Frontalization and adaptive exponential ensemble rule for deep-learning-based facial expression recognition system

2021 ◽  
pp. 116321
Author(s):  
Kai-Yuan Tsai ◽  
Yi-Wei Tsai ◽  
Yih-Cherng Lee ◽  
Jian-Jiun Ding ◽  
Ronald Y. Chang
Keyword(s):  
Deep Learning ◽  
Facial Expression ◽  
Facial Expression Recognition ◽  
Recognition System ◽  
Expression Recognition

scholarly journals Real Time Facial Expression Recognition System Based on Deep Learning

2019 ◽  
Vol 8 (2S11) ◽  
pp. 4047-4051
Keyword(s):  
Deep Learning ◽  
Facial Expression ◽  
Real Time ◽  
Facial Expression Recognition ◽  
Recognition System ◽  
Expression Recognition ◽  
Or Education ◽  
Face Expression ◽  
Active Research ◽  
Main Components

The automatic detection of facial expressions is an active research topic, since its wide fields of applications in human-computer interaction, games, security or education. However, the latest studies have been made in controlled laboratory environments, which is not according to real world scenarios. For that reason, a real time Facial Expression Recognition System (FERS) is proposed in this paper, in which a deep learning approach is applied to enhance the detection of six basic emotions: happiness, sadness, anger, disgust, fear and surprise in a real-time video streaming. This system is composed of three main components: face detection, face preparation and face expression classification. The results of proposed FERS achieve a 65% of accuracy, trained over 35558 face images..

A facial expression recognition system using robust face features from depth videos and deep learning

2017 ◽  
Vol 63 ◽  
pp. 114-125 ◽  
Author(s):  
Md. Zia Uddin ◽  
Mohammed Mehedi Hassan ◽  
Ahmad Almogren ◽  
Mansour Zuair ◽  
Giancarlo Fortino ◽  
...  
Keyword(s):  
Deep Learning ◽  
Facial Expression ◽  
Facial Expression Recognition ◽  
Recognition System ◽  
Expression Recognition ◽  
Face Features

CNN Based Facial Expression Recognition System Using Deep Learning Approach

2021 ◽  
pp. 391-405
Author(s):  
Hitesh Kumar Sharma ◽  
Tanupriya Choudhury ◽  
Adarsh Kandwal ◽  
Anurag Mor ◽  
Preeti Sharma ◽  
...  
Keyword(s):  
Deep Learning ◽  
Facial Expression ◽  
Facial Expression Recognition ◽  
Recognition System ◽  
Learning Approach ◽  
Expression Recognition

A Survey on Various Deep Learning Algorithms for an Efficient Facial Expression Recognition System

2021 ◽  
Author(s):  
Rudranath Banerjee ◽  
Sourav De ◽  
Shouvik Dey
Keyword(s):  
Deep Learning ◽  
Facial Expression ◽  
Facial Expression Recognition ◽  
Physical State ◽  
Feature Learning ◽  
Recognition System ◽  
Processing Technique ◽  
Research Field ◽  
Expression Recognition ◽  
Extraction Algorithm

Facial Expression (FE) encompasses information concerning the emotional together with the physical state of a human. In the last few years, FE Recognition (FER) has turned out to be a propitious research field. FER is the chief processing technique for non-verbal intentions, and also it is a significant and propitious computer vision together with the artificial intelligence field. As a novel machine learning theory, Deep Learning (DL) not only highlights the depth of the learning model but also emphasizes the significance of Feature Learning (FL) for the network model, and it has made several research achievements in FER. Here, the present research states are examined typically from the latest FE extraction algorithm as well as the FER centered on DL. The research on classifiers gathered from recent papers discloses a more powerful as well as reliable comprehending of the peculiar traits of classifiers for research fellows. At the ending of the survey, few problems in addition to chances that are required to be tackled in the upcoming future are presented.

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