Research on a fatigue emotion state analysis method for infrared

Computer vision-based methods can detect fatigue through eye movement and mouth state analysis. Due to the accuracy, real-time, non-invasive and low cost of image vision methods, the method of recognizing specific facial images has been proved to be the most industrialized technology at present. However, when people are tired driving, factors such as external light, head posture and facial changes still bring many challenges to human fatigue detection. The most important part of fatigue driving detection is face detection, feature extraction and classification recognition. This paper mainly studies the key problems of extracting facial features based on CNN network and infering fatigue state in real vehicle operating environment by LSTM network. The experimental results show that the proposed method has high performance and can be further applied to practical scenarios.