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Real Time Facial Emotion Recognition based on Image Processing and Machine Learning

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Rituparna Halder, Sushmit Sengupta, Arnab Pal, Sudipta Ghosh, Debashish Kundu
10.5120/ijca2016908707

Rituparna Halder, Sushmit Sengupta, Arnab Pal, Sudipta Ghosh and Debashish Kundu. Article: Real Time Facial Emotion Recognition based on Image Processing and Machine Learning. International Journal of Computer Applications 139(11):16-19, April 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Rituparna Halder and Sushmit Sengupta and Arnab Pal and Sudipta Ghosh and Debashish Kundu},
	title = {Article: Real Time Facial Emotion Recognition based on Image Processing and Machine Learning},
	journal = {International Journal of Computer Applications},
	year = {2016},
	volume = {139},
	number = {11},
	pages = {16-19},
	month = {April},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

Behaviors, actions, poses, facial expressions and speech; these are considered as channels that convey human emotions. Extensive research has being carried out to explore the relationships between these channels and emotions. This paper proposes a prototype system which automatically recognizes the emotion represented on a face. Thus a neural network based solution combined with image processing is used in classifying the universal emotions: Happiness, Sadness, Anger, Disgust, Surprise and Fear. Colored frontal face images are given as input to the prototype system. After the face is detected, image processing based feature point extraction method is used to extract a set of selected feature points. Finally, a set of values obtained after processing those extracted feature points are given as input to the neural network to recognize the emotion contained.

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Keywords

Image Processing, Facial Expression, Machine Learning, Python Programming, OpenCV