scholarly journals Digitalización automática del patrimonio arqueológico a partir de fotogrametría

2015 ◽  
Vol 4 (8) ◽  
pp. 46 ◽  
Author(s):  
Pedro Ortiz Coder
Keyword(s):  
Computer Vision ◽  
Unmanned Aerial Vehicles ◽  
Laser Scanner ◽  
Archaeological Site ◽  
New Techniques ◽  
Aerial Vehicles ◽  
Photogrammetric Method

<p>New techniques in graphical heritage documentation have been improving recently. Modern photogrammetry and laser scanner constitute techniques with a good quality for those purposes. In this document, we will explain an easy photogrammetric method which permits to obtain accurate results. It is important to separate it from other methods based on computer vision with less accuracy. 4e photogrammetry solution is applied in this test through pictures taken from UAV (Unmanned Aerial Vehicles) and used on an archaeological site in Extremadura.</p>

scholarly journals QUALITY ASSESSMENT OF 3D RECONSTRUCTION USING FISHEYE AND PERSPECTIVE SENSORS

2015 ◽  
Vol II-3/W4 ◽  
pp. 215-222 ◽  
Author(s):  
C. Strecha ◽  
R. Zoller ◽  
S. Rutishauser ◽  
B. Brot ◽  
K. Schneider-Zapp ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
Quality Assessment ◽  
Unmanned Aerial Vehicles ◽  
Point Cloud ◽  
Laser Scanner ◽  
3D Modelling ◽  
Sensor Selection ◽  
Aerial Vehicles ◽  
Photogrammetric Method ◽  
Fisheye Lenses

Recent mathematical advances, growing alongside the use of unmanned aerial vehicles, have not only overcome the restriction of roll and pitch angles during flight but also enabled us to apply non-metric cameras in photogrammetric method, providing more flexibility for sensor selection. Fisheye cameras, for example, advantageously provide images with wide coverage; however, these images are extremely distorted and their non-uniform resolutions make them more difficult to use for mapping or terrestrial 3D modelling. In this paper, we compare the usability of different camera-lens combinations, using the complete workflow implemented in Pix4Dmapper to achieve the final terrestrial reconstruction result of a well-known historical site in Switzerland: the Chillon Castle. We assess the accuracy of the outcome acquired by consumer cameras with perspective and fisheye lenses, comparing the results to a laser scanner point cloud.

scholarly journals Unmanned Aerial Vehicles (UAVs) for Physical Progress Monitoring of Construction

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4227
Author(s):  
Nicolás Jacob-Loyola ◽  
Felipe Muñoz-La Rivera ◽  
Rodrigo F. Herrera ◽  
Edison Atencio
Keyword(s):  
Computer Vision ◽  
Unmanned Aerial Vehicles ◽  
Progress Monitoring ◽  
Residential Building ◽  
Point Clouds ◽  
Construction Site ◽  
Manual Operation ◽  
Work Site ◽  
Aerial Vehicles ◽  
Made In

The physical progress of a construction project is monitored by an inspector responsible for verifying and backing up progress information, usually through site photography. Progress monitoring has improved, thanks to advances in image acquisition, computer vision, and the development of unmanned aerial vehicles (UAVs). However, no comprehensive and simple methodology exists to guide practitioners and facilitate the use of these methods. This research provides recommendations for the periodic recording of the physical progress of a construction site through the manual operation of UAVs and the use of point clouds obtained under photogrammetric techniques. The programmed progress is then compared with the actual progress made in a 4D BIM environment. This methodology was applied in the construction of a reinforced concrete residential building. The results showed the methodology is effective for UAV operation in the work site and the use of the photogrammetric visual records for the monitoring of the physical progress and the communication of the work performed to the project stakeholders.

scholarly journals ON PRACTICAL ACCURACY ASPECTS OF UNMANNED AERIAL VEHICLES EQUIPPED WITH SURVEY GRADE LASER SCANNERS

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 343-348
Author(s):  
K. Nakano ◽  
Y. Tanaka ◽  
H. Suzuki ◽  
K. Hayakawa ◽  
M. Kurodai
Keyword(s):  
Unmanned Aerial Vehicles ◽  
High Performance ◽  
Laser Scanner ◽  
Image Sensors ◽  
Measuring Devices ◽  
Aerial Vehicles ◽  
Laser Scanners ◽  
Surface Models ◽  
Reconstruction Software ◽  
Practical Accuracy

Abstract. Unmanned aerial vehicles (UAVs) equipped with image sensors, which have been widely used in various fields such as construction, agriculture, and disaster management, can obtain images at the millimeter to decimeter scale. Useful tools that produce realistic surface models using 3D reconstruction software based on computer vision technologies are generally used to produce datasets from acquired images using UAVs. However, it is difficult to obtain the feature points from surfaces with limited texture, such as new asphalt or concrete, or detect the ground in areas such as forests, which are commonly concealed by vegetation. A promising method to address such issues is the use of UAV-equipped laser scanners. Recently, low and high performance products that use direct georeferencing devices integrated with laser scanners have been available. Moreover, there have been numerous reports regarding the various applications of UAVs equipped with laser scanners; however, these reports only discuss UAVs as measuring devices. Therefore, to understand the functioning of UAVs equipped with laser scanners, we investigated the theoretical accuracy of the survey grade laser scanner unit from the viewpoint of photogrammetry. We evaluated the performance of the VUX-1HA laser scanner equipped on a Skymatix X-LS1 UAV at a construction site. We presented the theoretical values obtained using the observation equations and results of the accuracy aspects of the acquired data in terms of height.

scholarly journals Computer Vision in Autonomous Unmanned Aerial Vehicles—A Systematic Mapping Study

2019 ◽  
Vol 9 (15) ◽  
pp. 3196 ◽  
Author(s):  
Lidia María Belmonte ◽  
Rafael Morales ◽  
Antonio Fernández-Caballero
Keyword(s):  
Computer Vision ◽  
Unmanned Aerial Vehicles ◽  
Flight Control ◽  
Systematic Mapping Study ◽  
General View ◽  
Mapping Study ◽  
Vision Systems ◽  
Systematic Mapping ◽  
Aerial Vehicles ◽  
Assistant Robots

Personal assistant robots provide novel technological solutions in order to monitor people’s activities, helping them in their daily lives. In this sense, unmanned aerial vehicles (UAVs) can also bring forward a present and future model of assistant robots. To develop aerial assistants, it is necessary to address the issue of autonomous navigation based on visual cues. Indeed, navigating autonomously is still a challenge in which computer vision technologies tend to play an outstanding role. Thus, the design of vision systems and algorithms for autonomous UAV navigation and flight control has become a prominent research field in the last few years. In this paper, a systematic mapping study is carried out in order to obtain a general view of this subject. The study provides an extensive analysis of papers that address computer vision as regards the following autonomous UAV vision-based tasks: (1) navigation, (2) control, (3) tracking or guidance, and (4) sense-and-avoid. The works considered in the mapping study—a total of 144 papers from an initial set of 2081—have been classified under the four categories above. Moreover, type of UAV, features of the vision systems employed and validation procedures are also analyzed. The results obtained make it possible to draw conclusions about the research focuses, which UAV platforms are mostly used in each category, which vision systems are most frequently employed, and which types of tests are usually performed to validate the proposed solutions. The results of this systematic mapping study demonstrate the scientific community’s growing interest in the development of vision-based solutions for autonomous UAVs. Moreover, they will make it possible to study the feasibility and characteristics of future UAVs taking the role of personal assistants.

scholarly journals Survey of computer vision algorithms and applications for unmanned aerial vehicles

2018 ◽  
Vol 92 ◽  
pp. 447-463 ◽  
Author(s):  
Abdulla Al-Kaff ◽  
David Martín ◽  
Fernando García ◽  
Arturo de la Escalera ◽  
José María Armingol
Keyword(s):  
Computer Vision ◽  
Unmanned Aerial Vehicles ◽  
Aerial Vehicles

scholarly journals APPLICATION OF MODERN TECHNICAL AND SOFTWARE MEANS IN THE CONDITIONS OF FORMATION OF THE DIGITAL ECONOMY OF THE RUSSIAN FEDERATION

2020 ◽  
Vol 7 (2) ◽  
pp. 66-70
Author(s):  
Olga A. Opritova ◽  
Alexandr A. Antonov ◽  
Polina E. Ivanenko
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Russian Federation ◽  
Digital Economy ◽  
Aerial Vehicles ◽  
Photogrammetric Method ◽  
The Russian Federation ◽  
Software And Hardware

The article presents a method of using modern software and hardware in various fields and fields of activity. The definition and prospects of the development of the photogrammetric method in cadastral activities, as well as the possibility of using unmanned aerial vehicles and cloud platforms are given.

scholarly journals Autonomous trajectory following for an UAV based on computer vision

2020 ◽  
Vol 14 (1) ◽  
pp. 51-56
Author(s):  
Jorge Daniel Gallo Sanabria ◽  
Paula Andrea Mozuca Tamayo ◽  
Rafael Iván Rincón Fonseca
Keyword(s):  
Computer Vision ◽  
Unmanned Aerial Vehicles ◽  
Simple Algorithm ◽  
Aerial Vehicles ◽  
Package Delivery ◽  
Trajectory Following ◽  
The Way

The trajectory following performed by unmanned aerial vehicles has several advantages that can be taken to several applications, going from package delivery to agriculture. However, this involves several challenges depending on the way the following is performed, particularly in the case of trajectory following by using computer vision. In here we will show the design, the simulation and the implementation of a simple algorithm for trajectory following by using computer vision, this algorithm will be executed on a drone that will arrive into a wished point.

Forest fire flame and smoke detection from UAV-captured images using fire-specific color features and multi-color space local binary pattern

2020 ◽  
Vol 8 (4) ◽  
pp. 285-309
Author(s):  
F.M. Anim Hossain ◽  
Youmin M. Zhang ◽  
Masuda Akter Tonima
Keyword(s):  
Computer Vision ◽  
Unmanned Aerial Vehicles ◽  
Forest Fire ◽  
Local Binary Pattern ◽  
Color Space ◽  
Fire Detection ◽  
Large Field ◽  
Aerial Vehicles ◽  
Aerial Platforms ◽  
Forest Fire Detection

In recent years, the frequency and severity of forest fire occurrence have increased, compelling the research communities to actively search for early forest fire detection and suppression methods. Remote sensing using computer vision techniques can provide early detection from a large field of view along with providing additional information such as location and severity of the fire. Over the last few years, the feasibility of forest fire detection by combining computer vision and aerial platforms such as manned and unmanned aerial vehicles, especially low cost and small-size unmanned aerial vehicles, have been experimented with and have shown promise by providing detection, geolocation, and fire characteristic information. This paper adds to the existing research by proposing a novel method of detecting forest fire using color and multi-color space local binary pattern of both flame and smoke signatures and a single artificial neural network. The training and evaluation images in this paper have been mostly obtained from aerial platforms with challenging circumstances such as minuscule flame pixels, varying illumination and range, complex backgrounds, occluded flame and smoke regions, and smoke blending into the background. The proposed method has achieved F1 scores of 0.84 for flame and 0.90 for smoke while maintaining a processing speed of 19 frames per second. It has outperformed support vector machine, random forest, Bayesian classifiers and YOLOv3, and has demonstrated the capability of detecting challenging flame and smoke regions of a wide range of sizes, colors, textures, and opacity.

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