Behavior Recognition In Video Surveillance System For Indoor Public Areas Using Artificial Immune System

Behavior recognition and predicting the activities of people in public areas are still a major concern in image processing and artificial intelligence science. Artificial intelligence systems are widely used to extract and analyze the complicated human actions through logical and mathematical rules....

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Main Author:	Abad, Azad
Format:	Thesis
Language:	English
Published:	2008
Subjects:	Artificial intelligence Image processing - Digital techniques
Online Access:	http://psasir.upm.edu.my/id/eprint/5384/1/FK_2008_26.pdf
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id	my-upm-ir.5384
record_format	uketd_dc
spelling	my-upm-ir.53842016-07-22T03:25:59Z Behavior Recognition In Video Surveillance System For Indoor Public Areas Using Artificial Immune System 2008 Abad, Azad Behavior recognition and predicting the activities of people in public areas are still a major concern in image processing and artificial intelligence science. Artificial intelligence systems are widely used to extract and analyze the complicated human actions through logical and mathematical rules. This study has explored an intelligent video surveillance system, presented by real time moving detection, object classification and interpreting the activity of the people by employing image segmentation and new approach in artificial intelligence called artificial immune system. The new system was compared with the previous methods in two level processing such as preprocessing for pixel manipulation and high level processing for behavior description. It was discovered that the new system required less processing time to apply filters in pixel level and higher data accuracy with less time complexity to generate training data and monitoring phase. This study further improved the performance of object tracking. The improvement was achieved by simplifying the previous algorithm without applying mathematical or probabilistically formulas and selects the effective filters to create a clearer foreground pixel map. Also, the robust algorithm with hands of artificial immune system rules like binary hamming shape-space and advance detector structure with fast decision making to detect three abnormal behaviors such as entering the forbidden area, standing more than threshold and running was implemented The result obtained showed the improvement in the duration for each phase when compared with previous methods in image segmentation like mixture of Gaussian and behavior recognition like and/Or tree or neural networks. Artificial intelligence Image processing - Digital techniques 2008 Thesis http://psasir.upm.edu.my/id/eprint/5384/ http://psasir.upm.edu.my/id/eprint/5384/1/FK_2008_26.pdf application/pdf en public masters Universiti Putra Malaysia Artificial intelligence Image processing - Digital techniques Faculty of Engineering
institution	Universiti Putra Malaysia
collection	PSAS Institutional Repository
language	English
topic	Artificial intelligence Image processing - Digital techniques
spellingShingle	Artificial intelligence Image processing - Digital techniques Abad, Azad Behavior Recognition In Video Surveillance System For Indoor Public Areas Using Artificial Immune System
description	Behavior recognition and predicting the activities of people in public areas are still a major concern in image processing and artificial intelligence science. Artificial intelligence systems are widely used to extract and analyze the complicated human actions through logical and mathematical rules. This study has explored an intelligent video surveillance system, presented by real time moving detection, object classification and interpreting the activity of the people by employing image segmentation and new approach in artificial intelligence called artificial immune system. The new system was compared with the previous methods in two level processing such as preprocessing for pixel manipulation and high level processing for behavior description. It was discovered that the new system required less processing time to apply filters in pixel level and higher data accuracy with less time complexity to generate training data and monitoring phase. This study further improved the performance of object tracking. The improvement was achieved by simplifying the previous algorithm without applying mathematical or probabilistically formulas and selects the effective filters to create a clearer foreground pixel map. Also, the robust algorithm with hands of artificial immune system rules like binary hamming shape-space and advance detector structure with fast decision making to detect three abnormal behaviors such as entering the forbidden area, standing more than threshold and running was implemented The result obtained showed the improvement in the duration for each phase when compared with previous methods in image segmentation like mixture of Gaussian and behavior recognition like and/Or tree or neural networks.
format	Thesis
qualification_level	Master's degree
author	Abad, Azad
author_facet	Abad, Azad
author_sort	Abad, Azad
title	Behavior Recognition In Video Surveillance System For Indoor Public Areas Using Artificial Immune System
title_short	Behavior Recognition In Video Surveillance System For Indoor Public Areas Using Artificial Immune System
title_full	Behavior Recognition In Video Surveillance System For Indoor Public Areas Using Artificial Immune System
title_fullStr	Behavior Recognition In Video Surveillance System For Indoor Public Areas Using Artificial Immune System
title_full_unstemmed	Behavior Recognition In Video Surveillance System For Indoor Public Areas Using Artificial Immune System
title_sort	behavior recognition in video surveillance system for indoor public areas using artificial immune system
granting_institution	Universiti Putra Malaysia
granting_department	Faculty of Engineering
publishDate	2008
url	http://psasir.upm.edu.my/id/eprint/5384/1/FK_2008_26.pdf
_version_	1747810412580044800

Behavior Recognition In Video Surveillance System For Indoor Public Areas Using Artificial Immune System

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