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dc.contributor.advisorUddin, Dr. Jia
dc.contributor.authorLaboni, Pragna
dc.contributor.authorZaman, Nusrat
dc.date.accessioned2017-12-26T06:49:42Z
dc.date.available2017-12-26T06:49:42Z
dc.date.copyright2017
dc.date.issued8/21/2017
dc.identifier.otherID 12101074
dc.identifier.otherID 12101105
dc.identifier.urihttp://hdl.handle.net/10361/8705
dc.descriptionCataloged from PDF version of thesis report.
dc.descriptionIncludes bibliographical references (page 26-27).
dc.descriptionThis thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017.en_US
dc.description.abstractFacial Expression gives vital information about emotion of human being. It is really a speedily growing and an ever green research field in the sector of computer vision, artificial intelligence and automation. If we talk about a fully automated system, it might be used to have an interaction between a human being and a computer. Here a user without using his hands can give command to system with the help of facial expression. We are proposing a facial expression recognition model analyzes an image of a face and detects alignments to six different emotions which are disgust, annoy, surprise, crying, happiness and neutral. In this research we choosed JAFFE dataset and we used mean and standard deviation method to classify the images into categories. A new algorithm based on a set of images to face recognition is proposed here.en_US
dc.format.extent27 pages
dc.language.isoenen_US
dc.publisherBRAC 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.subjectFacial expressionen_US
dc.subjectComputer visionen_US
dc.subjectArtificial intelligenceen_US
dc.subjectExpression recognitionen_US
dc.subjectJAFFE dataseten_US
dc.titleAn efficient facial expression recognition method using mean And standard deviationen_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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