Abstract—This work aims to recognize the six basic emotions using facial expression and improve the classification in term of time and space memory.
We started with the idea that emotions can be absolutely distinctive and from a single feature we can recognize emotion and therefore we save time in learning data.
We also noted that the similarity between the characteristics of two emotions can cause a lot of errors.
So we concluded that it is necessary to specify the characteristics for each emotion to improve classification.
The study of various facial features (eyes, eyebrows and mouth) of each emotion has helped us to find a new use of face features and ultimately lead to a faster classification.
Index Terms—Emotion, recognition of emotions, emotion analysis, features extraction, facial expressions, face detection.
Y. Siwar is with Higher Institute of Computer Science and Multimedia of Gabes (ISIMG), Gabes, Tunisia (e-mail: yahiasiwar@yahoo.fr). E. Ridha, J. Olfa, and Z. Mourad are with Research Groups on Intelligent Machines (REGIM), University of Sfax National Engineering School of Sfax (ENIS) Tunisia (e-mail: ridha_ejbali@ieee.org, olfa.jemai@ieee.org, mourad.zaied@ieee.org).
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Cite:Y. Siwar, E. Ridha, J. Olfa, and Z. Mourad, "Improving the Classification of Emotions by Studying Facial Feature," International Journal of Computer Theory and Engineering vol. 8, no. 5, pp. 419-422, 2016.
