Abstract
This research aims at developing “Humanoid Robots” that can carry out intellectual conversation with human beings. The first step of our research is to recognize human emotions by a computer using neural network. In this paper all six universally recognized principal emotions namely angry, disgust, fear, happy, sad and surprise along with neutral one are recognized. Various neural networks such as Support Vector Machine (SVM), Multilayer Perceptron (MLP), Principal Component Analysis (PCA), and Generalized Feed Forward Neural Network (GFFNN) are employed and their performance is compared. 100% recognition accuracy is achieved on training data set (seen examples) and test data set (unseen examples).
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Kharat, G.U., Dudul, S.V. (2009). Emotion Recognition from Facial Expression Using Neural Networks. In: Hippe, Z.S., Kulikowski, J.L. (eds) Human-Computer Systems Interaction. Advances in Intelligent and Soft Computing, vol 60. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03202-8_17
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DOI: https://doi.org/10.1007/978-3-642-03202-8_17
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