dc.contributor.advisor | Ahmed, Tarem | |
dc.contributor.author | Motiwala, Murtaza | |
dc.contributor.author | Ahmed, Shupriyo Shafkat | |
dc.contributor.author | Ahmed, Sabrina | |
dc.date.accessioned | 2010-12-09T07:34:24Z | |
dc.date.available | 2010-12-09T07:34:24Z | |
dc.date.copyright | 2009 | |
dc.date.issued | 2009-04 | |
dc.identifier.other | ID 05310010 | |
dc.identifier.other | ID 05210036 | |
dc.identifier.other | ID 05310005 | |
dc.identifier.uri | http://hdl.handle.net/10361/683 | |
dc.description | This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2009. | |
dc.description | Cataloged from PDF version of thesis report. | |
dc.description | Includes bibliographical references (page 47). | |
dc.description.abstract | The importance of public security cannot be overemphasized in today’s world. Surveillance systems consisting of extensive camera networks now have many applications. The London Underground has 9000 cameras, with each staff required to monitor as many as 60 at a time. This presents a significant scope for automation. Processing a sequence of images from a network presents challenges in terms of deciding upon the feature set to be extracted, and the appropriate choice of algorithm. We investigate methods based upon principal component analysis and nearest-neighbor distances to propose a system of automated intruder detection in surveillance systems and suggest new applications in Bangladesh of such systems. | en_US |
dc.description.statementofresponsibility | Murtaza Motiwala | |
dc.description.statementofresponsibility | Shupriyo Shafkat Ahmed | |
dc.description.statementofresponsibility | Sabrina Ahmed | |
dc.format.extent | 47 pages | |
dc.language.iso | en | en_US |
dc.publisher | BRAC University | en_US |
dc.rights | BRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. | |
dc.subject | Computer science and engineering | |
dc.title | Automated incident detection in surveillance systems | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Department of Computer Science and Engineering, BRAC University | |
dc.description.degree | B. Computer science and engineering | |