Optimization of image mapping & camera coverage efficiency for continuous location and tracking

The Vision Based location and tracking is a vastly escalating technology mainly used to monitor various environments. This technology can be briefly divided to 3 parts which is the localization of image sensors (cameras), maximizing the total area of vision and the locating and tracking of other obj...

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Main Authors: Avinash, A.R., Chandan, K.C.
Format: Conference Paper
Language:en_US
Published: 2017
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spelling my.uniten.dspace-57282017-12-14T04:10:38Z Optimization of image mapping & camera coverage efficiency for continuous location and tracking Avinash, A.R. Chandan, K.C. The Vision Based location and tracking is a vastly escalating technology mainly used to monitor various environments. This technology can be briefly divided to 3 parts which is the localization of image sensors (cameras), maximizing the total area of vision and the locating and tracking of other objects. Initially only one GPS camera is used for reference and timing purposes. By using the image mapping technique distance between 1st and 2nd camera can be obtained. Thus by knowing the rotation angle of the 2nd camera to locate the first camera, the 2nd camera can be localized .This same method is used for the other cameras to localize itself. Finally when all cameras are localized tracking of objects can proceed. Simulation done using Matlab has proved the significance of image mapping method (error=1.3%), iteration algorithm (error=5.98%) and velocity tracking (error=0.52%) when results of simulation was compared to actual measurement. ©2009 IEEE. 2017-12-08T06:45:44Z 2017-12-08T06:45:44Z 2009 Conference Paper 10.1109/MICC.2009.5431397 en_US Proceedings - MICC 2009: 2009 IEEE 9th Malaysia International Conference on Communications with a Special Workshop on Digital TV Contents 2009, Article number 5431397, Pages 742-747
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
language en_US
description The Vision Based location and tracking is a vastly escalating technology mainly used to monitor various environments. This technology can be briefly divided to 3 parts which is the localization of image sensors (cameras), maximizing the total area of vision and the locating and tracking of other objects. Initially only one GPS camera is used for reference and timing purposes. By using the image mapping technique distance between 1st and 2nd camera can be obtained. Thus by knowing the rotation angle of the 2nd camera to locate the first camera, the 2nd camera can be localized .This same method is used for the other cameras to localize itself. Finally when all cameras are localized tracking of objects can proceed. Simulation done using Matlab has proved the significance of image mapping method (error=1.3%), iteration algorithm (error=5.98%) and velocity tracking (error=0.52%) when results of simulation was compared to actual measurement. ©2009 IEEE.
format Conference Paper
author Avinash, A.R.
Chandan, K.C.
spellingShingle Avinash, A.R.
Chandan, K.C.
Optimization of image mapping & camera coverage efficiency for continuous location and tracking
author_facet Avinash, A.R.
Chandan, K.C.
author_sort Avinash, A.R.
title Optimization of image mapping & camera coverage efficiency for continuous location and tracking
title_short Optimization of image mapping & camera coverage efficiency for continuous location and tracking
title_full Optimization of image mapping & camera coverage efficiency for continuous location and tracking
title_fullStr Optimization of image mapping & camera coverage efficiency for continuous location and tracking
title_full_unstemmed Optimization of image mapping & camera coverage efficiency for continuous location and tracking
title_sort optimization of image mapping & camera coverage efficiency for continuous location and tracking
publishDate 2017
_version_ 1644493760094011392
score 13.189025