FACIAL EXPRESSION RECOGNITION WITH LOCAL BINARY PATTERN IN MACHINE LEARNING: A REVIEW

Abstract

Automatically analyzing facial expressions is an intriguing and challenging problem which has significant applications in numerous fields, including data-driven animation and human–computer interaction. An essential step in successfully recognizing facial expressions is obtaining an accurate facial representation from original face image. For person-independent facial expression recognition, in this paper we have local feature- based facial representation and local binary patterns (LBP) techniques. On a number of databases, comprehensive analysis has been presented on various machine-learning techniques for facial recognition. LBP Feature extraction technique has been demonstrated to recognize facial expressions. Further, to extract the most discriminating local binary pattern features a boosted- LBP feature with support vector machine classifiers has been suggested which results in best face recognition performance accuracy. Additionally, we have described the investigations of low-resolution facial expression recognition with LBP feature extraction which is a crucial issue which have not received earlier consideration.