Facial expressions recognition using an ensemble of feature sets based on key-point descriptors

摘要

The authors in this study proposed facial expression recognition system in order to improve the expression recognition performance over the recently proposed systems. Feature sets for all training samples are constructed based on speed up robust feature descriptors. An ensemble of feature sets is then created incrementally. To achieve high diversity of ensemble, the dissimilarities between the training samples for each class are computed. This high diversity led to a high recognition rate. Experimentation on two publicly available datasets is performed. The system achieved 98.6% accuracy on JAFFE dataset and 96.3% accuracy on Multimedia Understanding Group dataset. The results of proposed system are compared with recently proposed work in this area and proved the soundness of the proposed method.