TY - JOUR
T1 - Real time facial expression recognition system based on deep learning
AU - Bustamante, Jose Carlos
AU - Rodriguez, Ciro
AU - Esenarro, Doris
N1 - Publisher Copyright:
©BEIESP.
PY - 2019/9
Y1 - 2019/9
N2 - 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..
AB - 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..
KW - Affective Computing
KW - Convolutional Neural Networks
KW - Deep Learning
KW - Emotion Classification
KW - Facial Expression Recognition System
KW - Real Time
UR - http://www.scopus.com/inward/record.url?scp=85074388632&partnerID=8YFLogxK
U2 - 10.35940/ijrte.B1591.0982S1119
DO - 10.35940/ijrte.B1591.0982S1119
M3 - Artículo
AN - SCOPUS:85074388632
SN - 2277-3878
VL - 8
SP - 4047
EP - 4051
JO - International Journal of Recent Technology and Engineering
JF - International Journal of Recent Technology and Engineering
IS - 2 Special Issue 11
ER -