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

Authors :
Rezvan, Hassan
Rezagholi, Elham
Varshosaz, Masood
Source :
International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences; 2024, Vol. 48 Issue 1, p573-578, 6p
Publication Year :
2024

Abstract

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16821750
Volume :
48
Issue :
1
Database :
Complementary Index
Journal :
International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences
Publication Type :
Academic Journal
Accession number :
177679068
Full Text :
https://doi.org/10.5194/isprs-archives-XLVIII-1-2024-573-2024