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Object Occlusion Detection Using Automatic Camera Calibration for a Wide-Area Video Surveillance System

This paper presents an object occlusion detection algorithm using object depth information that is estimated by automatic camera calibration. The object occlusion problem is a major factor to degrade the performance of object tracking and recognition. To detect an object occlusion, the proposed algo...

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Detalles Bibliográficos
Autores principales: Jung, Jaehoon, Yoon, Inhye, Paik, Joonki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4970033/
https://www.ncbi.nlm.nih.gov/pubmed/27347978
http://dx.doi.org/10.3390/s16070982
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author Jung, Jaehoon
Yoon, Inhye
Paik, Joonki
author_facet Jung, Jaehoon
Yoon, Inhye
Paik, Joonki
author_sort Jung, Jaehoon
collection PubMed
description This paper presents an object occlusion detection algorithm using object depth information that is estimated by automatic camera calibration. The object occlusion problem is a major factor to degrade the performance of object tracking and recognition. To detect an object occlusion, the proposed algorithm consists of three steps: (i) automatic camera calibration using both moving objects and a background structure; (ii) object depth estimation; and (iii) detection of occluded regions. The proposed algorithm estimates the depth of the object without extra sensors but with a generic red, green and blue (RGB) camera. As a result, the proposed algorithm can be applied to improve the performance of object tracking and object recognition algorithms for video surveillance systems.
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spelling pubmed-49700332016-08-04 Object Occlusion Detection Using Automatic Camera Calibration for a Wide-Area Video Surveillance System Jung, Jaehoon Yoon, Inhye Paik, Joonki Sensors (Basel) Article This paper presents an object occlusion detection algorithm using object depth information that is estimated by automatic camera calibration. The object occlusion problem is a major factor to degrade the performance of object tracking and recognition. To detect an object occlusion, the proposed algorithm consists of three steps: (i) automatic camera calibration using both moving objects and a background structure; (ii) object depth estimation; and (iii) detection of occluded regions. The proposed algorithm estimates the depth of the object without extra sensors but with a generic red, green and blue (RGB) camera. As a result, the proposed algorithm can be applied to improve the performance of object tracking and object recognition algorithms for video surveillance systems. MDPI 2016-06-25 /pmc/articles/PMC4970033/ /pubmed/27347978 http://dx.doi.org/10.3390/s16070982 Text en © 2016 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 (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Jung, Jaehoon
Yoon, Inhye
Paik, Joonki
Object Occlusion Detection Using Automatic Camera Calibration for a Wide-Area Video Surveillance System
title Object Occlusion Detection Using Automatic Camera Calibration for a Wide-Area Video Surveillance System
title_full Object Occlusion Detection Using Automatic Camera Calibration for a Wide-Area Video Surveillance System
title_fullStr Object Occlusion Detection Using Automatic Camera Calibration for a Wide-Area Video Surveillance System
title_full_unstemmed Object Occlusion Detection Using Automatic Camera Calibration for a Wide-Area Video Surveillance System
title_short Object Occlusion Detection Using Automatic Camera Calibration for a Wide-Area Video Surveillance System
title_sort object occlusion detection using automatic camera calibration for a wide-area video surveillance system
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4970033/
https://www.ncbi.nlm.nih.gov/pubmed/27347978
http://dx.doi.org/10.3390/s16070982
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