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Automated incident detection in surveillance systems

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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


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