Facial Expression Recognition Using Principal Component Analysis
Ajit P. Gosavi1, S. R. Khot2

1Ajit P. Gosavi, Electronics and Telecommunication Department, S.S.P.M. college of Engineering, Kankavali, India.
2Professor S.R.Khot, Information Technology Department, D.Y. Patil college of Engineering and Technology, Kasaba Bawada, Kolhapur, India.
Manuscript received on August 08, 2013. | Revised Manuscript received on August 29, 2013. | Manuscript published on September 05, 2013. | PP: 258-262 | Volume-3, Issue-4, September 2013. | Retrieval Number: D1824093413/2013©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Expression detection is useful as a non-invasive method of lie detection and behaviour prediction. However, these facial expressions may be difficult to detect to the untrained eye. In this paper we implements facial expression recognition techniques using Principal Component analysis (PCA). Experiments are performed using standard database like Japanese Female Facial Expression (JAFFE) database. The universally accepted six principal emotions to be recognized are: Angry, Happy, Sad, Disgust, Fear and Surprise along with neutral. Euclidean distance based matching Classifier is used.
Keywords: Facial Expression Detection, Feature Extraction Japanese Female Facial Expression (JAFFE) database, Principal Component Analysis (PCA).