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Sensors 2013, 13(4), 4225-4257; doi:10.3390/s130404225

Optical Flow and Driver’s Kinematics Analysis for State of Alert Sensing

Department of Electrical Engineering, Pontificia Universidad Catòlica de Chile, Vicuña Mackenna 4860, Casilla 306-22, Santiago, Chile
* Author to whom correspondence should be addressed.
Received: 30 January 2013 / Revised: 16 February 2013 / Accepted: 19 February 2013 / Published: 28 March 2013
(This article belongs to the Special Issue New Trends towards Automatic Vehicle Control and Perception Systems)
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Road accident statistics from different countries show that a significant number of accidents occur due to driver’s fatigue and lack of awareness to traffic conditions. In particular, about 60% of the accidents in which long haul truck and bus drivers are involved are attributed to drowsiness and fatigue. It is thus fundamental to improve non-invasive systems for sensing a driver’s state of alert. One of the main challenges to correctly resolve the state of alert is measuring the percentage of eyelid closure over time (PERCLOS), despite the driver’s head and body movements. In this paper, we propose a technique that involves optical flow and driver’s kinematics analysis to improve the robustness of the driver’s alert state measurement under pose changes using a single camera with near-infrared illumination. The proposed approach infers and keeps track of the driver’s pose in 3D space in order to ensure that eyes can be located correctly, even after periods of partial occlusion, for example, when the driver stares away from the camera. Our experiments show the effectiveness of the approach with a correct eyes detection rate of 99.41%, on average. The results obtained with the proposed approach in an experiment involving fifteen persons under different levels of sleep deprivation also confirm the discriminability of the fatigue levels. In addition to the measurement of fatigue and drowsiness, the pose tracking capability of the proposed approach has potential applications in distraction assessment and alerting of machine operators.
Keywords: fatigue detection; alert state sensing; driver assistance; head tracking; PERCLOS; driver’s kinematics fatigue detection; alert state sensing; driver assistance; head tracking; PERCLOS; driver’s kinematics
This is an open access article distributed under the Creative Commons Attribution License (CC BY) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Jiménez-Pinto, J.; Torres-Torriti, M. Optical Flow and Driver’s Kinematics Analysis for State of Alert Sensing. Sensors 2013, 13, 4225-4257.

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