One of the primary causes of road accidents is related to driver inattention or drowsiness. In this paper we propose a vision-based Multi-Task Driver Monitoring Framework (MTDMF) that simultaneously analyzes head pose, eyes and mouth status, and drowsiness level of the driver. Experimental results on both frame-level and sequence-level classification show the effectiveness of the proposed framework.
Celona, L., Mammana, L., Bianco, S., Schettini, R. (2018). A multi-task CNN framework for driver face monitoring. In 2018 IEEE 8th International Conference on Consumer Electronics - Berlin (ICCE-Berlin) (pp.1-4). IEEE Computer Society [10.1109/ICCE-Berlin.2018.8576244].
A multi-task CNN framework for driver face monitoring
Celona, L
;Bianco, S;Schettini, R
2018
Abstract
One of the primary causes of road accidents is related to driver inattention or drowsiness. In this paper we propose a vision-based Multi-Task Driver Monitoring Framework (MTDMF) that simultaneously analyzes head pose, eyes and mouth status, and drowsiness level of the driver. Experimental results on both frame-level and sequence-level classification show the effectiveness of the proposed framework.
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