Fuzzy-based path analysis

Video surveillance can be a very powerful tool in the fight against crime, by accurately monitoring human activities. Nevertheless, most surveillance systems today provide only a passive form of site monitoring. Extensive video records may be kept to help find the instigator of criminal activities a...

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Main Authors: Khan, Imran Moez, Htike@Muhammad Yusof, Zaw Zaw, Khalifa, Othman Omran, Weng, Kin Lai
Format: Conference or Workshop Item
Language:English
Published: 2009
Subjects:
Online Access:http://irep.iium.edu.my/8505/
http://irep.iium.edu.my/8505/1/WAIC09-1.1%282%29.pdf
id iium-8505
recordtype eprints
spelling iium-85052015-06-01T01:31:39Z http://irep.iium.edu.my/8505/ Fuzzy-based path analysis Khan, Imran Moez Htike@Muhammad Yusof, Zaw Zaw Khalifa, Othman Omran Weng, Kin Lai TK Electrical engineering. Electronics Nuclear engineering TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices Video surveillance can be a very powerful tool in the fight against crime, by accurately monitoring human activities. Nevertheless, most surveillance systems today provide only a passive form of site monitoring. Extensive video records may be kept to help find the instigator of criminal activities after the crime has been committed but preventive measures usually require human involvement. In addition to this, there is a need for large amounts of data storage to keep up to several terabytes of video streams that may be needed for later analysis. In order to achieve any form of real-time monitoring, guards often need to be employed to watch video feeds for hours on end to recognize suspicious, dangerous or potentially harmful situations. In a multi-camera scene monitoring system, this can be quite infeasible as there can be up to 20 to 50 cameras on average in a large building complex such as an airport or shopping malls. Intelligent video surveillance aims to reduce or even eliminate the need for human supervision of video feeds, and continuous recording. Having such a system will provide numerous other facilities and services to operators and emergency teams, by conducting behavioral analysis on incoming video feeds and detecting unusual or suspicious behavior. Behavioral analysis itself can be applied to numerous features extracted from video sequences including path detection and classification of which several methods are reviewed here. In this paper, we investigated a fuzzy inference engine approach to identify the human trajectories based on the paths that had been modeled by a self-learning system. 2009 Conference or Workshop Item NonPeerReviewed application/pdf en http://irep.iium.edu.my/8505/1/WAIC09-1.1%282%29.pdf Khan, Imran Moez and Htike@Muhammad Yusof, Zaw Zaw and Khalifa, Othman Omran and Weng, Kin Lai (2009) Fuzzy-based path analysis. In: Workshop on Advances in Intelligent Computing, 7-8 December 2009, Kuala Lumpur, Malaysia.
repository_type Digital Repository
institution_category Local University
institution International Islamic University Malaysia
building IIUM Repository
collection Online Access
language English
topic TK Electrical engineering. Electronics Nuclear engineering
TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
Khan, Imran Moez
Htike@Muhammad Yusof, Zaw Zaw
Khalifa, Othman Omran
Weng, Kin Lai
Fuzzy-based path analysis
description Video surveillance can be a very powerful tool in the fight against crime, by accurately monitoring human activities. Nevertheless, most surveillance systems today provide only a passive form of site monitoring. Extensive video records may be kept to help find the instigator of criminal activities after the crime has been committed but preventive measures usually require human involvement. In addition to this, there is a need for large amounts of data storage to keep up to several terabytes of video streams that may be needed for later analysis. In order to achieve any form of real-time monitoring, guards often need to be employed to watch video feeds for hours on end to recognize suspicious, dangerous or potentially harmful situations. In a multi-camera scene monitoring system, this can be quite infeasible as there can be up to 20 to 50 cameras on average in a large building complex such as an airport or shopping malls. Intelligent video surveillance aims to reduce or even eliminate the need for human supervision of video feeds, and continuous recording. Having such a system will provide numerous other facilities and services to operators and emergency teams, by conducting behavioral analysis on incoming video feeds and detecting unusual or suspicious behavior. Behavioral analysis itself can be applied to numerous features extracted from video sequences including path detection and classification of which several methods are reviewed here. In this paper, we investigated a fuzzy inference engine approach to identify the human trajectories based on the paths that had been modeled by a self-learning system.
format Conference or Workshop Item
author Khan, Imran Moez
Htike@Muhammad Yusof, Zaw Zaw
Khalifa, Othman Omran
Weng, Kin Lai
author_facet Khan, Imran Moez
Htike@Muhammad Yusof, Zaw Zaw
Khalifa, Othman Omran
Weng, Kin Lai
author_sort Khan, Imran Moez
title Fuzzy-based path analysis
title_short Fuzzy-based path analysis
title_full Fuzzy-based path analysis
title_fullStr Fuzzy-based path analysis
title_full_unstemmed Fuzzy-based path analysis
title_sort fuzzy-based path analysis
publishDate 2009
url http://irep.iium.edu.my/8505/
http://irep.iium.edu.my/8505/1/WAIC09-1.1%282%29.pdf
first_indexed 2023-09-18T20:18:14Z
last_indexed 2023-09-18T20:18:14Z
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