Facial expression recognition based on Local Binary Patterns

Extraction methods of facial expression characteristics have disadvantages according to Classical LBP such as complexity and high dimensions of feature vectors that make it necessary to apply dimension reduction processes. In this paper, we introduce an improved LBP algorithm to solve these problems that utilizes Fast PCA algorithm for reduction of vector dimensions of extracted features. In other words, proffer method (Fast PCAⰓ) is an improved LBP algorithm that is extracted from classical LBP operator. In this method, first circular neighbor operator is used for features extraction of facial expression. Then, an algorithm of Fast PCA is used for reduction of feature vector dimensions. Simulation results show that the proposed method in this paper in terms of accuracy and speed of recognition, has had a better performance compared with the same algorithm.