expression

Various real-time applications such as Human–Computer Interactions, Psychometric analysis, etc. use facial expressions as one of the important parameters. The researchers have used Action Units (AU) of the face as feature points and its deformation is compared with the reference points on the face to estimate the facial expressions. Among many partsof the face, features from the mouth contribute largely to all the well-known emotions. In this paper, the parabola theory is used to identify and mark various points on the lips. These points are considered as feature points to construct feature vectors. The Latus Rectum, Focal Point, Directrix, Vertex, etc. are also considered to identify the feature points of the lower lips and upper lips. The proposed approach is evaluated on benchmark datasets such as JAFFEE and Cohn–Kanade dataset and it is found that the performance is encouraging in understanding the facial expressions. The results are compared with contemporary methods and found that the proposed approach has given good classification accuracy in recognizing facial expressions. © 2020, Springer Nature B.V.