scholarly journals INVESTIGATION INTO THE USE OF ACTION CAMERAS IN THE DOCUMENTATION OF ARCHITECTURAL DETAILS – THE CASE STUDY OF A BAROQUE CHAMBER

2018 ◽  
Vol XLII-2 ◽  
pp. 667-674 ◽  
Author(s):  
J. Markiewicz ◽  
S. Łapiński ◽  
M. Pilarska ◽  
R. Bieńkowski ◽  
A. Kaliszewska
Keyword(s):  
Point Cloud ◽  
Low Cost ◽  
Point Clouds ◽  
Distortion Correction ◽  
Ground Control ◽  
Architectural Elements ◽  
Ground Control Points ◽  
Analysis Quality

In this paper the possibility of using the Xiaomi 4K action cameras as a low-cost sensor for the generation of high resolution documentation of architecture and architectural elements in the field of Cultural Heritage was analysed. For that purpose a series of images was acquired together with tachometric measurements to determine the ground control points. Additionally TLS data was collected, which was treated as a reference. For the purpose of point cloud generation the Structure-from-motion (SfM) and Multi- View Stereo (MVS) approaches were used. The following parameters of the collected data and the resulting documentation were tested: the interior orientation parameters analysis, quality of the Xiaomi built-in Lenses Distortion Correction; the accuracy of the orientation on ground control and check points, the point cloud density; the flatness of the walls; the discrepancies between point clouds derived from the low-cost cameras and TLS data, shape of the architectural details based on cross-section analysis. After the analysis of the obtained results it can be concluded that the Xiaomi 4K low-cost sensors are well suited for the purpose of documentation of architecture and architectural details. All the data for the presented investigation were acquired at the baroque residence of the Bieliński Palace in Otwock Wielki in Poland.

scholarly journals EVALUATION OF LOW-COST TERRESTRIAL PHOTOGRAMMETRY FOR 3D RECONSTRUCTION OF COMPLEX BUILDINGS

2017 ◽  
Vol IV-2/W4 ◽  
pp. 199-206 ◽  
Author(s):  
S. Altman ◽  
W. Xiao ◽  
B. Grayson
Keyword(s):  
Natural Disaster ◽  
Point Cloud ◽  
Low Cost ◽  
Point Clouds ◽  
3D Modelling ◽  
Negative Effects ◽  
Accessible Method ◽  
Digital Modelling ◽  
Terrestrial Photogrammetry

Terrestrial photogrammetry is an accessible method of 3D digital modelling, and can be done with low-cost consumer grade equipment. Globally there are many undocumented buildings, particularly in the developing world, that could benefit from 3D modelling for documentation, redesign or restoration. Areas with buildings at risk of destruction by natural disaster or war could especially benefit. This study considers a range of variables that affect the quality of photogrammetric results. Different point clouds of the same building are produced with different variables, and they are systematically tested to see how the output was affected. This is done by geometrically comparing them to a laser scanned point cloud of the same building. It finally considers how best results can be achieved for different applications, how to mitigate negative effects, and the limits of this technique.

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 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 Improvement of 3D Power Line Extraction from Multiple Low-Cost UAV Imagery Using Wavelet Analysis

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 700 ◽  
Author(s):  
Anna Fryskowska
Keyword(s):  
Point Cloud ◽  
Accuracy Assessment ◽  
Low Cost ◽  
Three Dimensional ◽  
Point Clouds ◽  
Power Line ◽  
Power Lines ◽  
Remotely Sensed Data ◽  
Processing Algorithms

Three-dimensional (3D) mapping of power lines is very important for power line inspection. Many remotely-sensed data products like light detection and ranging (LiDAR) have been already studied for power line surveys. More and more data are being obtained via photogrammetric measurements. This increases the need for the implementation of advanced processing techniques. In recent years, there have been several developments in visualisation techniques using UAV (unmanned aerial vehicle) platform photography. The most modern of such imaging systems have the ability to generate dense point clouds. However, image-based point cloud accuracy is very often various (unstable) and dependent on the radiometric quality of images and the efficiency of image processing algorithms. The main factor influencing the point cloud quality is noise. Such problems usually arise with data obtained via low-cost UAV platforms. Therefore, generated point clouds representing power lines are usually incomplete and noisy. To obtain a complete and accurate 3D model of power lines and towers, it is necessary to develop improved data processing algorithms. The experiment tested the algorithms on power lines with different voltages. This paper presents the wavelet-based method of processing data acquired with a low-cost UAV camera. The proposed, original method involves the application of algorithms for coarse filtration and precise filtering. In addition, a new way of calculating the recommended flight height was proposed. At the end, the accuracy assessment of this two-stage filtration process was examined. For this, point quality indices were proposed. The experimental results show that the proposed algorithm improves the quality of low-cost point clouds. The proposed methods improve the accuracy of determining the parameters of the lines by more than twice. About 10% of noise is reduced by using the wavelet-based approach.

scholarly journals Point Cloud Coding Solutions, Subjective Assessment and Objective Measures: A Case Study

Symmetry ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 1955
Author(s):  
Emil Dumic ◽  
Luis A. da Silva Cruz
Keyword(s):  
Point Cloud ◽  
Point Clouds ◽  
Quality Measures ◽  
Subjective Assessment ◽  
Subjective Quality ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Objective Quality

This paper presents a summary of recent progress in compression, subjective assessment and objective quality measures of point cloud representations of three dimensional visual information. Different existing point cloud datasets, as well as discusses the protocols that have been proposed to evaluate the subjective quality of point cloud data. Several geometry and attribute point cloud data objective quality measures are also presented and described. A case study on the evaluation of subjective quality of point clouds in two laboratories is presented. Six original point clouds degraded with G-PCC and V-PCC point cloud compression and five degradation levels were subjectively evaluated, showing high inter-laboratory correlation. Furthermore, performance of several geometry-based objective quality measures applied to the same data are described, concluding that the highest correlation with subjective scores is obtained using point-to-plane measures. Finally, several current challenges and future research directions on point clouds compression and quality evaluation are discussed.

scholarly journals Geocoding Error Correction for InSAR Point Clouds

2018 ◽  
Vol 10 (10) ◽  
pp. 1523 ◽  
Author(s):  
Sina Montazeri ◽  
Fernando Rodríguez González ◽  
Xiao Zhu
Keyword(s):  
Point Cloud ◽  
Point Clouds ◽  
Ground Control ◽  
Control Points ◽  
Persistent Scatterer Interferometry ◽  
Sar Images ◽  
Localization Accuracy ◽  
Ground Control Points ◽  
Persistent Scatterer ◽  
The City

Persistent Scatterer Interferometry (PSI) is an advanced multitemporal InSAR technique that is capable of retrieving the 3D coordinates and the underlying deformation of time-coherent scatterers. Various factors degrade the localization accuracy of PSI point clouds in the geocoding process, which causes problems for interpretation of deformation results and also making it difficult for the point clouds to be compared with or integrated into data from other sensors. In this study, we employ the SAR imaging geodesy method to perform geodetic corrections on SAR timing observations and thus improve the positioning accuracy in the horizontal components. We further utilize geodetic stereo SAR to extract large number of highly precise ground control points (GCP) from SAR images, in order to compensate for the unknown height offset of the PSI point cloud. We demonstrate the applicability of the approach using TerraSAR-X high resolution spotlight images over the city of Berlin, Germany. The corrected results are compared with a reference LiDAR point cloud of Berlin, which confirms the improvement in the geocoding accuracy.

scholarly journals Analysis of the impacts on the quality of UAV photogrammetric products

2020 ◽  
Vol 64 (04) ◽  
pp. 489-507
Author(s):  
Mojca Kosmatin Fras ◽  
Urška Drešček ◽  
Anka Lisec ◽  
Dejan Grigillo
Keyword(s):  
Data Acquisition ◽  
Unmanned Aerial Vehicles ◽  
Spatial Data ◽  
Point Clouds ◽  
Ground Control ◽  
Control Points ◽  
Positional Accuracy ◽  
Ground Control Points ◽  
Aerial Vehicles

Unmanned aerial vehicles, equipped with various sensors and devices, are increasingly used to acquire geospatial data in geodesy, geoinformatics, and environmental studies. In this context, a new research and professional field has been developed – UAV photogrammetry – dealing with photogrammetry data acquisition and data processing, acquired by unmanned aerial vehicles. In this study, we analyse the selected factors that impact the quality of data provided using UAV photogrammetry, with the focus on positional accuracy; they are discussed in three groups: (a) factors related to the camera properties and the quality of images; (b) factors related to the mission planning and execution; and (c) factors related to the indirect georeferencing of images using ground control points. These selected factors are analysed based on the detailed review of relevant scientific publications. Additionally, the influence of the number of ground control points and their spatial distribution on point clouds' positional accuracy has been investigated for the case study. As the conclusion, key findings and recommendations for UAV photogrammetric projects are given; we have highlighted the importance of suitable lighting and weather conditions when performing UAV missions for spatial data acquisition, quality equipment, appropriate parameters of UAV data acquisition, and a sufficient number of ground control points, which should be determined with the appropriate positional accuracy and their correct distribution in the field.

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

2019 ◽  
Vol 7 (4) ◽  
pp. 1009-1017 ◽  
Author(s):  
Kristen L. Cook ◽  
Michael Dietze
Keyword(s):  
Change Detection ◽  
Low Cost ◽  
Point Clouds ◽  
Standard Approach ◽  
Ground Control ◽  
Control Points ◽  
Ground Control Points ◽  
Tectonically Active ◽  
Comparative Accuracy ◽  
Coastal Cliffs

Abstract. High-quality 3-D 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 differential GNSS (dGNSS)-equipped UAV. The method is based on the automated detection of common tie points in stable portions of the survey area. 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 feasible.

scholarly journals Determining the Suitable Number of Ground Control Points for UAS Images Georeferencing by Varying Number and Spatial Distribution

2020 ◽  
Vol 12 (5) ◽  
pp. 876 ◽  
Author(s):  
Valeria-Ersilia Oniga ◽  
Ana-Ioana Breaban ◽  
Norbert Pfeifer ◽  
Constantin Chirila
Keyword(s):  
Coordinate System ◽  
High Precision ◽  
Random Distribution ◽  
Low Cost ◽  
Local Coordinate System ◽  
Point Clouds ◽  
Ground Control ◽  
Unmanned Aerial Systems ◽  
Control Points ◽  
Ground Control Points

Currently, products that are obtained by Unmanned Aerial Systems (UAS) image processing based on structure-from-motion photogrammetry (SfM) are being investigated for use in high precision projects. Independent of the georeferencing process being done directly or indirectly, Ground Control Points (GCPs) are needed to increase the accuracy of the obtained products. A minimum of three GCPs is required to bring the results into a desired coordinate system through the indirect georeferencing process, but it is well known that increasing the number of GCPs will lead to a higher accuracy of the final results. The aim of this study is to find the suitable number of GCPs to derive high precision results and what is the effect of GCPs systematic or stratified random distribution on the accuracy of the georeferencing process and the final products, respectively. The case study involves an urban area of about 1 ha that was photographed with a low-cost UAS, namely, the DJI Phantom 3 Standard, at 28 m above ground. The camera was oriented in a nadiral position and 300 points were measured using a total station in a local coordinate system. The UAS images were processed using the 3DF Zephyr software performing a full BBA with a variable number of GCPs i.e., from four up to 150, while the number and the spatial location of check points (ChPs) was kept constant i.e., 150 for each independent distribution. In addition, the systematic and stratified random distribution of GCPs and ChPs spatial positions was analysed. Furthermore, the point clouds and the mesh surfaces that were automatically derived were compared with a terrestrial laser scanner (TLS) point cloud while also considering three test areas: two inside the area defined by GCPs and one outside the area. The results expressed a clear overview of the number of GCPs needed for the indirect georeferencing process with minimum influence on the final results. The RMSE can be reduced down to 50% when switching from four to 20 GCPs, whereas a higher number of GCPs only slightly improves the results.

scholarly journals MATLAB Virtual Toolbox for Retrospective Rockfall Source Detection and Volume Estimation Using 3D Point Clouds: A Case Study of a Subalpine Molasse Cliff

Geosciences ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 75
Author(s):  
Dario Carrea ◽  
Antonio Abellan ◽  
Marc-Henri Derron ◽  
Neal Gauvin ◽  
Michel Jaboyedoff
Keyword(s):  
Point Cloud ◽  
Natural Hazard ◽  
Point Clouds ◽  
Volume Estimation ◽  
Natural Phenomena ◽  
Frequency Distributions ◽  
Erosion Rates ◽  
3D Point Clouds

The use of 3D point clouds to improve the understanding of natural phenomena is currently applied in natural hazard investigations, including the quantification of rockfall activity. However, 3D point cloud treatment is typically accomplished using nondedicated (and not optimal) software. To fill this gap, we present an open-source, specific rockfall package in an object-oriented toolbox developed in the MATLAB® environment. The proposed package offers a complete and semiautomatic 3D solution that spans from extraction to identification and volume estimations of rockfall sources using state-of-the-art methods and newly implemented algorithms. To illustrate the capabilities of this package, we acquired a series of high-quality point clouds in a pilot study area referred to as the La Cornalle cliff (West Switzerland), obtained robust volume estimations at different volumetric scales, and derived rockfall magnitude–frequency distributions, which assisted in the assessment of rockfall activity and long-term erosion rates. An outcome of the case study shows the influence of the volume computation on the magnitude–frequency distribution and ensuing erosion process interpretation.

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