Abstract
The emotion recognition system has been a significant field in human-computer interaction. It is a considerably challenging field to generate an intelligent computer that is able to identify and understand human emotions for various vital purposes, e.g. security, society, entertainment. Many research studies have been carried out in order to produce an accurate and effective emotion recognition system. Emotion recognition methods can be classified into different categories along a number of dimensions: speech emotion recognition vs. facial emotion recognition; machine learning method vs. statistic method. Facial expression method can also be classified based on input data to a sequence video or static image. This report focuses on different types of human facial expressions, like different types of sad, happiness, and surprise moments. This is carried out by trying to extract unique facial expression feature among emotions using Fuzzy and the Principal Component Analysis (PCA) approach.
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Mishra, S.R., Ravikiran, B., Sudhan, K.S.M., Anudeep, N., Jagdish, G. (2014). Human Emotion Classification Using Fuzzy and PCA Approach. In: Satapathy, S., Udgata, S., Biswal, B. (eds) Proceedings of the International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2013. Advances in Intelligent Systems and Computing, vol 247. Springer, Cham. https://doi.org/10.1007/978-3-319-02931-3_10
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DOI: https://doi.org/10.1007/978-3-319-02931-3_10
Publisher Name: Springer, Cham
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