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A Vision Based Top-View Transformation Model for a Vehicle Parking Assistant

This paper proposes the Top-View Transformation Model for image coordinate transformation, which involves transforming a perspective projection image into its corresponding bird's eye vision. A fitting parameters searching algorithm estimates the parameters that are used to transform the coordi...

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Detalles Bibliográficos
Autores principales: Lin, Chien-Chuan, Wang, Ming-Shi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3355419/
https://www.ncbi.nlm.nih.gov/pubmed/22666038
http://dx.doi.org/10.3390/s120404431
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author Lin, Chien-Chuan
Wang, Ming-Shi
author_facet Lin, Chien-Chuan
Wang, Ming-Shi
author_sort Lin, Chien-Chuan
collection PubMed
description This paper proposes the Top-View Transformation Model for image coordinate transformation, which involves transforming a perspective projection image into its corresponding bird's eye vision. A fitting parameters searching algorithm estimates the parameters that are used to transform the coordinates from the source image. Using this approach, it is not necessary to provide any interior and exterior orientation parameters of the camera. The designed car parking assistant system can be installed at the rear end of the car, providing the driver with a clearer image of the area behind the car. The processing time can be reduced by storing and using the transformation matrix estimated from the first image frame for a sequence of video images. The transformation matrix can be stored as the Matrix Mapping Table, and loaded into the embedded platform to perform the transformation. Experimental results show that the proposed approaches can provide a clearer and more accurate bird's eye view to the vehicle driver.
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spelling pubmed-33554192012-06-04 A Vision Based Top-View Transformation Model for a Vehicle Parking Assistant Lin, Chien-Chuan Wang, Ming-Shi Sensors (Basel) Article This paper proposes the Top-View Transformation Model for image coordinate transformation, which involves transforming a perspective projection image into its corresponding bird's eye vision. A fitting parameters searching algorithm estimates the parameters that are used to transform the coordinates from the source image. Using this approach, it is not necessary to provide any interior and exterior orientation parameters of the camera. The designed car parking assistant system can be installed at the rear end of the car, providing the driver with a clearer image of the area behind the car. The processing time can be reduced by storing and using the transformation matrix estimated from the first image frame for a sequence of video images. The transformation matrix can be stored as the Matrix Mapping Table, and loaded into the embedded platform to perform the transformation. Experimental results show that the proposed approaches can provide a clearer and more accurate bird's eye view to the vehicle driver. Molecular Diversity Preservation International (MDPI) 2012-03-30 /pmc/articles/PMC3355419/ /pubmed/22666038 http://dx.doi.org/10.3390/s120404431 Text en © 2012 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Lin, Chien-Chuan
Wang, Ming-Shi
A Vision Based Top-View Transformation Model for a Vehicle Parking Assistant
title A Vision Based Top-View Transformation Model for a Vehicle Parking Assistant
title_full A Vision Based Top-View Transformation Model for a Vehicle Parking Assistant
title_fullStr A Vision Based Top-View Transformation Model for a Vehicle Parking Assistant
title_full_unstemmed A Vision Based Top-View Transformation Model for a Vehicle Parking Assistant
title_short A Vision Based Top-View Transformation Model for a Vehicle Parking Assistant
title_sort vision based top-view transformation model for a vehicle parking assistant
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3355419/
https://www.ncbi.nlm.nih.gov/pubmed/22666038
http://dx.doi.org/10.3390/s120404431
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