PCA + LDA Fuzzy Based Model for Emotional Nature Recognition of Human Video

Human expresses their emotions by means of verbal and nonverbal communication. Nonverbal communications are done mainly using facial expression. This paper aims to recognize human emotion using nonverbal communication of human facial expressions. Different mathematical techniques like: principle component analysis (PCA), linear discriminate analysis (LDA) and independent component analysis (ICA) are widely used for human facial expression recognition. This paper applied fusion of PCA and LDA based model for facial video emotion recognition with neural network (NN), fuzzy approach and Ekman’s proposed concept of action units of faces. Moreover, results obtained in linguistic form using action units with fuzzy approach on unknwn individual persons for identification of nature of input video and compare with the actual data to validate the model. This paper concludes that developed approach provides 99% accuracy for human facial expression recognition and identification of nature of input video.