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 CAN WE USE LOW-COST 360 DEGREE CAMERAS TO CREATE ACCURATE 3D MODELS?

2018 ◽  
Vol XLII-2 ◽  
pp. 69-75 ◽  
Author(s):  
L. Barazzetti ◽  
M. Previtali ◽  
F. Roncoroni
Keyword(s):  
Laser Scanning ◽  
Low Cost ◽  
Point Clouds ◽  
3D Models ◽  
Bundle Adjustment ◽  
Field Of View ◽  
Large Field ◽  
Single Shot ◽  
New Paradigm ◽  
Image Orientation

360 degree cameras capture the whole scene around a photographer in a single shot. Cheap 360 cameras are a new paradigm in photogrammetry. The camera can be pointed to any direction, and the large field of view reduces the number of photographs. This paper aims to show that accurate metric reconstructions can be achieved with affordable sensors (less than 300 euro). The camera used in this work is the Xiaomi Mijia Mi Sphere 360, which has a cost of about 300 USD (January 2018). Experiments demonstrate that millimeter-level accuracy can be obtained during the image orientation and surface reconstruction steps, in which the solution from 360° images was compared to check points measured with a total station and laser scanning point clouds. The paper will summarize some practical rules for image acquisition as well as the importance of ground control points to remove possible deformations of the network during bundle adjustment, especially for long sequences with unfavorable geometry. The generation of orthophotos from images having a 360° field of view (that captures the entire scene around the camera) is discussed. Finally, the paper illustrates some case studies where the use of a 360° camera could be a better choice than a project based on central perspective cameras. Basically, 360° cameras become very useful in the survey of long and narrow spaces, as well as interior areas like small rooms.

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).

scholarly journals Point Cloud Stacking: A Workflow to Enhance 3D Monitoring Capabilities Using Time-Lapse Cameras

2020 ◽  
Vol 12 (8) ◽  
pp. 1240 ◽  
Author(s):  
Xabier Blanch ◽  
Antonio Abellan ◽  
Marta Guinau
Keyword(s):  
Point Cloud ◽  
Low Cost ◽  
Three Dimensional ◽  
Synthetic Data ◽  
Real Data ◽  
Point Clouds ◽  
Time Lapse ◽  
Position Estimation ◽  
Bundle Adjustment ◽  
Camera System

The emerging use of photogrammetric point clouds in three-dimensional (3D) monitoring processes has revealed some constraints with respect to the use of LiDAR point clouds. Oftentimes, point clouds (PC) obtained by time-lapse photogrammetry have lower density and precision, especially when Ground Control Points (GCPs) are not available or the camera system cannot be properly calibrated. This paper presents a new workflow called Point Cloud Stacking (PCStacking) that overcomes these restrictions by making the most of the iterative solutions in both camera position estimation and internal calibration parameters that are obtained during bundle adjustment. The basic principle of the stacking algorithm is straightforward: it computes the median of the Z coordinates of each point for multiple photogrammetric models to give a resulting PC with a greater precision than any of the individual PC. The different models are reconstructed from images taken simultaneously from, at least, five points of view, reducing the systematic errors associated with the photogrammetric reconstruction workflow. The algorithm was tested using both a synthetic point cloud and a real 3D dataset from a rock cliff. The synthetic data were created using mathematical functions that attempt to emulate the photogrammetric models. Real data were obtained by very low-cost photogrammetric systems specially developed for this experiment. Resulting point clouds were improved when applying the algorithm in synthetic and real experiments, e.g., 25th and 75th error percentiles were reduced from 3.2 cm to 1.4 cm in synthetic tests and from 1.5 cm to 0.5 cm in real conditions.

scholarly journals ACCURACY ASSESSMENT OF A COMPLEX BUILDING 3D MODEL RECONSTRUCTED FROM IMAGES ACQUIRED WITH A LOW-COST UAS

2017 ◽  
Vol XLII-2/W3 ◽  
pp. 551-558 ◽  
Author(s):  
E. Oniga ◽  
C. Chirilă ◽  
F. Stătescu
Keyword(s):  
Computer Aided Design ◽  
3D Model ◽  
Least Squares Method ◽  
Accuracy Assessment ◽  
Low Cost ◽  
Point Clouds ◽  
3D Models ◽  
Bundle Adjustment ◽  
Unmanned Aerial Systems ◽  
Characteristic Points

Nowadays, Unmanned Aerial Systems (UASs) are a wide used technique for acquisition in order to create buildings 3D models, providing the acquisition of a high number of images at very high resolution or video sequences, in a very short time. Since low-cost UASs are preferred, the accuracy of a building 3D model created using this platforms must be evaluated. To achieve results, the dean's office building from the Faculty of “Hydrotechnical Engineering, Geodesy and Environmental Engineering” of Iasi, Romania, has been chosen, which is a complex shape building with the roof formed of two hyperbolic paraboloids. Seven points were placed on the ground around the building, three of them being used as GCPs, while the remaining four as Check points (CPs) for accuracy assessment. Additionally, the coordinates of 10 natural CPs representing the building characteristic points were measured with a Leica TCR 405 total station. The building 3D model was created as a point cloud which was automatically generated based on digital images acquired with the low-cost UASs, using the image matching algorithm and different software like 3DF Zephyr, Visual SfM, PhotoModeler Scanner and Drone2Map for ArcGIS. Except for the PhotoModeler Scanner software, the interior and exterior orientation parameters were determined simultaneously by solving a self-calibrating bundle adjustment. Based on the UAS point clouds, automatically generated by using the above mentioned software and GNSS data respectively, the parameters of the east side hyperbolic paraboloid were calculated using the least squares method and a statistical blunder detection. Then, in order to assess the accuracy of the building 3D model, several comparisons were made for the facades and the roof with reference data, considered with minimum errors: TLS mesh for the facades and GNSS mesh for the roof. Finally, the front facade of the building was created in 3D based on its characteristic points using the PhotoModeler Scanner software, resulting a CAD (Computer Aided Design) model. The results showed the high potential of using low-cost UASs for building 3D model creation and if the building 3D model is created based on its characteristic points the accuracy is significantly improved.

scholarly journals Comparative Analysis of Digital Models of Objects of Cultural Heritage Obtained by the “3D SLS” and “SfM” Methods

2021 ◽  
Vol 11 (12) ◽  
pp. 5321
Author(s):  
Marcin Barszcz ◽  
Jerzy Montusiewicz ◽  
Magdalena Paśnikowska-Łukaszuk ◽  
Anna Sałamacha
Keyword(s):  
Cultural Heritage ◽  
Low Cost ◽  
Three Dimensional ◽  
3D Models ◽  
Silk Road ◽  
Digital Models ◽  
Global Pandemic ◽  
University Of Technology ◽  
Three Dimensional Models ◽  
3D Digitisation

In the era of the global pandemic caused by the COVID-19 virus, 3D digitisation of selected museum artefacts is becoming more and more frequent practice, but the vast majority is performed by specialised teams. The paper presents the results of comparative studies of 3D digital models of the same museum artefacts from the Silk Road area generated by two completely different technologies: Structure from Motion (SfM)—a method belonging to the so-called low-cost technologies—and by Structured-light 3D Scanning (3D SLS). Moreover, procedural differences in data acquisition and their processing to generate three-dimensional models are presented. Models built using a point cloud were created from data collected in the Afrasiyab museum in Samarkand (Uzbekistan) during “The 1st Scientific Expedition of the Lublin University of Technology to Central Asia” in 2017. Photos for creating 3D models in SfM technology were taken during a virtual expedition carried out under the “3D Digital Silk Road” program in 2021. The obtained results show that the quality of the 3D models generated with SfM differs from the models from the technology (3D SLS), but they may be placed in the galleries of the vitrual museum. The obtained models from SfM do not have information about their size, which means that they are not fully suitable for archiving purposes of cultural heritage, unlike the models from SLS.

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 IMPROVING UAV TELEMETRY POSITIONING FOR DIRECT PHOTOGRAMMETRY

2021 ◽  
Vol XLIII-B2-2021 ◽  
pp. 61-68
Author(s):  
L. Rossi ◽  
F. Ioli ◽  
E. Capizzi ◽  
L. Pinto ◽  
M. Reguzzoni
Keyword(s):  
Low Cost ◽  
Three Dimensional ◽  
Control Points ◽  
Three Dimensional Model ◽  
Commercial Software ◽  
Ground Control Points ◽  
Lower Accuracy ◽  
Least Squares Adjustment ◽  
Gnss Receivers

Abstract. A fundamental step of UAV photogrammetric processes is to collect Ground Control Points (GCPs) by means of geodetic-quality GNSS receivers or total stations, thus obtaining an absolutely oriented model with a centimetric accuracy. This procedure is usually time-consuming, expensive and potentially dangerous for operators who sometimes need to reach inaccessible areas. UAVs equipped with low-cost GNSS/IMU sensors can provide information about position and attitude of the images. This telemetry information is not enough for a photogrammetric restitution with a centimetric accuracy, but it can be usefully exploited when a lower accuracy is required. The algorithm proposed in this paper aims at improving the quality of this information, in order to introduce it into a direct-photogrammetric process, without collecting GCPs. In particular, the estimation of an optimal trajectory is obtained by combining the camera positions derived from UAV telemetry and from the relative orientation of the acquired images, by means of a least squares adjustment. Then, the resulting trajectory is used as a direct observation of the camera positions into a commercial software, thus replacing the information of GCPs. The algorithm has been tested on different datasets, comparing the classical photogrammetric solution (with GCPs) with the proposed one. These case-studies showed that using the improved trajectory as input to the commercial software (without GCPs) the reconstruction of the three-dimensional model can be improved with respect to the solution computed by using the UAV raw telemetry only.

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 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 Weighing trees with lasers: advances, challenges and opportunities

2018 ◽  
Vol 8 (2) ◽  
pp. 20170048 ◽  
Author(s):  
M. I. Disney ◽  
M. Boni Vicari ◽  
A. Burt ◽  
K. Calders ◽  
S. L. Lewis ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Large Scale ◽  
Three Dimensional ◽  
Point Clouds ◽  
3D Models ◽  
Tree Form ◽  
Form And Function ◽  
Challenges And Opportunities ◽  
And Function ◽  
Non Destructive

Terrestrial laser scanning (TLS) is providing exciting new ways to quantify tree and forest structure, particularly above-ground biomass (AGB). We show how TLS can address some of the key uncertainties and limitations of current approaches to estimating AGB based on empirical allometric scaling equations (ASEs) that underpin all large-scale estimates of AGB. TLS provides extremely detailed non-destructive measurements of tree form independent of tree size and shape. We show examples of three-dimensional (3D) TLS measurements from various tropical and temperate forests and describe how the resulting TLS point clouds can be used to produce quantitative 3D models of branch and trunk size, shape and distribution. These models can drastically improve estimates of AGB, provide new, improved large-scale ASEs, and deliver insights into a range of fundamental tree properties related to structure. Large quantities of detailed measurements of individual 3D tree structure also have the potential to open new and exciting avenues of research in areas where difficulties of measurement have until now prevented statistical approaches to detecting and understanding underlying patterns of scaling, form and function. We discuss these opportunities and some of the challenges that remain to be overcome to enable wider adoption of TLS methods.

Sign in / Sign up

Export Citation Format

Share Document