Abstract
As defined by some theorists, human emotions are discrete and consistent responses to internal or external events which have significance for an organism. They constitute a major part of our non-verbal communication. Among the human emotions, happy, sad, fear, anger, surprise, disgust and neutral are the seven basic emotions. Facial expressions are the best way to exhibit emotions. In this era of booming human-computer interaction, enabling the machines to recognize these emotions is a paramount task. There is an amalgamation of emotions in every facial expression. In this paper, we identified the different emotions and their intensity level in a human face by implementing deep learning approach through our proposed Convolution Neural Network (CNN). The architecture and the algorithm here yield appreciable results that can be used as a motivation for further research in computer based emotion recognition system.
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Mishra, S., Prasada, G.R.B., Kumar, R.K., Sanyal, G. (2017). Emotion Recognition Through Facial Gestures - A Deep Learning Approach. In: Ghosh, A., Pal, R., Prasath, R. (eds) Mining Intelligence and Knowledge Exploration. MIKE 2017. Lecture Notes in Computer Science(), vol 10682. Springer, Cham. https://doi.org/10.1007/978-3-319-71928-3_2
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DOI: https://doi.org/10.1007/978-3-319-71928-3_2
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