Facial expression pair matching

In this study, facial expression recognition is defined as a pair matching problem. Our objectives to formulate this talk in this way are to be able to decide whether the facial expressions of the unlabeled images of two people are the same or different and to benefit from the proposed pair matching methods that have been studied for many years in the face recognition field. The Extended Cohn-Kanade (CK+) dataset which is commonly used for classification of facial expression is chosen to obtain match and mismatch pairs. To provide a baseline approach for the proposed pair matching formulation, in our paper, feature extraction by using local binary pattern is applied and match and mismatch facial expressions are classified by using support vector machines. 99.28% matching accuracy was achieved.