Facial expressions are an important form of communication as they help us determine the person’s mood and intentions. Facial emotions are helpful for communicating with the other person without using words. There are a few terms which are highly common and often used, they are: Happiness, sad, angry, hatred, scare, surprise also neutral. It is vital that we detect and catch these features in the person’s face as they play a key role in Computer vision and Artificial Intelligence. The main objective of human emotion recognition is to evaluate the human emotions. The features of this technology are myriad, they can be of use in various fields in security systems, or while taking feedback of an interview or human robot interaction. In view of this the emotion exposure has been handled in both actual and fixed images. We have used the Cohn-Kannade Catalog (CK) which has some fixed images 640 x 400 pixels and for the actual-time, footage has been used. Extremely, for emotion perception, we essential detect the faces by via HAAR mesh from Open CV in the fixed images and in the actual videos. Once we identify the face, it can be treated and scratch spread through detection of facial landmarks. Using Support Vector Machine, we get exactness of around 93.7%. These facemask standards can be improved for better efficiency.
Volume 12 | Issue 2
Pages: 916-922
DOI: 10.5373/JARDCS/V12I2/S20201115