scholarly journals Replacement of Professional Photogrammetric Workstations with Low Cost or Free of Charge Photogrammetric Software and Services for Image Triangulation and Image Matching

2013 ◽  
Vol 12 ◽  
pp. 42-48
Author(s):  
Umesh Kumar
Keyword(s):  
Digital Technology ◽  
Image Matching ◽  
Accuracy Assessment ◽  
Low Cost ◽  
Image Data ◽  
Free Software ◽  
Commercial Software ◽  
Aerial Triangulation ◽  
Modern Context ◽  
Image Orientation

In the modern context of digital technology in the field of surveying and mapping, the technique of digital photogrammetry plays crucial role in all steps of mapping. There are some very expensive as well as low cost and free softwares are available in the market for professional photogrammetric work stations. The image triangulation and image matching is one of the very important steps of photogrammetry for which LPS as a commercial software is available in market. There are some low cost and free software as 123D Catch and Patch Boased Multi View Stereo Softwear (PMVS) also available. So, this paper mainly deals with the accuracy as well as the performance of those software for aerial triangulation and image matching for airborne image data to substitute commercial software for photogrammetric workstations. The accuracy assessment of image orientation, points cloud as well as DSM generated from those points cloud are also performed and compared with all products of LPS as commercial software. Nepalese Journal on Geoinformatics -12, 2070 (2013AD): 42-48

scholarly journals Assessment of DSM Based on Radiometric Transformation of UAV Data

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1649
Author(s):  
Muhammad Hamid Chaudhry ◽  
Anuar Ahmad ◽  
Qudsia Gulzar ◽  
Muhammad Shahid Farid ◽  
Himan Shahabi ◽  
...  
Keyword(s):  
Point Cloud ◽  
Accuracy Assessment ◽  
Low Cost ◽  
Image Data ◽  
Flying Height ◽  
Surface Model ◽  
Lidar Data ◽  
Local Accuracy ◽  
Uav Images ◽  
Uav Image

Unmanned Aerial Vehicle (UAV) is one of the latest technologies for high spatial resolution 3D modeling of the Earth. The objectives of this study are to assess low-cost UAV data using image radiometric transformation techniques and investigate its effects on global and local accuracy of the Digital Surface Model (DSM). This research uses UAV Light Detection and Ranging (LIDAR) data from 80 meters and UAV Drone data from 300 and 500 meters flying height. RAW UAV images acquired from 500 meters flying height are radiometrically transformed in Matrix Laboratory (MATLAB). UAV images from 300 meters flying height are processed for the generation of 3D point cloud and DSM in Pix4D Mapper. UAV LIDAR data are used for the acquisition of Ground Control Points (GCP) and accuracy assessment of UAV Image data products. Accuracy of enhanced DSM with DSM generated from 300 meters flight height were analyzed for point cloud number, density and distribution. Root Mean Square Error (RMSE) value of Z is enhanced from ±2.15 meters to 0.11 meters. For local accuracy assessment of DSM, four different types of land covers are statistically compared with UAV LIDAR resulting in compatibility of enhancement technique with UAV LIDAR accuracy.

scholarly journals SfM for Orthophoto to Generation: A Winning Approach for Cultural Heritage Knowledge

2015 ◽  
Vol XL-5/W7 ◽  
pp. 91-98 ◽  
Author(s):  
F. Chiabrando ◽  
E. Donadio ◽  
F. Rinaudo
Keyword(s):  
Cultural Heritage ◽  
Structure From Motion ◽  
Image Matching ◽  
Accuracy Assessment ◽  
Low Cost ◽  
Survey Techniques ◽  
Large Sets ◽  
The Rich ◽  
Rich Content ◽  
Digital Survey

3D detailed models derived from digital survey techniques have increasingly developed and focused in many field of application. The high detailed content and accuracy of such models make them so attractive and usable for large sets of purposes in Cultural Heritage. The present paper focuses on one of the main techniques used nowadays for Cultural Heritage survey and documentation: the image matching approach or Structure from Motion (SfM) technique. According to the low cost nature and the rich content of derivable information, these techniques are extremely strategic in poor available resources sectors such as Cultural Heritage documentation. <br><br> After an overview of the employed algorithms and used approaches of SfM computer vision based techniques, the paper is focused in a critical analysis of the strategy used by two common employed software: the commercial suite Agisoft Photoscan and the open source tool MicMac realized by IGN France. The experimental section is focused on the description of applied tests (from RPAS data to terrestrial acquisitions), purposed to compare different solutions in various featured study cases. Finally, the accuracy assessment of the achieved products is compared and analyzed according to the strategy employed by the studied software.

scholarly journals Digital Model in Close-Range Photogrammetry Using a Smartphone Camera

2021 ◽  
Vol 318 ◽  
pp. 04005
Author(s):  
Tariq N. Ataiwe ◽  
Israa Hatem ◽  
Hisham M. J. Al Sharaa
Keyword(s):  
Camera Calibration ◽  
3D Model ◽  
Accuracy Assessment ◽  
Low Cost ◽  
Calibration Model ◽  
Digital Cameras ◽  
Close Range Photogrammetry ◽  
Close Range ◽  
Chessboard Pattern ◽  
Image Orientation

Smartphones recently expanded the potential for low-cost close-range photogrammetry for 3D modeling. They enable the simultaneous collection of large amounts of data for a variety of requirements. It is possible to calculate image orientation elements and triangular coordinates in phases as in Relative and Absolute image orientation. This study demonstrates the photogrammetric 3D reconstruction approach that performs on tablets and smartphones as well. Images are taken with smartphone cameras of iPhone 6 and then calibrated automatically using normal calibration model for photogrammetry and computer vision on a PC, depend on Agisoft Lens add-on that imbedded in Agisoft program, and MATLAB camera calibration Toolbox, and by using an oriented bunch of images of chessboard pattern for large point cloud-based picture using matching. The camera calibration results indicate that the calibration processing routines pass without any error, and the accuracy of estimated IOPs was convenient compared with non-metric digital cameras and are more accurate in Agisoft Lens in terms of standard error. For the 3D model, 435 cameras were used, 428 cameras located from 435 are aligned in two photogrammetric software, Agisoft PhotoScan, and LPS. The number of tie points that are used in LPS is 10 tie points, and 4 control points which used to estimate the EOPs, and the number of tie points that are regenerated in Agisoft PhotoScan were 135.605 points, the number of Dense cloud 3,716,912 points are generated, for 3D model a number of 316,253 faces are generated, after processing the tiled model generated (6 levels, 1.25 cm/pix), the generated DEM having (2136×1774/pix), the dimensions of the generated high-resolution orthomosaic are (5520×4494, 4.47 cm/pix). For accuracy assessment, the Xerr. = 0.292 m, Yerr. = 0.38577 m, Zerr.= 0.2889 m, and the total RMS = 0.563 m in the estimated locations of the exterior orientation parameters.

Rapid mapping accuracy assessment using low-cost UAV and open-source Structure from Motion

2020 ◽  
Vol 52 ◽  
pp. 55-61
Author(s):  
Ettore Potente ◽  
Cosimo Cagnazzo ◽  
Alessandro Deodati ◽  
Giuseppe Mastronuzzi
Keyword(s):  
Open Source ◽  
Structure From Motion ◽  
Accuracy Assessment ◽  
Low Cost ◽  
Mapping Accuracy ◽  
Rapid Mapping ◽  
Source Structure

scholarly journals New Omnidirectional Sensor Based on Open-Source Software and Hardware for Tracking and Backtracking of Dual-Axis Solar Trackers in Photovoltaic Plants

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 726
Author(s):  
Francisco J. Gómez-Uceda ◽  
José Ramirez-Faz ◽  
Marta Varo-Martinez ◽  
Luis Manuel Fernández-Ahumada
Keyword(s):  
Open Source Software ◽  
Energy Production ◽  
Scientific Community ◽  
Radiative Capture ◽  
Low Cost ◽  
Free Software ◽  
Solar Tracking ◽  
Software And Hardware ◽  
Celestial Sphere ◽  
Photovoltaic Plants

In this work, an omnidirectional sensor that enables identification of the direction of the celestial sphere with maximum solar irradiance is presented. The sensor, based on instantaneous measurements, functions as a position server for dual-axis solar trackers in photovoltaic plants. The proposed device has been developed with free software and hardware, which makes it a pioneering solution because it is open and accessible as well as capable of being improved by the scientific community, thereby contributing to the rapid advancement of technology. In addition, the device includes an algorithm developed ex professo that makes it possible to predetermine the regions of the celestial sphere for which, according to the geometric characteristics of the PV plant, there would be shading between the panels. In this way, solar trackers do not have to locate the Sun’s position at all times according to astronomical models, while taking into account factors such as shadows or cloudiness that also affect levels of incident irradiance on solar collectors. Therefore, with this device, it is possible to provide photovoltaic plants with dual-axis solar tracking with a low-cost device that helps to optimise the trajectory of the trackers and, consequently, their radiative capture and energy production.

scholarly journals DSM Generation from Single and Cross-Sensor Multi-View Satellite Images Using the New Agisoft Metashape: The Case Studies of Trento and Matera (Italy)

2021 ◽  
Vol 13 (4) ◽  
pp. 593
Author(s):  
Lorenzo Lastilla ◽  
Valeria Belloni ◽  
Roberta Ravanelli ◽  
Mattia Crespi
Keyword(s):  
Case Studies ◽  
Accuracy Assessment ◽  
Stereo Pair ◽  
Commercial Software ◽  
Processing Module ◽  
Land Covers ◽  
Image Metadata ◽  
The Impact ◽  
The City ◽  
Reliable Software

DSM generation from satellite imagery is a long-lasting issue and it has been addressed in several ways over the years; however, expert and users are continuously searching for simpler but accurate and reliable software solutions. One of the latest ones is provided by the commercial software Agisoft Metashape (since version 1.6), previously known as Photoscan, which joins other already available open-source and commercial software tools. The present work aims to quantify the potential of the new Agisoft Metashape satellite processing module, considering that to the best knowledge of the authors, only two papers have been published, but none considering cross-sensor imagery. Here we investigated two different case studies to evaluate the accuracy of the generated DSMs. The first dataset consists of a triplet of Pléiades images acquired over the area of Trento and the Adige valley (Northern Italy), which is characterized by a great variety in terms of geomorphology, land uses and land covers. The second consists of a triplet composed of a WorldView-3 stereo pair and a GeoEye-1 image, acquired over the city of Matera (Southern Italy), one of the oldest settlements in the world, with the worldwide famous area of Sassi and a very rugged morphology in the surroundings. First, we carried out the accuracy assessment using the RPCs supplied by the satellite companies as part of the image metadata. Then, we refined the RPCs with an original independent terrain technique able to supply a new set of RPCs, using a set of GCPs adequately distributed across the regions of interest. The DSMs were generated both in a stereo and multi-view (triplet) configuration. We assessed the accuracy and completeness of these DSMs through a comparison with proper references, i.e., DSMs obtained through LiDAR technology. The impact of the RPC refinement on the DSM accuracy is high, ranging from 20 to 40% in terms of LE90. After the RPC refinement, we achieved an average overall LE90 <5.0 m (Trento) and <4.0 m (Matera) for the stereo configuration, and <5.5 m (Trento) and <4.5 m (Matera) for the multi-view (triplet) configuration, with an increase of completeness in the range 5–15% with respect to stereo pairs. Finally, we analyzed the impact of land cover on the accuracy of the generated DSMs; results for three classes (urban, agricultural, forest and semi-natural areas) are also supplied.

scholarly journals Identifying Habitat Elements from Bird Images Using Deep Convolutional Neural Networks

Animals ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 1263
Author(s):  
Zhaojun Wang ◽  
Jiangning Wang ◽  
Congtian Lin ◽  
Yan Han ◽  
Zhaosheng Wang ◽  
...  
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Digital Technology ◽  
Rapid Development ◽  
Image Data ◽  
Image Database ◽  
Test Accuracy ◽  
Practical Application ◽  
Accuracy Rate ◽  
Deep Convolutional Neural Networks

With the rapid development of digital technology, bird images have become an important part of ornithology research data. However, due to the rapid growth of bird image data, it has become a major challenge to effectively process such a large amount of data. In recent years, deep convolutional neural networks (DCNNs) have shown great potential and effectiveness in a variety of tasks regarding the automatic processing of bird images. However, no research has been conducted on the recognition of habitat elements in bird images, which is of great help when extracting habitat information from bird images. Here, we demonstrate the recognition of habitat elements using four DCNN models trained end-to-end directly based on images. To carry out this research, an image database called Habitat Elements of Bird Images (HEOBs-10) and composed of 10 categories of habitat elements was built, making future benchmarks and evaluations possible. Experiments showed that good results can be obtained by all the tested models. ResNet-152-based models yielded the best test accuracy rate (95.52%); the AlexNet-based model yielded the lowest test accuracy rate (89.48%). We conclude that DCNNs could be efficient and useful for automatically identifying habitat elements from bird images, and we believe that the practical application of this technology will be helpful for studying the relationships between birds and habitat elements.

Accuracy assessment of aerial photographs acquired using lighter-than-air blimps: low-cost tools for mapping river corridors

2009 ◽  
Vol 25 (8) ◽  
pp. 985-1000 ◽  
Author(s):  
Damià Vericat ◽  
James Brasington ◽  
Joe Wheaton ◽  
Michaela Cowie
Keyword(s):  
Accuracy Assessment ◽  
Low Cost ◽  
Aerial Photographs ◽  
River Corridors

FEASIBILITY ANALYSIS OF AN AUTOMATED DETECTION OF PHYSICAL DEFECT VIA COMPUTER VISION

2015 ◽  
Vol 76 (12) ◽  
Author(s):  
Por Jing Zhao ◽  
Shafriza Nisha Basah ◽  
Shazmin Aniza Abdul Shukor
Keyword(s):  
Computer Vision ◽  
Low Cost ◽  
Image Data ◽  
Automated Detection ◽  
Building Construction ◽  
High Demand ◽  
Major City ◽  
Cost System ◽  
Kinect Camera ◽  
Wall Condition

High demand of building construction has been taking places in the major city of Malaysia. However, despite this magnificent development, the lack of proper maintenance has caused a large portion of these properties deteriorated over time. The implementation of the project - Automated Detection of Physical Defect via Computer Vision - is a low cost system that helps to inspect the wall condition using Kinect camera. The system is able to classify the types of physical defects -crack and hole - and state its level of severity.The system uses artificial neural network as the image classifier due to its reliability and consistency. The validity of the system is shown using experiments on synthetic and real image data. This automated physical defect detection could detect building defect early, quickly, and easily, which results in cost saving and extending building life span. 

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.

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