Optimization of radial distortion self-calibration for structure from motion from uncalibrated UAV images

Structure from motion (SfM) and self-calibration from images of unknown radial distortions could fail under some critical configurations and produce distorted reconstruction results. In this paper, we propose an effective approach to optimize the estimation of radial distortion coefficient by taking...

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Bibliographic Details
Published in2016 23rd International Conference on Pattern Recognition (ICPR) pp. 3721 - 3726
Main Authors Yonglu Li, Yinghao Cai, Dayong Wen, Yiping Yang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2016
Subjects
Cameras
Distortion
Estimation
Global Positioning System
Image reconstruction
Optimization
Unmanned aerial vehicles
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Summary:Structure from motion (SfM) and self-calibration from images of unknown radial distortions could fail under some critical configurations and produce distorted reconstruction results. In this paper, we propose an effective approach to optimize the estimation of radial distortion coefficient by taking full advantage of GPS information, which allows for more accurate SfM results. A feedback function is designed as the metric to indicate the magnitude of the distortion error. Heuristic search strategies are applied to search for the optimal distortion coefficient. Extensive experimental results show that our approach can effectively reduce the distorted deformation error and improve the estimation accuracy of the distortion coefficient.
DOI:10.1109/ICPR.2016.7900213