Superiority of PCA algorithm for Facial Expression Recognition

摘要

Facial expression recognition is a rapidly growing area of research in computer vision due to its immense applications such as human-computer interaction, psychology and intelligent robotic systems etc. Various methods have been proposed in past two decades aiming to solve different issues in this aspect. Most of the researches used distinct databases for the evaluation of their techniques, so it is very challenging task to infer which one is superior. In this paper, we have implemented three methods of facial expression recognition named: Principal Component Analysis (PCA), Artificial Neural Network (ANN) and Local Binary Pattern (LBP) and evaluated their performances using JAFFE database. Keywords: Facial Expression Recognition, Emotion Recognition, JAFFE Dataset, PCA, LBP, ANN.