Research Article Open Access

Facial Expression Recognition Using Local Binary Patterns

Abstract

The most expressive way humans display emotions is through facial expressions. The aim of facial expression recognition methods is to build a system for classification of facial expressions from static images automatically. The face area is first divided automatically into small regions, from which the local binary pattern (LBP) histograms are extracted and concatenated into a single feature histogram, efficiently representing facial expressions— anger, disgust, fear, happiness and neutral. The best recognition performance is obtained by using Support Vector Machine classifiers (SVM) on LBP features. Images are taken from JAFFE database for conducting experiments.

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