In recent times, the interaction between human beings and computers has become an increasing field of research due to its wide application of computational systems. Determination of the current state of human psychological problems, one of the most relevant techniques is emotion recognition. The dynamic behavior of human is crucial for its interpretation. So, Facial emotion recognition (FER) is an important research area for detection the of different facial emotions. In this paper, we proposed an Unconstrained Minimum Average Correlation Energy (UMACE) filter as a classifier for facial emotion recognition. We are applying this proposed method in the CK+ database and it can give a better recognition rate.
Topics
Correlation energy
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