Facial expression classification using Support Vector Machine based on bidirectional Local Binary Pattern Histogram feature descriptor
Talele Kiran, Tuckley Kushal · 2016
In this paper, two class emotion detection and multi class facial expression classification using Support Vector Machine (SVM) is presented. Facial feature vectors in dual form are obtained using Local Binary Pattern (LBP) Histogram by tracing the bins in clockwise and anticlockwise direction. The Histogram feature descriptors are calculated from LBP images in dual form which are then concatenated to obtain features of complete face image. The proposed algorithm is tested using standard Japanese Female Facial Expression Database and Taiwanese facial Expression Database and results are verified using locally developed Indian face database of students. The proposed algorithm significantly outperforms the classical LBP based algorithms.