Recognizing Human Emotional State Based on the 2D-FrFT and FLDA

Computer recognition of human emotional states is an important component for efficient human-computer interaction. In this paper we explore an approach for recognition of human emotion from the visual information. We perform feature selection by using the two dimensions fractional Fourier transform. As a generalization of Fourier transform, the two dimensions fractional Fourier transform (2D-FrFT) contains simultaneity the time-frequency information of the signal, and is considered as a new tool for time-frequency analysis, especially in the area of image recognition. In this paper we use the amplitude of the 2D-FrFT of an image as the feature of the images to train the FLDA multiclassifier for human emotion recognition. Simulation result shows that this method of the features extraction and classifier has high recognition rate.