Facial Emotion Classifier using Convolutional Neural Networks for Reaction Review

Author:

Madhavi Makarand,Gujar Isha,Jadhao Viraj,Gulwani Reshma

Abstract

Applications of facial emotion classification is gaining popularity in the world. There are many ways to train a model to classify human facial expressions by use of existing technologies. The strategy to order and recognize feelings of an individual conveyed by his facial expression is done by contrasting it to a gathered set of labelled experiences of feelings. In this paper, we propose the making of an intelligent system that will recognize and classify facial emotions. A multi-layer Convolutional Neural Network model is proposed. Another method of training using pretrained ResNet50 Model is explored. A basic live video streaming application is developed to showcase the use case of our model which will be capable of monitoring and recording facial emotions in real time from a live video stream and subsequently summarize the overall reactions at the end of the stream.

Publisher

EDP Sciences

Subject

General Medicine

Reference25 articles.

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3. Deng Zhiwei, Navarathna Rajitha, Carr Peter, Mandt Stephan, Yue Yisong, Matthews Iain, “Factorized Variational Auto encoders for Modelling Audience Reactions to Movies”, Greg Mori Simon Fraser University, Disney Research, Caltech.

4. Khandait S.P., Dr. Thool R.C. & Khandait P.D., “Automatic Facial Feature Extraction and Expression Recognition based on Neural Network”, (IJACSA) International Journal of Advanced Computer Science and Applications. 2, No.1, January 2011.

5. Arriaga Octavio, Ploger Paul G., Valdenegro Matias, “Real-time Convolutional Neural Networks for Emotion and Gender Classification”.

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