scholarly journals Workflow: From photo-based 3-D reconstruction of remotely piloted aircraft images to a 3-D geological model

Geosphere ◽  
2019 ◽  
Vol 15 (4) ◽  
pp. 1393-1408 ◽  
Author(s):  
Reuben J. Hansman ◽  
Uwe Ring
Keyword(s):  
Remote Sensing ◽  
United Arab Emirates ◽  
Low Cost ◽  
Three Dimensional ◽  
Point Clouds ◽  
Geological Mapping ◽  
Geological Model ◽  
Geological Processes ◽  
Aerial Imaging ◽  
Remotely Piloted Aircraft

AbstractGeological field mapping is a vital first step in understanding geological processes. During the 20th century, mapping was revolutionized through advances in remote sensing technology. With the recent availability of low-cost remotely piloted aircraft (RPA), field geologists now routinely carry out aerial imaging without the need to use satellite, helicopter, or airplane systems. RPA photographs are processed by photo-based three-dimensional (3-D) reconstruction software, which uses structure-from-motion and multi-view stereo algorithms to create an ultra-high-resolution, 3-D point cloud of a region or target outcrop. These point clouds are analyzed to extract the orientation of geological structures and strata, and are also used to create digital elevation models and photorealistic 3-D models. However, this technique has only recently been used for structural mapping. Here, we outline a workflow starting with RPA data acquisition, followed by photo-based 3-D reconstruction, and ending with a 3-D geological model. The Jabal Hafit anticline in the United Arab Emirates was selected to demonstrate this workflow. At this anticline, outcrop exposure is excellent and the terrain is challenging to navigate due to areas of high relief. This makes for an ideal RPA mapping site and provides a good indication of how practical this method may be for the field geologist. Results confirm that RPA photo-based 3-D reconstruction mapping is an accurate and cost-efficient remote sensing method for geological mapping.

scholarly journals Estimating tree stem diameters and volume from smartphone photogrammetric point clouds

2019 ◽  
Vol 93 (3) ◽  
pp. 411-429 ◽  
Author(s):  
Maria Immacolata Marzulli ◽  
Pasi Raumonen ◽  
Roberto Greco ◽  
Manuela Persia ◽  
Patrizia Tartarino
Keyword(s):  
Low Cost ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Point Clouds ◽  
Stem Volume ◽  
Forest Plot ◽  
3D Point Clouds ◽  
Dense Point ◽  
Minimum Number ◽  
Scale Point

Abstract Methods for the three-dimensional (3D) reconstruction of forest trees have been suggested for data from active and passive sensors. Laser scanner technologies have become popular in the last few years, despite their high costs. Since the improvements in photogrammetric algorithms (e.g. structure from motion—SfM), photographs have become a new low-cost source of 3D point clouds. In this study, we use images captured by a smartphone camera to calculate dense point clouds of a forest plot using SfM. Eighteen point clouds were produced by changing the densification parameters (Image scale, Point density, Minimum number of matches) in order to investigate their influence on the quality of the point clouds produced. In order to estimate diameter at breast height (d.b.h.) and stem volumes, we developed an automatic method that extracts the stems from the point cloud and then models them with cylinders. The results show that Image scale is the most influential parameter in terms of identifying and extracting trees from the point clouds. The best performance with cylinder modelling from point clouds compared to field data had an RMSE of 1.9 cm and 0.094 m3, for d.b.h. and volume, respectively. Thus, for forest management and planning purposes, it is possible to use our photogrammetric and modelling methods to measure d.b.h., stem volume and possibly other forest inventory metrics, rapidly and without felling trees. The proposed methodology significantly reduces working time in the field, using ‘non-professional’ instruments and automating estimates of dendrometric parameters.

scholarly journals ACCURACY ASSESSMENT OF UNDERWATER PHOTOGRAMMETRIC THREE DIMENSIONAL MODELLING FOR CORAL REEFS

2016 ◽  
Vol XLI-B5 ◽  
pp. 821-828 ◽  
Author(s):  
T. Guo ◽  
A. Capra ◽  
M. Troyer ◽  
A. Gruen ◽  
A. J. Brooks ◽  
...  
Keyword(s):  
Coral Cover ◽  
Accuracy Assessment ◽  
Low Cost ◽  
Three Dimensional ◽  
Point Clouds ◽  
3D Modelling ◽  
Relative Accuracy ◽  
3D Point Clouds ◽  
The Individual ◽  
Working Distance

Recent advances in automation of photogrammetric 3D modelling software packages have stimulated interest in reconstructing highly accurate 3D object geometry in unconventional environments such as underwater utilizing simple and low-cost camera systems. The accuracy of underwater 3D modelling is affected by more parameters than in single media cases. This study is part of a larger project on 3D measurements of temporal change of coral cover in tropical waters. It compares the accuracies of 3D point clouds generated by using images acquired from a system camera mounted in an underwater housing and the popular GoPro cameras respectively. A precisely measured calibration frame was placed in the target scene in order to provide accurate control information and also quantify the errors of the modelling procedure. In addition, several objects (cinder blocks) with various shapes were arranged in the air and underwater and 3D point clouds were generated by automated image matching. These were further used to examine the relative accuracy of the point cloud generation by comparing the point clouds of the individual objects with the objects measured by the system camera in air (the best possible values). Given a working distance of about 1.5 m, the GoPro camera can achieve a relative accuracy of 1.3 mm in air and 2.0 mm in water. The system camera achieved an accuracy of 1.8 mm in water, which meets our requirements for coral measurement in this system.

scholarly journals Quantification of Extent, Density, and Status of Aquatic Reed Beds Using Point Clouds Derived from UAV–RGB Imagery

2018 ◽  
Vol 10 (12) ◽  
pp. 1869 ◽  
Author(s):  
Nicolás Corti Meneses ◽  
Florian Brunner ◽  
Simon Baier ◽  
Juergen Geist ◽  
Thomas Schneider
Keyword(s):  
Cross Sections ◽  
Vegetation Index ◽  
Low Cost ◽  
Three Dimensional ◽  
Field Measurements ◽  
Point Clouds ◽  
Conservation Strategies ◽  
Reed Beds ◽  
Combining Data ◽  
Reed Bed

Quantification of reed coverage and vegetation status is fundamental for monitoring and developing lake conservation strategies. The applicability of Unmanned Aerial Vehicles (UAV) three-dimensional data (point clouds) for status evaluation was investigated. This study focused on mapping extent, density, and vegetation status of aquatic reed beds. Point clouds were calculated with Structure from Motion (SfM) algorithms in aerial imagery recorded with Rotary Wing (RW) and Fixed Wing (FW) UAV. Extent was quantified by measuring the surface between frontline and shoreline. Density classification was based on point geometry (height and height variance) in point clouds. Spectral information per point was used for calculating a vegetation index and was used as indicator for vegetation vitality. Status was achieved by combining data on density, vitality, and frontline shape outputs. Field observations in areas of interest (AOI) and optical imagery were used for reference and validation purposes. A root mean square error (RMSE) of 1.58 m to 3.62 m for cross sections from field measurements and classification was achieved for extent map. The overall accuracy (OA) acquired for density classification was 88.6% (Kappa = 0.8). The OA for status classification of 83.3% (Kappa = 0.7) was reached by comparison with field measurements complemented by secondary Red, Green, Blue (RGB) data visual assessments. The research shows that complex transitional zones (water–vegetation–land) can be assessed and support the suitability of the applied method providing new strategies for monitoring aquatic reed bed using low-cost UAV imagery.

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.

3D reconstruction of human head based on consumer RGB-D sensors

2020 ◽  
pp. 2050061
Author(s):  
Zihan Liu ◽  
Guanghong Gong ◽  
Ni Li ◽  
Zihao Yu
Keyword(s):  
3D Reconstruction ◽  
Low Cost ◽  
Three Dimensional ◽  
Human Head ◽  
Point Clouds ◽  
Microsoft Kinect ◽  
Head Model ◽  
Registration Method ◽  
Three Dimensional Modeling ◽  
Texture Generation

Three-dimensional (3D) reconstruction of a human head with high precision has promising applications in scientific research, product design and other fields. However, it still faces resistance from two factors. One is inaccurate registration caused by symmetrical distribution of head feature points, and the other is economic burden due to high-accuracy sensors. Research on 3D reconstruction with portable consumer RGB-D sensors such as the Microsoft Kinect has been highlighted in recent years. Based on our multi-Kinect system, a precise and low-cost three-dimensional modeling method and its system implementation are introduced in this paper. A registration method for multi-source point clouds is provided, which can reduce the fusion differences and reconstruct the head model accurately. In addition, a template-based texture generation algorithm is presented to generate a fine texture. The comparison and analysis of our experiments show that our method can reconstruct a head model in an acceptable time with less memory and better effect.

scholarly journals A Self-Assembly Portable Mobile Mapping System for Archeological Reconstruction Based on VSLAM-Photogrammetric Algorithm

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3952 ◽  
Author(s):  
* ◽  
*
Keyword(s):  
Self Assembly ◽  
Average Distance ◽  
Low Cost ◽  
Three Dimensional ◽  
Point Clouds ◽  
3D Models ◽  
Data Capture ◽  
Information Modeling ◽  
3D Point Clouds ◽  
Mean Square Errors

Three Dimensional (3D) models are widely used in clinical applications, geosciences, cultural heritage preservation, and engineering; this, together with new emerging needs such as building information modeling (BIM) develop new data capture techniques and devices with a low cost and reduced learning curve that allow for non-specialized users to employ it. This paper presents a simple, self-assembly device for 3D point clouds data capture with an estimated base price under €2500; furthermore, a workflow for the calculations is described that includes a Visual SLAM-photogrammetric threaded algorithm that has been implemented in C++. Another purpose of this work is to validate the proposed system in BIM working environments. To achieve it, in outdoor tests, several 3D point clouds were obtained and the coordinates of 40 points were obtained by means of this device, with data capture distances ranging between 5 to 20 m. Subsequently, those were compared to the coordinates of the same targets measured by a total station. The Euclidean average distance errors and root mean square errors (RMSEs) ranging between 12–46 mm and 8–33 mm respectively, depending on the data capture distance (5–20 m). Furthermore, the proposed system was compared with a commonly used photogrammetric methodology based on Agisoft Metashape software. The results obtained demonstrate that the proposed system satisfies (in each case) the tolerances of ‘level 1’ (51 mm) and ‘level 2’ (13 mm) for point cloud acquisition in urban design and historic documentation, according to the BIM Guide for 3D Imaging (U.S. General Services).

Development on Filtering Algorithms of Airborne LiDAR Point Clouds

2012 ◽  
Vol 226-228 ◽  
pp. 1892-1898
Author(s):  
Jian Qing Shi ◽  
Ting Chen Jiang ◽  
Ming Lian Jiao
Keyword(s):  
Remote Sensing ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Filtering Algorithms ◽  
Filtering Algorithm ◽  
Digital Elevation ◽  
City Model ◽  
Elevation Model

Airborne LiDAR is a new kind of surveying technology of remote sensing which developed rapidly during recent years. Raw laser scanning point clouds data include terrain points, building points, vegetation points, outlier points, etc.. In order to generate digital elevation model (DEM) and three-dimensional city model,these point clouds data must be filtered. Mathematical morphology based filtering algorithm, slope based filtering algorithm, TIN based filtering algorithm, moving surface based filtering algorithm, scanning lines based filtering algorithm and so on several representative filtering algorithms for LiDAR point clouds data have been introduced and discussed and contrasted in this paper. Based on these algorithms summarize the studying progresss about the filtering algorithm of airborne LiDAR point clouds data in home and abroad. In the end, the paper gives an expectation which will provides a reference for the following relative study.

scholarly journals SYNCHRONIZATION OF PICAM CAMERAS FOR THREE-DIMENSIONAL STUDY OF DYNAMIC MULTI-DOMAINS NATURAL SCENES

2020 ◽  
Vol V-1-2020 ◽  
pp. 277-284
Author(s):  
L. Avanthey ◽  
L. Beaudoin ◽  
C. Villard ◽  
S. Mellouk ◽  
R. Treglia
Keyword(s):  
Remote Sensing ◽  
3D Reconstruction ◽  
Low Cost ◽  
Three Dimensional ◽  
Main Issue ◽  
Natural Scenes ◽  
Dynamic Scenes ◽  
Final Model ◽  
Close Range

Abstract. In this article, we study the interest of PiCam and its possibilities offered for the realization of a light payload (small and inexpensive) in order to perform the 3D reconstruction of dynamic scenes (underwater or aerial) in close-range remote sensing. We see that on these observation scales, movements of the scenes due to flora and fauna cannot be ignored if we want these objects to be part of the final model. We review the sensors used in the literature for 3D reconstruction and then present the arguments in favor of PiCam with regard to the constraints posed by the use of light and agile vectors. The main issue is the synchronization of these low cost sensors, which is not native: we explain the different steps to obtain a satisfactory synchronization rate with regard to the dynamism of the studied scenes and present the results obtained.

scholarly journals Hardly Accessible Morphological Structures – Geological Mapping and Accuracy Analysis of SfM and TLS Surveying Technologies

2020 ◽  
pp. 479-493
Keyword(s):  
Laser Scanning ◽  
Point Clouds ◽  
Geological Mapping ◽  
High Temporal Resolution ◽  
Remotely Piloted Aircraft ◽  
Close Range ◽  
Mutual Comparison ◽  
Aircraft System ◽  
Map Data

The aim of geological field mapping is to collect and interpret data on the relief of the Earth's surface. From thus created geological maps, we can obtain information about mineral units and their structure – rock and mineral types, their thickness, lithological deposits, faults, folds, fractures, and thus interpret information as they originated over time. However, the accessibility of such structures is affected by various morphological elements – terrain notches, watercourses, but also by vegetation. Simultaneous geodetic and geological mapping could be a solution for surveying hardly accessible morphological structures. Non-contact surveying technologies – terrestrial laser scanning (TLS) and close-range photogrammetry (terrestrial and remotely piloted aircraft system (RPAS) photogrammetry) provide reliable, high-quality and accurate data on the topographic surface with a high temporal resolution, as the spatial accuracy of the measured point can be mXYZ ≤ 10 mm at an imaging distance of about 20 – 30 m. From the measured data, it is possible to generate point clouds, digital terrain models, and orthophoto maps based on automated data processing. However, the disadvantage of photogrammetric imaging is a proportional decrease in accuracy with increasing imaging distance. The accuracy of TLS is not significantly affected by increasing distance. The paper presents a case study of the use and comparison of non-contact surveying technologies and their application for in-situ mapping of hardly accessible geological structures in the area of Spišská Magura (Slovak-Polish border). The results are given for two localities on two outcrops - Jurgów (PL) and Bachledova valley (SK), while analyzing the usability of TLS and RPAS photogrammetry, with and without the use of artificial ground control points (GCP). The paper presents a mutual comparison of all obtained graphical outputs in terms of 1D and 2D quality depending on the type of GCPs used, depending on the terrain and accessibility. The results show that by using photogrammetry when creating map data, in comparison with TLS, we are able to get sufficient accuracy of outputs for in-situ geological mapping.

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