Using Support Vector Machine and Local Binary Pattern For Facial Expression Recognition
Ayeni Olaniyi Abiodun, Alese Boniface Kayode, Dada Olabisi Matemilayo
Corresponding Author : Ayeni Olaniyi Abiodun,
Department of Computer Science, Federal University Technology Akure, PMB 704, Akure, Nigeria.
Email ID : email@example.com
Received : 2015-09-22 Accepted : 2015-12-14 Published : 2015-12-14
Abstract : Facial expressions are natural ways by which people can express their feelings and emotions. In the field of affective computing and human computer interactions, a better result will be achieved when we have an intelligent interface(s) that could act and behaves in a way similar to that of human being. This research intends to bring about the development of a face recognition model and applying it to a real-data set of expressions. Five expressions will be classified which include: fear, happiness, disgust, sadness and surprise using the innovations of support vector machine (SVM) and local binary pattern (LBP). The students of Federal University of Technology, Akure (FUTA) will be used as a case study. LBP will be used for feature extraction while SVM will be used for classification and recognition of expressions.
Keywords : facial expression, detection, recognition, support vector machine, principal local binary pattern & face feature.
Citation : Ayeni Olaniyi Abiodun. (2015). Using Support Vector Machine and Local Binary Pattern For Facial Expression Recognition. J. of Computation in Biosciences and Engineering. V3I2. DOI : 10.5281/zenodo.898046
Copyright : © 2015 Ayeni Olaniyi Abiodun. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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