Pattern Averaging Technique for Facial Expression Recognition Using Support Vector Machines

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N.P.Gopalan 1,* Sivaiah Bellamkonda 1

1. 2Department of Computer Applications, National Institute of Technology, Tiruchirappalli, India

* Corresponding author.


Received: 24 May 2018 / Revised: 14 Jun. 2018 / Accepted: 3 Jul. 2018 / Published: 8 Sep. 2018

Index Terms

Facial expression recognition, pattern averaging, support vector machine, human-computer interaction


Facial expression is one of the nonverbal communication methods of identifying an emotional state of a human being.  Due to its crucial importance in Human-Robot interaction, facial expression recognition (FER) is in the limelight of recent research activities.  Most of the studies consider the whole expression images in their analysis, and it has several has several drawbacks concerning illumination, orientation, texture, zoom level, time and space complexity. In this paper, a novel feature extraction technique called the pattern averaging is studied on whole image data using reduction in the dimension of the image by averaging the neighboring pixels. The study is found to give better results on standard datasets using support vector machine classifier. 

Cite This Paper

N. P. Gopalan, Sivaiah Bellamkonda, " Pattern Averaging Technique for Facial Expression Recognition Using Support Vector Machines", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.10, No.9, pp. 27-33, 2018. DOI: 10.5815/ijigsp.2018.09.04


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