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Pose Estimation of Omnidirectional Camera with Improved EPnP Algorithm

The omnidirectional camera, having the advantage of broadening the field of view, realizes 360° imaging in the horizontal direction. Due to light reflection from the mirror surface, the collinearity relation is altered and the imaged scene has severe nonlinear distortions. This makes it more difficu...

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Detalles Bibliográficos
Autores principales: Gong, Xuanrui, Lv, Yaowen, Xu, Xiping, Wang, Yuxuan, Li, Mengdi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8228276/
https://www.ncbi.nlm.nih.gov/pubmed/34200669
http://dx.doi.org/10.3390/s21124008
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author Gong, Xuanrui
Lv, Yaowen
Xu, Xiping
Wang, Yuxuan
Li, Mengdi
author_facet Gong, Xuanrui
Lv, Yaowen
Xu, Xiping
Wang, Yuxuan
Li, Mengdi
author_sort Gong, Xuanrui
collection PubMed
description The omnidirectional camera, having the advantage of broadening the field of view, realizes 360° imaging in the horizontal direction. Due to light reflection from the mirror surface, the collinearity relation is altered and the imaged scene has severe nonlinear distortions. This makes it more difficult to estimate the pose of the omnidirectional camera. To solve this problem, we derive the mapping from omnidirectional camera to traditional camera and propose an omnidirectional camera linear imaging model. Based on the linear imaging model, we improve the EPnP algorithm to calculate the omnidirectional camera pose. To validate the proposed solution, we conducted simulations and physical experiments. Results show that the algorithm has a good performance in resisting noise.
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spelling pubmed-82282762021-06-26 Pose Estimation of Omnidirectional Camera with Improved EPnP Algorithm Gong, Xuanrui Lv, Yaowen Xu, Xiping Wang, Yuxuan Li, Mengdi Sensors (Basel) Article The omnidirectional camera, having the advantage of broadening the field of view, realizes 360° imaging in the horizontal direction. Due to light reflection from the mirror surface, the collinearity relation is altered and the imaged scene has severe nonlinear distortions. This makes it more difficult to estimate the pose of the omnidirectional camera. To solve this problem, we derive the mapping from omnidirectional camera to traditional camera and propose an omnidirectional camera linear imaging model. Based on the linear imaging model, we improve the EPnP algorithm to calculate the omnidirectional camera pose. To validate the proposed solution, we conducted simulations and physical experiments. Results show that the algorithm has a good performance in resisting noise. MDPI 2021-06-10 /pmc/articles/PMC8228276/ /pubmed/34200669 http://dx.doi.org/10.3390/s21124008 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Gong, Xuanrui
Lv, Yaowen
Xu, Xiping
Wang, Yuxuan
Li, Mengdi
Pose Estimation of Omnidirectional Camera with Improved EPnP Algorithm
title Pose Estimation of Omnidirectional Camera with Improved EPnP Algorithm
title_full Pose Estimation of Omnidirectional Camera with Improved EPnP Algorithm
title_fullStr Pose Estimation of Omnidirectional Camera with Improved EPnP Algorithm
title_full_unstemmed Pose Estimation of Omnidirectional Camera with Improved EPnP Algorithm
title_short Pose Estimation of Omnidirectional Camera with Improved EPnP Algorithm
title_sort pose estimation of omnidirectional camera with improved epnp algorithm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8228276/
https://www.ncbi.nlm.nih.gov/pubmed/34200669
http://dx.doi.org/10.3390/s21124008
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