Detection of Fatigued Face

For some large and complex operating platforms in machinery factories, in order to detect fatigued workers in time, machine vision is adopted for fatigue detection. Normal camera cannot cover the entire working range. So come up with an idea to use an industrial computer to control the pan-tilt for face tracking and fatigue detection. First, face detection is performed on the image information captured by the pan-tilt. Then, the pan-tilt is controlled to rotate according to the position of the face to achieve the purpose of tracking the face of the staff in real time. On this basis, the feature points recognized by face detection algorithm and the PERCLOS algorithm are used to calculate, The thresholds of EAR value and MAR value were set as 0.18 and 0.4 respectively according to the experimental results to identify the fatigue features of the face for fatigue detection. Finally, whether the person is in a state of fatigue is judged according to whether the percentage of the time that the person is in a fatigue characteristic exceeds 75% .The results show that the corresponding hardware equipment and the algorithm used can make the recognition accuracy basically reach 90% during working time, and the detection time is less than 90ms, which satisfy the requirements of real-time face tracking and fatigue detection accuracy and execution efficiency under working state.