Camera Self-Calibration with GNSS Constrained Bundle Adjustment for Weakly Structured Long Corridor UAV Images

Camera self-calibration determines the precision and robustness of AT (aerial triangulation) for UAV (unmanned aerial vehicle) images. The UAV images collected from long transmission line corridors are critical configurations, which may lead to the “bowl effect” with camera self-calibration. To solv...

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Autores principales:	Wei Huang, San Jiang, Wanshou Jiang
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	digital photogrammetry camera self-calibration Brown model polynomial model aerial triangulation Science Q
Acceso en línea:	https://doaj.org/article/1b9e50bb25b74ad3b012be36c8b4f5a2
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id	oai:doaj.org-article:1b9e50bb25b74ad3b012be36c8b4f5a2
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spelling	oai:doaj.org-article:1b9e50bb25b74ad3b012be36c8b4f5a22021-11-11T18:50:32ZCamera Self-Calibration with GNSS Constrained Bundle Adjustment for Weakly Structured Long Corridor UAV Images10.3390/rs132142222072-4292https://doaj.org/article/1b9e50bb25b74ad3b012be36c8b4f5a22021-10-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/21/4222https://doaj.org/toc/2072-4292Camera self-calibration determines the precision and robustness of AT (aerial triangulation) for UAV (unmanned aerial vehicle) images. The UAV images collected from long transmission line corridors are critical configurations, which may lead to the “bowl effect” with camera self-calibration. To solve such problems, traditional methods rely on more than three GCPs (ground control points), while this study designs a new self-calibration method with only one GCP. First, existing camera distortion models are grouped into two categories, i.e., physical and mathematical models, and their mathematical formulas are exploited in detail. Second, within an incremental SfM (Structure from Motion) framework, a camera self-calibration method is designed, which combines the strategies for initializing camera distortion parameters and fusing high-precision GNSS (Global Navigation Satellite System) observations. The former is achieved by using an iterative optimization algorithm that progressively optimizes camera parameters; the latter is implemented through inequality constrained BA (bundle adjustment). Finally, by using four UAV datasets collected from two sites with two data acquisition modes, the proposed algorithm is comprehensively analyzed and verified, and the experimental results demonstrate that the proposed method can dramatically alleviate the “bowl effect” of self-calibration for weakly structured long corridor UAV images, and the horizontal and vertical accuracy can reach 0.04 m and 0.05 m, respectively, when using one GCP. In addition, compared with open-source and commercial software, the proposed method achieves competitive or better performance.Wei HuangSan JiangWanshou JiangMDPI AGarticledigital photogrammetrycamera self-calibrationBrown modelpolynomial modelaerial triangulationScienceQENRemote Sensing, Vol 13, Iss 4222, p 4222 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	digital photogrammetry camera self-calibration Brown model polynomial model aerial triangulation Science Q
spellingShingle	digital photogrammetry camera self-calibration Brown model polynomial model aerial triangulation Science Q Wei Huang San Jiang Wanshou Jiang Camera Self-Calibration with GNSS Constrained Bundle Adjustment for Weakly Structured Long Corridor UAV Images
description	Camera self-calibration determines the precision and robustness of AT (aerial triangulation) for UAV (unmanned aerial vehicle) images. The UAV images collected from long transmission line corridors are critical configurations, which may lead to the “bowl effect” with camera self-calibration. To solve such problems, traditional methods rely on more than three GCPs (ground control points), while this study designs a new self-calibration method with only one GCP. First, existing camera distortion models are grouped into two categories, i.e., physical and mathematical models, and their mathematical formulas are exploited in detail. Second, within an incremental SfM (Structure from Motion) framework, a camera self-calibration method is designed, which combines the strategies for initializing camera distortion parameters and fusing high-precision GNSS (Global Navigation Satellite System) observations. The former is achieved by using an iterative optimization algorithm that progressively optimizes camera parameters; the latter is implemented through inequality constrained BA (bundle adjustment). Finally, by using four UAV datasets collected from two sites with two data acquisition modes, the proposed algorithm is comprehensively analyzed and verified, and the experimental results demonstrate that the proposed method can dramatically alleviate the “bowl effect” of self-calibration for weakly structured long corridor UAV images, and the horizontal and vertical accuracy can reach 0.04 m and 0.05 m, respectively, when using one GCP. In addition, compared with open-source and commercial software, the proposed method achieves competitive or better performance.
format	article
author	Wei Huang San Jiang Wanshou Jiang
author_facet	Wei Huang San Jiang Wanshou Jiang
author_sort	Wei Huang
title	Camera Self-Calibration with GNSS Constrained Bundle Adjustment for Weakly Structured Long Corridor UAV Images
title_short	Camera Self-Calibration with GNSS Constrained Bundle Adjustment for Weakly Structured Long Corridor UAV Images
title_full	Camera Self-Calibration with GNSS Constrained Bundle Adjustment for Weakly Structured Long Corridor UAV Images
title_fullStr	Camera Self-Calibration with GNSS Constrained Bundle Adjustment for Weakly Structured Long Corridor UAV Images
title_full_unstemmed	Camera Self-Calibration with GNSS Constrained Bundle Adjustment for Weakly Structured Long Corridor UAV Images
title_sort	camera self-calibration with gnss constrained bundle adjustment for weakly structured long corridor uav images
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/1b9e50bb25b74ad3b012be36c8b4f5a2
work_keys_str_mv	AT weihuang cameraselfcalibrationwithgnssconstrainedbundleadjustmentforweaklystructuredlongcorridoruavimages AT sanjiang cameraselfcalibrationwithgnssconstrainedbundleadjustmentforweaklystructuredlongcorridoruavimages AT wanshoujiang cameraselfcalibrationwithgnssconstrainedbundleadjustmentforweaklystructuredlongcorridoruavimages
_version_	1718431689936470016

Camera Self-Calibration with GNSS Constrained Bundle Adjustment for Weakly Structured Long Corridor UAV Images

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