Open AccessOperator’s State Estimation Based on the Face’s Video Images Analysis Using Deep Convolutional Neural Networks
Author(s) -
О. Н. Корсун,
Vladimir Yurko,
E. I. Mikhaylov
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/714/1/012012
Subject(s) - convolutional neural network , operator (biology) , artificial intelligence , computer science , face (sociological concept) , task (project management) , pattern recognition (psychology) , computer vision , state (computer science) , deep learning , algorithm , engineering , social science , sociology , gene , biochemistry , chemistry , systems engineering , repressor , transcription factor
The paper deals with the problem of operator’s state estimating. For this purpose various approaches based on using deep convolutional neural networks are proposed. The approach using automatic emotion recognition methods is considered in the most detail. During the experiment video records of the operator’s face registered during operator performing the flight task on the flight simulator were processed. To determine the type of operator’s activity the studies based on using the emotional background of the face are also carried out. The experimental results of this approach confirmed the efficiency of the selected methods, especially for monitoring the operator’s state when falling asleep.