Tracking and indexing moving object in multitude environment

The project will be focusing on tracking multiple people in various environments specifically for outdoor scene. This will also involve in indexing each different person in the same area or background. Tracking 1 moving object is an easy works but if tracking involved more than 1 people the process...

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Main Author:	Abdul Kadir, Muhd. Khairulzaman
Format:	Thesis
Language:	English
Published:	2007
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/6406/1/MuhdKhairulzamanAbdulKadirMFKE2007.pdf
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id	my-utm-ep.6406
record_format	uketd_dc
spelling	my-utm-ep.64062018-08-26T04:45:27Z Tracking and indexing moving object in multitude environment 2007-05 Abdul Kadir, Muhd. Khairulzaman TK Electrical engineering. Electronics Nuclear engineering The project will be focusing on tracking multiple people in various environments specifically for outdoor scene. This will also involve in indexing each different person in the same area or background. Tracking 1 moving object is an easy works but if tracking involved more than 1 people the process will become harder. The complexity also is more complicated if it involves moving object occlusion and illuminations change in the image frame. In this tracking and indexing system, background subtraction model for each frame is being used for extracting the moving object from the background. But, before background subtraction model is executed, each frame (background and current) will be filtered by using Gaussian filter for reducing small noise in the frame and morphological filter process is perform after background subtraction. Next, each moving object will be labeled so as to differentiate each different people that exist in the same background or environment. This was done by using feature-based model method which used area, center point of each moving people and the average of RGB pixels value as recognition. All the work will be done in a grayscale image and applied to every frame. Without loss of generality, the indexing algorithm will be done up to 4 people within the same background with different types of actions (different posture) and different type of conditions (walking slow and faster). The results of this system are 100% accurate for 1 and 2 moving people without any errors. But, if the moving objects are from 3 to 4 people, the accuracy reduces around 25% due to the feature not robust enough in differentiating it. 2007-05 Thesis http://eprints.utm.my/id/eprint/6406/ http://eprints.utm.my/id/eprint/6406/1/MuhdKhairulzamanAbdulKadirMFKE2007.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:62215 masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Abdul Kadir, Muhd. Khairulzaman Tracking and indexing moving object in multitude environment
description	The project will be focusing on tracking multiple people in various environments specifically for outdoor scene. This will also involve in indexing each different person in the same area or background. Tracking 1 moving object is an easy works but if tracking involved more than 1 people the process will become harder. The complexity also is more complicated if it involves moving object occlusion and illuminations change in the image frame. In this tracking and indexing system, background subtraction model for each frame is being used for extracting the moving object from the background. But, before background subtraction model is executed, each frame (background and current) will be filtered by using Gaussian filter for reducing small noise in the frame and morphological filter process is perform after background subtraction. Next, each moving object will be labeled so as to differentiate each different people that exist in the same background or environment. This was done by using feature-based model method which used area, center point of each moving people and the average of RGB pixels value as recognition. All the work will be done in a grayscale image and applied to every frame. Without loss of generality, the indexing algorithm will be done up to 4 people within the same background with different types of actions (different posture) and different type of conditions (walking slow and faster). The results of this system are 100% accurate for 1 and 2 moving people without any errors. But, if the moving objects are from 3 to 4 people, the accuracy reduces around 25% due to the feature not robust enough in differentiating it.
format	Thesis
qualification_level	Master's degree
author	Abdul Kadir, Muhd. Khairulzaman
author_facet	Abdul Kadir, Muhd. Khairulzaman
author_sort	Abdul Kadir, Muhd. Khairulzaman
title	Tracking and indexing moving object in multitude environment
title_short	Tracking and indexing moving object in multitude environment
title_full	Tracking and indexing moving object in multitude environment
title_fullStr	Tracking and indexing moving object in multitude environment
title_full_unstemmed	Tracking and indexing moving object in multitude environment
title_sort	tracking and indexing moving object in multitude environment
granting_institution	Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department	Faculty of Electrical Engineering
publishDate	2007
url	http://eprints.utm.my/id/eprint/6406/1/MuhdKhairulzamanAbdulKadirMFKE2007.pdf
_version_	1747814652439429120

Tracking and indexing moving object in multitude environment

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