dc.contributor.advisor | Biswwas, Rubel | |
dc.contributor.author | Aurangzeb, Chowdhury Farsad | |
dc.contributor.author | Shanchary, Israt Jahan | |
dc.contributor.author | Tasdid, Salman | |
dc.date.accessioned | 2015-01-31T10:10:16Z | |
dc.date.available | 2015-01-31T10:10:16Z | |
dc.date.copyright | 2014 | |
dc.date.issued | 2014 | |
dc.identifier.other | ID 11301019 | |
dc.identifier.other | ID 10201022 | |
dc.identifier.other | ID 08110072 | |
dc.identifier.uri | http://hdl.handle.net/10361/3970 | |
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, 2014. | en_US |
dc.description | Cataloged from PDF version of thesis report. | |
dc.description | Includes bibliographical references (page 49 - 50). | |
dc.description.abstract | We are presenting a new framework for smart threat detection with the help of video surveillance
which captures live streaming from the camera and determine if any abandoned object has been
set up. It then raises an alarm right after the carrier of the bag leaves the scene. The abandoned
object is detected with the help of background subtraction and brought more accuracy on the
object’s image with the help of morphology. Every individual person on the frame is being
detected by their body with the help of Kalman filter and brought relation of the body with the
bag, so that the alarm is raised only when the body of the abandoned object carrier leaves the
frame. | en_US |
dc.description.statementofresponsibility | Chowdhury Farsad Aurangzeb | |
dc.description.statementofresponsibility | Israt Jahan Shanchary | |
dc.description.statementofresponsibility | Salman Tasdid | |
dc.format.extent | 50 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 | en_US |
dc.subject | Video surveillance | en_US |
dc.title | Abandoned object detection with video surveillance | 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 | |