Emotion Recognition using Open CV
P.S.R.V Aditya1, P Dinesh Sai2, Purvaja Varati3, R Rohan Singh4, Ranjitha U.N5
1P.S.R.V Aditya, School of C&IT, REVA University, India.
2P Dinesh Sai, School of C&IT, REVA University, India.
3Purvaja Varati, School of C&IT, REVA University, India.
4R Rohan Singh, School of C&IT, REVA University, India.
5Ranjitha U.N, School of C&IT, REVA University, India.
Manuscript received on 04 June 2019 | Revised Manuscript received on 12 June 2019 | Manuscript Published on 29 June 2019 | PP: 91-93 | Volume-8 Issue-5S, May 2019 | Retrieval Number: E10190585S19/19©BEIESP
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© The Authors. 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: The human face plays a pivotal role in identifying emotions, regardless of subject-independent features. For human-computer interaction, facial expressions form a platform for non-verbal communication. In this regard, a system which detects and analyses facial expressions, needs to be robust enough to account for human faces having multiple variability such as color, orientation, posture and so on. Our paper focuses on the technicalities which makes the system capable of addressing the variability associated with facial expressions. This is achieved using concepts of machine learning, deep learning and artificial intelligence. The focus extends to making human-machine interaction not only an interactive process, but also a user friendly one. The implementation makes use of a Haar Cascade Classifier, Tensor flow and open Cv.
Keywords: Facial Expressions, Haar Cascade Classifier, Machine Learning, Non-Verbal Communication, Open cv, Tensor Flow
Scope of the Article: Pattern Recognition