Crowd detection from aerial images

The detection of crowd from surveillance imagery is important to monitor public places and to ensure public safety. Hence, this work proposes crowd detection from static image captured from Unmanned Aerial Vehicle. The proposed methodology consists of three steps: FAST feature extraction, Gray Level...

Full description

Saved in:

Bibliographic Details
Main Author:	Md. Zaini, Siti Ernee
Format:	Thesis
Language:	English
Published:	2015
Subjects:	TK7885-7895 Computer engineer Computer hardware
Online Access:	http://eprints.utm.my/id/eprint/48892/25/SitiErneeMdzAiniMFKE2015.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-utm-ep.48892
record_format	uketd_dc
spelling	my-utm-ep.488922020-07-05T06:48:38Z Crowd detection from aerial images 2015-01 Md. Zaini, Siti Ernee TK7885-7895 Computer engineer. Computer hardware The detection of crowd from surveillance imagery is important to monitor public places and to ensure public safety. Hence, this work proposes crowd detection from static image captured from Unmanned Aerial Vehicle. The proposed methodology consists of three steps: FAST feature extraction, Gray Level Co-Occurrence Matrix (GLCM) feature computation and the use of Support Vector Machine (SVM) for classification. The use of FAST corner detector is to obtain regions of interest where possible existence of crowd. The application of GLCM is to extract second order statistical texture features for texture analysis. The result of GLCM then, will be classified to crowd and non-crowd using SVM. For evaluation, ten different images were used taken in various crowd formation, event and location. The accuracy of the proposed method is obtained and the classification results are shown visually. 2015-01 Thesis http://eprints.utm.my/id/eprint/48892/ http://eprints.utm.my/id/eprint/48892/25/SitiErneeMdzAiniMFKE2015.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:86749 masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK7885-7895 Computer engineer Computer hardware
spellingShingle	TK7885-7895 Computer engineer Computer hardware Md. Zaini, Siti Ernee Crowd detection from aerial images
description	The detection of crowd from surveillance imagery is important to monitor public places and to ensure public safety. Hence, this work proposes crowd detection from static image captured from Unmanned Aerial Vehicle. The proposed methodology consists of three steps: FAST feature extraction, Gray Level Co-Occurrence Matrix (GLCM) feature computation and the use of Support Vector Machine (SVM) for classification. The use of FAST corner detector is to obtain regions of interest where possible existence of crowd. The application of GLCM is to extract second order statistical texture features for texture analysis. The result of GLCM then, will be classified to crowd and non-crowd using SVM. For evaluation, ten different images were used taken in various crowd formation, event and location. The accuracy of the proposed method is obtained and the classification results are shown visually.
format	Thesis
qualification_level	Master's degree
author	Md. Zaini, Siti Ernee
author_facet	Md. Zaini, Siti Ernee
author_sort	Md. Zaini, Siti Ernee
title	Crowd detection from aerial images
title_short	Crowd detection from aerial images
title_full	Crowd detection from aerial images
title_fullStr	Crowd detection from aerial images
title_full_unstemmed	Crowd detection from aerial images
title_sort	crowd detection from aerial images
granting_institution	Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department	Faculty of Electrical Engineering
publishDate	2015
url	http://eprints.utm.my/id/eprint/48892/25/SitiErneeMdzAiniMFKE2015.pdf
_version_	1747817497234505728

Crowd detection from aerial images

Similar Items