Discrimination of moderate and acute drowsiness based on spontaneous facial expressions

Vural, Esra and Bartlett, Marian and Littlewort, Gwen and Çetin, Müjdat and Erçil, Aytül and Movellan, Javier (2010) Discrimination of moderate and acute drowsiness based on spontaneous facial expressions. In: 20th International Conference on Pattern Recognition (ICPR), Istanbul, Turkey

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It is important for drowsiness detection systems to identify different levels of drowsiness and respond appropriately at each level. This study explores how to discriminate moderate from acute drowsiness by applying computer vision techniques to the human face. In our previous study, spontaneous facial expressions measured through computer vision techniques were used as an indicator to discriminate alert from acutely drowsy episodes. In this study we are exploring which facial muscle movements are predictive of moderate and acute drowsiness. The effect of temporal dynamics of action units on prediction performances is explored by capturing temporal dynamics using an overcomplete representation of temporal Gabor Filters. In the final system we perform feature selection to build a classifier that can discriminate moderate drowsy from acute drowsy episodes. The system achieves a classification rate of .96 A’ in discriminating moderately drowsy versus acutely drowsy episodes. Moreover the study reveals new information in facial behavior occurring during different stages of drowsiness.
Item Type: Papers in Conference Proceedings
Uncontrolled Keywords: Facial Expression Recognition , Moderate versus Acute Drowsiness Detection , Temporal Dynamics
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Electronics
Faculty of Engineering and Natural Sciences
Depositing User: Aytül Erçil
Date Deposited: 25 Oct 2010 16:40
Last Modified: 26 Apr 2022 08:57
URI: https://research.sabanciuniv.edu/id/eprint/14818

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