STRESS DETECTION BASED ON EMOTION RECOGNITION  USING DEEP LEARNING

STRESS DETECTION BASED ON EMOTION RECOGNITION USING DEEP LEARNING
Author(s):
Anjali R, J. Babitha, Rithika W
Keywords:
Facial Emotion Recognition, Convolutional Neural Network , Deep Convolutional Neural Network
Abstract
Automatic emotion recognition based on facial expression is an interesting research field, which has presented and applied in several areas. Also, Machine learning and deep learning algorithms have gained great success in different applications such as classification systems, recommendation systems, pattern recognition etc. Human face conveys many information including age, gender, identity, personality, emotions, etc. Emotion recognition refers to identifying human emotions typically from facial expressions. This project aims to develop a facial emotion recognition system to identify whether the person is stressed or not. To classify the emotion on a person’s face, use a deep convolutional neural network. Dataset having 7 facial expressions is used to train the CNN network. This work is a real time application, in which facial emotion can be detected in live video stream. To detect faces in each frames in the webcam, Haarcascade technique is used.
Article Details
Unique Paper ID: 154242 Publication Volume & Issue: Volume 8, Issue 7 Page(s): 109 - 114
Article Preview & Download

Share This Article

NCSST-2021

AICTE Sponsored National Conference on Smart Systems and Technologies

Last Date: 25th November 2021

LATEST INNOVATION’S AND FUTURE TRENDS IN MANAGEMENT

Last Date: 7th November 2021