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Video Mining for Observing Human Activities

With the advance in video technology, video cameras have become an integral part of daily life. They are installed in parking lots, traffic intersections, airports, banks, etc. Usually a human operator watches them to catch events of interest in the scene, but this is a tedious and time consuming pr...

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Main Author:	Altahir Mohammed, Altahir Abdalla Altahir Mohammed
Format:	Thesis
Language:	English English English English English English English English English English
Published:	2008
Online Access:	http://utpedia.utp.edu.my/2892/1/Appendix.pdf http://utpedia.utp.edu.my/2892/2/AWARDS_AND_PUBLICATIONS.pdf http://utpedia.utp.edu.my/2892/3/BIBLIOGRAPHY.pdf http://utpedia.utp.edu.my/2892/4/CH1.pdf http://utpedia.utp.edu.my/2892/5/CH2.pdf http://utpedia.utp.edu.my/2892/6/CH3.pdf http://utpedia.utp.edu.my/2892/7/CH4.pdf http://utpedia.utp.edu.my/2892/8/CH5.pdf http://utpedia.utp.edu.my/2892/9/Conclusion.pdf http://utpedia.utp.edu.my/2892/10/first_pages.pdf http://utpedia.utp.edu.my/2892/
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id	my-utp-utpedia.2892
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spelling	my-utp-utpedia.28922017-01-25T09:44:47Z http://utpedia.utp.edu.my/2892/ Video Mining for Observing Human Activities Altahir Mohammed, Altahir Abdalla Altahir Mohammed With the advance in video technology, video cameras have become an integral part of daily life. They are installed in parking lots, traffic intersections, airports, banks, etc. Usually a human operator watches them to catch events of interest in the scene, but this is a tedious and time consuming process requiring constant attention, and leads to inadequate surveillance capability. Therefore, there is an urgent need for automated systems for analysis of surveillance video streams. This thesis presents a novel operational computer vision framework for visual knowledge extraction from human motion. The system captures a video of a scene and classifies those moving objects which are characteristically human. Then perform analyzing and mining operations based on full frame based analysis and inter frame based analysis to interpret the current activity. Moreover, based on selective criteria from full frame board and inter frame board the system evaluate the current activity to assist the security officers to catch the events of interest moreover, creating multi storing scheme for reducing the storage capacity in 24 hours surveillances system. 2008-12 Thesis NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/2892/1/Appendix.pdf application/pdf en http://utpedia.utp.edu.my/2892/2/AWARDS_AND_PUBLICATIONS.pdf application/pdf en http://utpedia.utp.edu.my/2892/3/BIBLIOGRAPHY.pdf application/pdf en http://utpedia.utp.edu.my/2892/4/CH1.pdf application/pdf en http://utpedia.utp.edu.my/2892/5/CH2.pdf application/pdf en http://utpedia.utp.edu.my/2892/6/CH3.pdf application/pdf en http://utpedia.utp.edu.my/2892/7/CH4.pdf application/pdf en http://utpedia.utp.edu.my/2892/8/CH5.pdf application/pdf en http://utpedia.utp.edu.my/2892/9/Conclusion.pdf application/pdf en http://utpedia.utp.edu.my/2892/10/first_pages.pdf Altahir Mohammed, Altahir Abdalla Altahir Mohammed (2008) Video Mining for Observing Human Activities. Masters thesis, UNIVERSITI TEKNOLOGI PETRONAS.
institution	Universiti Teknologi Petronas
building	UTP Resource Centre
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Petronas
content_source	UTP Electronic and Digitized Intellectual Asset
url_provider	http://utpedia.utp.edu.my/
language	English English English English English English English English English English
description	With the advance in video technology, video cameras have become an integral part of daily life. They are installed in parking lots, traffic intersections, airports, banks, etc. Usually a human operator watches them to catch events of interest in the scene, but this is a tedious and time consuming process requiring constant attention, and leads to inadequate surveillance capability. Therefore, there is an urgent need for automated systems for analysis of surveillance video streams. This thesis presents a novel operational computer vision framework for visual knowledge extraction from human motion. The system captures a video of a scene and classifies those moving objects which are characteristically human. Then perform analyzing and mining operations based on full frame based analysis and inter frame based analysis to interpret the current activity. Moreover, based on selective criteria from full frame board and inter frame board the system evaluate the current activity to assist the security officers to catch the events of interest moreover, creating multi storing scheme for reducing the storage capacity in 24 hours surveillances system.
format	Thesis
author	Altahir Mohammed, Altahir Abdalla Altahir Mohammed
spellingShingle	Altahir Mohammed, Altahir Abdalla Altahir Mohammed Video Mining for Observing Human Activities
author_facet	Altahir Mohammed, Altahir Abdalla Altahir Mohammed
author_sort	Altahir Mohammed, Altahir Abdalla Altahir Mohammed
title	Video Mining for Observing Human Activities
title_short	Video Mining for Observing Human Activities
title_full	Video Mining for Observing Human Activities
title_fullStr	Video Mining for Observing Human Activities
title_full_unstemmed	Video Mining for Observing Human Activities
title_sort	video mining for observing human activities
publishDate	2008
url	http://utpedia.utp.edu.my/2892/1/Appendix.pdf http://utpedia.utp.edu.my/2892/2/AWARDS_AND_PUBLICATIONS.pdf http://utpedia.utp.edu.my/2892/3/BIBLIOGRAPHY.pdf http://utpedia.utp.edu.my/2892/4/CH1.pdf http://utpedia.utp.edu.my/2892/5/CH2.pdf http://utpedia.utp.edu.my/2892/6/CH3.pdf http://utpedia.utp.edu.my/2892/7/CH4.pdf http://utpedia.utp.edu.my/2892/8/CH5.pdf http://utpedia.utp.edu.my/2892/9/Conclusion.pdf http://utpedia.utp.edu.my/2892/10/first_pages.pdf http://utpedia.utp.edu.my/2892/
_version_	1739830972503818240
score	13.211869

Video Mining for Observing Human Activities

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