Open AccessEmotion Recognition using Feed Forward Neural Network & Naïve Bayes
Author(s) -
Mr .Rahul Mahadeo Shahane*,
Ramakrishna Sharma .K,
Md. Seemab Siddeeq
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.b7070.129219
Subject(s) - computer science , face (sociological concept) , feeling , negative emotion , emotion classification , facial recognition system , pixel , emotion recognition , artificial intelligence , naive bayes classifier , speech recognition , psychology , pattern recognition (psychology) , social psychology , support vector machine , social science , sociology
In this paper we analyze and predict the emotion of a user by recognizing his/her face. Face recognition is a software application which is used to identify a particular person; it will be mostly useful in security applications to secure our data. Now a day we are using face unlock in mobiles to unlock our phones. We need to know the emotions of a person in some situations. Though we can recognize his emotion through his tone of voice, it would be more helpful if get to know his emotions. This can be much helpful in finding out a criminal by finding out his emotion whether he is feeling nervous or not which expresses his/her fear by this. In order to analyze his/her emotion firstly we need to recognize his/her face, so we need to use face recognition method and then implement emotion analysis. Here we use different algorithms to implement emotion analysis such as CNN. We will have the dataset with pixels and emotion this will be the training data. Then we will be initially taking the picture and then convert them to pixels these will be acting as the testing data. We then use an algorithm to predict these pixels emotion which is nothing but predicting the emotion of the picture taken