Critical Examination of 3D Building Modelling through UAV Frame and Video Imaging

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出版年:The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences vol. XLVIII-1-2024 (2024), p. 573
第一著者: Hassan Rezvan
その他の著者: Rezagholi, Elham, Varshosaz, Masood
出版事項:
Copernicus GmbH
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オンライン・アクセス:Citation/Abstract
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100 1 |a Hassan Rezvan  |u Geomatics Engineering Faculty, K. N. Toosi University of Technology, Tehran, Iran; Geomatics Engineering Faculty, K. N. Toosi University of Technology, Tehran, Iran 
245 1 |a Critical Examination of 3D Building Modelling through UAV Frame and Video Imaging 
260 |b Copernicus GmbH  |c 2024 
513 |a Journal Article 
520 3 |a Data capture in UAV photogrammetry is carried out using two main methodologies: frame frame-based and video video-based. Frame Frame-based data gathering is the preferred method among UAV projects because to its inherent reliability in calibration. Nonetheless, circumstances involving moving objects or occlusions inside the measured region may produce unsatisfactory results utilizing this method. I In response to these challenges, video video-based data collecting appears as a potential option, capable of creating a series of successive images that together alleviate the constraints outlined above. In this study we aim to compare the usefulness of frame and video images in building 3D models, using both oblique and vertical image orientations. Rigorous evaluations produced many outputs, including dense point clouds, digital surface models (DSM), meshes, and orthophotographs. The evaluation criteria included da ta acquisition velocity, processing efficiency, calibration precision, distortion analysis, residual plots, scale correctness, and reprojection error. The empirical results demonstrated the advantages of video video-frame captures in improving the quality of the resulting 3D models. Notably, the use of video frames resulted in a significant reduction in reprojection error by 16%, calibration residuals by 36%, distortions by up to 51%, and processing time by 27%. Thus, it seems that integrating video frames improves data gathering accuracy and speeds up processing, replacing standard frame images with video counterparts for increased efficacy. 
653 |a Digital imaging 
653 |a Frames (data processing) 
653 |a Calibration 
653 |a Error correction 
653 |a Photogrammetry 
653 |a Three dimensional models 
653 |a Data capture 
653 |a Video data 
653 |a Error reduction 
653 |a Empirical analysis 
653 |a Vertical orientation 
653 |a Evaluation 
653 |a Environmental 
700 1 |a Rezagholi, Elham  |u Geomatics Engineering Faculty, K. N. Toosi University of Technology, Tehran, Iran; Geomatics Engineering Faculty, K. N. Toosi University of Technology, Tehran, Iran 
700 1 |a Varshosaz, Masood  |u Institute of Artificial Intelligence, USX, Zhejiang, China; Institute of Artificial Intelligence, USX, Zhejiang, China; Geomatics Engineering Faculty, K. N. Toosi University of Technology, Tehran, Iran 
773 0 |t The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences  |g vol. XLVIII-1-2024 (2024), p. 573 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3053250613/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3053250613/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch