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In this paper, we introduce a new dataset, the driver emotion facialexpression (DEFE) dataset, for driver spontaneous emotions analysis. Thedataset includes facial expression recordings from 60 participants duringdriving. After watching a selected video-audio clip to elicit a specificemotion, each participant completed the driving tasks in the same drivingscenario and rated their emotional responses during the driving processes fromthe aspects of dimensional emotion and discrete emotion. We also conductedclassification experiments to recognize the scales of arousal, valence,dominance, as well as the emotion category and intensity to establish baselineresults for the proposed dataset. Besides, this paper compared and discussedthe differences in facial expressions between driving and non-drivingscenarios. The results show that there were significant differences in AUs(Action Units) presence of facial expressions between driving and non-drivingscenarios, indicating that human emotional expressions in driving scenarioswere different from other life scenarios. Therefore, publishing a human emotiondataset specifically for the driver is necessary for traffic safetyimprovement. The proposed dataset will be publicly available so thatresearchers worldwide can use it to develop and examine their driver emotionanalysis methods. To the best of our knowledge, this is currently the onlypublic driver facial expression dataset.

A Spontaneous Driver Emotion Facial Expression (DEFE) Dataset for Intelligent Vehicles