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%20%20%20%20Using%20Support%20Vector%20Machine%20and%20Local%20Binary%20Pattern%20For%20Facial%20Expression%20Recognition
Research article
  

Using Support Vector Machine and Local Binary Pattern For Facial Expression Recognition


Ayeni Olaniyi Abiodun, Alese Boniface Kayode, Dada Olabisi Matemilayo

1. Department of Computer Science, Federal University Technology Akure, PMB 704, Akure, Nigeria.
2. Department of computer science, Kwara state polytechnic Ilorin, Kwara-State, Nigeria.


Corresponding author :

Ayeni Olaniyi Abiodun,
Email:

Received: September 22, 2015,   Accepted: December 14, 2015,   Published: December 14, 2015.


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: 10.15297/JCLS.V3I2.02


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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      Journal of Computation in Biosciences and Engineering