疲劳驾驶人脸视频数据集

we collect a video dataset of 17 drivers containing fatigue state or non-fatigue state (The dataset is available at https://github.com/ChenDelong1999/DriverFatigueDetection, where the videos of fatigue state is collected when the drivers have sufficient sleeping, while non-fatigue state videos are collected under sleep deprivation condition. Each video lasts about 100 seconds. We use a 300-frame sliding-window and a stride of 5 frames to collect training and testing samples. Each sample consists of 300 video frames and a label indicating the corresponding fatigue state. The samples are divided into a training set and a testing set whose sizes are respectively 13,402 and 7,332.

Fan Liu*, Delong Chen (本科生), et al. A Review of Driver Fatigue Detection and Its Advances on the Use of RGB-D Camera and Deep Learning. Engineering Applications of Artificial Intelligence, EAAI, 2022. (SCI, JCR一区, IF: 7.802).

数据集主页： https://github.com/ChenDelong1999/DriverFatigueDetection