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dc.contributor.advisorAlom, Md. Zahangir
dc.contributor.authorHoque, Md. Rezwanul
dc.contributor.authorKarim, Nabil Tahmidul
dc.contributor.authorRozario, Saikat Lawrence
dc.contributor.authorMd. Rumman Bin Ashraf
dc.date.accessioned2013-09-09T05:07:11Z
dc.date.available2013-09-09T05:07:11Z
dc.date.copyright2013
dc.date.issued2013-09-01
dc.identifier.otherID 09201016
dc.identifier.otherID 09201020
dc.identifier.otherID 10101007
dc.identifier.otherID 10101028
dc.identifier.urihttp://hdl.handle.net/10361/2747
dc.descriptionThis thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2013.
dc.descriptionCataloged from PDF version of thesis report.
dc.descriptionIncludes bibliographical references (page 50).
dc.description.abstractThis paper presents an automated system for human face recognition in a real time background for a company to mark the attendance of their employees. So Smart Attendance using Real Time Face Recognition is a real world solution which comes with day to day activities of handling employees. The task is very difficult as the real time background subtraction in an image is still a challenge. To detect real time human face Haar cascade is used and a simple fast Principal Component Analysis is used to recognize the faces detected with a high accuracy rate. The matched face is then used to mark attendance of the employees. Our system generates how much time each employee spends at his workstation and provides update to the employer whenever he wants. This product gives much more solutions with accurate results in user interactive manner rather than existing attendance and leave management systems.en_US
dc.description.statementofresponsibilityMd. Rezwanul Hoque
dc.description.statementofresponsibilityNabil Tahmidul Karim
dc.description.statementofresponsibilitySaikat Lawrence Rozario
dc.description.statementofresponsibilityAshraf, Md. Rumman Bin
dc.format.extent51 pages
dc.language.isoenen_US
dc.publisherDepartment of Computer Science and Engineering, BRAC Universityen_US
dc.rightsBRAC 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.subjectReal Time Face Recognitionen_US
dc.subjectPrinciple Component Analysisen_US
dc.subjectNatural Language Processingen_US
dc.subjectFace recognitionen_US
dc.subjectHaar Cascade Classifieren_US
dc.subjectComputer science and engineering
dc.titleComputer vision based employee activities analysisen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, BRAC University
dc.description.degreeB. Computer Science and Engineering


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