scholarly journals Dense 3D Reconstruction for Visual Tunnel Inspection using Unmanned Aerial Vehicle

Author(s):  
Ramanpreet Singh Pahwa ◽  
Kennard Yanting Chan ◽  
Jiamin Bai ◽  
Vincensius Billy Saputra ◽  
Minh N. Do ◽  
...  
2019 ◽  
Vol 11 (20) ◽  
pp. 2440 ◽  
Author(s):  
Randa Almadhoun ◽  
Abdullah Abduldayem ◽  
Tarek Taha ◽  
Lakmal Seneviratne ◽  
Yahya Zweiri

In this paper, a Next Best View (NBV) approach with a profiling stage and a novel utility function for 3D reconstruction using an Unmanned Aerial Vehicle (UAV) is proposed. The proposed approach performs an initial scan in order to build a rough model of the structure that is later used to improve coverage completeness and reduce flight time. Then, a more thorough NBV process is initiated, utilizing the rough model in order to create a dense 3D reconstruction of the structure of interest. The proposed approach exploits the reflectional symmetry feature if it exists in the initial scan of the structure. The proposed NBV approach is implemented with a novel utility function, which consists of four main components: information theory, model density, traveled distance, and predictive measures based on symmetries in the structure. This system outperforms classic information gain approaches with a higher density, entropy reduction and coverage completeness. Simulated and real experiments were conducted and the results show the effectiveness and applicability of the proposed approach.


2020 ◽  
Vol 12 (18) ◽  
pp. 2873 ◽  
Author(s):  
Elisa Mariarosaria Farella ◽  
Alessandro Torresani ◽  
Fabio Remondino

The paper presents an efficient photogrammetric workflow to improve the 3D reconstruction of scenes surveyed by integrating terrestrial and Unmanned Aerial Vehicle (UAV) images. In the last years, the integration of this kind of images has shown clear advantages for the complete and detailed 3D representation of large and complex scenarios. Nevertheless, their photogrammetric integration often raises several issues in the image orientation and dense 3D reconstruction processes. Noisy and erroneous 3D reconstructions are the typical result of inaccurate orientation results. In this work, we propose an automatic filtering procedure which works at the sparse point cloud level and takes advantage of photogrammetric quality features. The filtering step removes low-quality 3D tie points before refining the image orientation in a new adjustment and generating the final dense point cloud. Our method generalizes to many datasets, as it employs statistical analyses of quality feature distributions to identify suitable filtering thresholds. Reported results show the effectiveness and reliability of the method verified using both internal and external quality checks, as well as visual qualitative comparisons. We made the filtering tool publicly available on GitHub.


2009 ◽  
Vol 2009 (0) ◽  
pp. _1A1-D18_1-_1A1-D18_3
Author(s):  
Kiichiro ISHIKAWA ◽  
Taro SUZUKI ◽  
Syuhei ONO ◽  
Takashi FUJISHIMA ◽  
Shinji SUZUKI ◽  
...  

2020 ◽  
Vol 20 (4) ◽  
pp. 332-342
Author(s):  
Hyung Jun Park ◽  
Seong Hee Cho ◽  
Kyung-Hwan Jang ◽  
Jin-Woon Seol ◽  
Byung-Gi Kwon ◽  
...  

2018 ◽  
pp. 7-13
Author(s):  
Anton M. Mishchenko ◽  
Sergei S. Rachkovsky ◽  
Vladimir A. Smolin ◽  
Igor V . Yakimenko

Results of experimental studying radiation spatial structure of atmosphere background nonuniformities and of an unmanned aerial vehicle being the detection object are presented. The question on a possibility of its detection using optoelectronic systems against the background of a cloudy field in the near IR wavelength range is also considered.


Author(s):  
Amir Birjandi ◽  
◽  
Valentin Guerry ◽  
Eric Bibeau ◽  
Hamidreza Bolandhemmat ◽  
...  

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