The comparative study of model-based and appearance based gait recognition for leave bag behind

Nowadays, the increasing number of crimes and violence in the world has become a concern of modern society. This is why the need for criminal recognition using gait used for civilian and forensic analysis applications has evoked considerable interest. The literature accurate the result can be found...

Full description

Saved in:

Bibliographic Details
Main Author:	Zainol, Norfazilah
Format:	Thesis
Language:	English English
Published:	2018
Subjects:	QA76 Computer software
Online Access:	http://eprints.uthm.edu.my/518/1/24p%20%20NORFAZILAH%20ZAINOL.pdf http://eprints.uthm.edu.my/518/2/NORFAZILAH%20ZAINOL%20WATERMARK.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-uthm-ep.518
record_format	uketd_dc
spelling	my-uthm-ep.5182021-07-25T08:34:50Z The comparative study of model-based and appearance based gait recognition for leave bag behind 2018-08 Zainol, Norfazilah QA76 Computer software Nowadays, the increasing number of crimes and violence in the world has become a concern of modern society. This is why the need for criminal recognition using gait used for civilian and forensic analysis applications has evoked considerable interest. The literature accurate the result can be found in gait recognition by leave bag behind detection especially in the critical area examples airport and shopping mall environment. This is important because the method used capable of identifying the subject based on their gait and can be presented as the most probable subject as a strong evidence for criminal identification. This research limited to leave the bag behind detection on gait recognition. In this research, the analysis performed using two methods which are Model-Based approaches and Appearance-Based approaches. The selected methods were implemented in MATLAB R2014a and R Studio and tested with a standard dataset from the Chinese Academy of Science (CASIA) and tested using two classifiers which is Support Vector Machine (SVM) and KNN (K nearest Neighbour) based on accuracy and misclassification rates (MER) metrics. The experiment results show that the accuracy and misclassification rate (MER) of Appearance-based approaches obtained is 93.66% and 6.33% respectively tested on SVM classifier then the accuracy and misclassification rate (MER) of Appearancebased approaches is 97.66% and 2.33% respectively tested on KNN algorithm. Meanwhile, the accuracy and misclassification rate (MER) of Model-based approaches obtained is 97.00% and 3.00% respectively tested on SVM classifier then the accuracy and misclassification rate (MER) of Model-based approaches is 99.00% and 1.00% respectively tested on KNN algorithm. It can be concluded from experiments conducted by Model-based approaches better than Appearance-based approaches because Model-Based approaches higher precision value as well as low misclassification. 2018-08 Thesis http://eprints.uthm.edu.my/518/ http://eprints.uthm.edu.my/518/1/24p%20%20NORFAZILAH%20ZAINOL.pdf text en public http://eprints.uthm.edu.my/518/2/NORFAZILAH%20ZAINOL%20WATERMARK.pdf text en validuser mphil masters Universiti Tun Hussein Onn Malaysia Faculty of Computer Science and Information Technology
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English
topic	QA76 Computer software
spellingShingle	QA76 Computer software Zainol, Norfazilah The comparative study of model-based and appearance based gait recognition for leave bag behind
description	Nowadays, the increasing number of crimes and violence in the world has become a concern of modern society. This is why the need for criminal recognition using gait used for civilian and forensic analysis applications has evoked considerable interest. The literature accurate the result can be found in gait recognition by leave bag behind detection especially in the critical area examples airport and shopping mall environment. This is important because the method used capable of identifying the subject based on their gait and can be presented as the most probable subject as a strong evidence for criminal identification. This research limited to leave the bag behind detection on gait recognition. In this research, the analysis performed using two methods which are Model-Based approaches and Appearance-Based approaches. The selected methods were implemented in MATLAB R2014a and R Studio and tested with a standard dataset from the Chinese Academy of Science (CASIA) and tested using two classifiers which is Support Vector Machine (SVM) and KNN (K nearest Neighbour) based on accuracy and misclassification rates (MER) metrics. The experiment results show that the accuracy and misclassification rate (MER) of Appearance-based approaches obtained is 93.66% and 6.33% respectively tested on SVM classifier then the accuracy and misclassification rate (MER) of Appearancebased approaches is 97.66% and 2.33% respectively tested on KNN algorithm. Meanwhile, the accuracy and misclassification rate (MER) of Model-based approaches obtained is 97.00% and 3.00% respectively tested on SVM classifier then the accuracy and misclassification rate (MER) of Model-based approaches is 99.00% and 1.00% respectively tested on KNN algorithm. It can be concluded from experiments conducted by Model-based approaches better than Appearance-based approaches because Model-Based approaches higher precision value as well as low misclassification.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Zainol, Norfazilah
author_facet	Zainol, Norfazilah
author_sort	Zainol, Norfazilah
title	The comparative study of model-based and appearance based gait recognition for leave bag behind
title_short	The comparative study of model-based and appearance based gait recognition for leave bag behind
title_full	The comparative study of model-based and appearance based gait recognition for leave bag behind
title_fullStr	The comparative study of model-based and appearance based gait recognition for leave bag behind
title_full_unstemmed	The comparative study of model-based and appearance based gait recognition for leave bag behind
title_sort	comparative study of model-based and appearance based gait recognition for leave bag behind
granting_institution	Universiti Tun Hussein Onn Malaysia
granting_department	Faculty of Computer Science and Information Technology
publishDate	2018
url	http://eprints.uthm.edu.my/518/1/24p%20%20NORFAZILAH%20ZAINOL.pdf http://eprints.uthm.edu.my/518/2/NORFAZILAH%20ZAINOL%20WATERMARK.pdf
_version_	1747830629729304576

The comparative study of model-based and appearance based gait recognition for leave bag behind

Similar Items