A LBP and SVM Based Face Expression Classification System

Abstract

This work presents support vector machine (SVM)-based emotion detection and multi-class facial expression categorization. By traversing each bin in both a clockwise and an anticlockwise orientation, the Local Binary Pattern (LBP) Histogram can be used to generate facial feature vectors in double format. The LBP pictures in double format are used to determine the Histogram feature descriptors, which are then combined to produce the features of the full-face image. The suggested algorithm is evaluated using the conventional Japanese Female Facial Expression Database (JFFED) and the Taiwanese facial expression database, and the outcomes are confirmed using a locally created student face database in India. The suggested algorithm functions noticeably better than traditional LBP-based techniques.