accuracy in a comparative (i.e., from survey to survey) and absolute (between survey and an external reference system) sense. Here we present a simple workflow for calculating pairs or sets of point clouds with a high comparative accuracy, without the need for ground control points or a dGPS equipped UAV. We demonstrate the efficacy of the new approach using a consumer-grade UAV in two contrasting landscapes: the coastal cliffs on the Island of Rügen, Germany, and the tectonically active Daan River gorge in Taiwan. Compared to a standard approach using ground control points, our workflow results in a nearly identical distribution of measured changes. Compared to a standard approach without ground control, our workflow reduces the level of change detection from several meters to 10–15 cm. This approach enables robust change detection using UAVs in settings where ground control is not possible.

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 A Comparison of Low-Cost Sensor Systems in Automatic Cloud-Based Indoor 3D Modeling

2020 ◽  
Vol 12 (16) ◽  
pp. 2624 ◽  
Author(s):  
Matias Ingman ◽  
Juho-Pekka Virtanen ◽  
Matti T. Vaaja ◽  
Hannu Hyyppä
Keyword(s):  
3D Modeling ◽  
Low Cost ◽  
Laser Scanner ◽  
Point Clouds ◽  
Sensor Systems ◽  
Modeling Process ◽  
Recent Developments ◽  
Fully Automatic ◽  
The Cost ◽  
Indoor Spaces

The automated 3D modeling of indoor spaces is a rapidly advancing field, in which recent developments have made the modeling process more accessible to consumers by lowering the cost of instruments and offering a highly automated service for 3D model creation. We compared the performance of three low-cost sensor systems; one RGB-D camera, one low-end terrestrial laser scanner (TLS), and one panoramic camera, using a cloud-based processing service to automatically create mesh models and point clouds, evaluating the accuracy of the results against a reference point cloud from a higher-end TLS. While adequately accurate results could be obtained with all three sensor systems, the TLS performed the best both in terms of reconstructing the overall room geometry and smaller details, with the panoramic camera clearly trailing the other systems and the RGB-D offering a middle ground in terms of both cost and quality. The results demonstrate the attractiveness of fully automatic cloud-based indoor 3D modeling for low-cost sensor systems, with the latter providing better model accuracy and completeness, and with all systems offering a rapid rate of data acquisition through an easy-to-use interface.

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