{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T04:16:25Z","timestamp":1780373785478,"version":"3.54.1"},"reference-count":66,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2013,3,28]],"date-time":"2013-03-28T00:00:00Z","timestamp":1364428800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Road accident statistics from different countries show that a significant number of accidents occur due to driver\u2019s 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\u2019s 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\u2019s head and body movements. In this paper, we propose a technique that involves optical flow and driver\u2019s kinematics analysis to improve the robustness of the driver\u2019s alert state measurement under pose changes using a single camera with near-infrared illumination. The proposed approach infers and keeps track of the driver\u2019s 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.<\/jats:p>","DOI":"10.3390\/s130404225","type":"journal-article","created":{"date-parts":[[2013,3,28]],"date-time":"2013-03-28T13:35:44Z","timestamp":1364477744000},"page":"4225-4257","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Optical Flow and Driver\u2019s Kinematics Analysis for State of Alert Sensing"],"prefix":"10.3390","volume":"13","author":[{"given":"Javier","family":"Jim\u00e9nez-Pinto","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, Pontificia Universidad Cat\u00f2lica de Chile, Vicu\u00f1a Mackenna 4860, Casilla 306-22, Santiago, Chile"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Miguel","family":"Torres-Torriti","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Pontificia Universidad Cat\u00f2lica de Chile, Vicu\u00f1a Mackenna 4860, Casilla 306-22, Santiago, Chile"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2013,3,28]]},"reference":[{"key":"ref_1","unstructured":"Wolrd Health Organization Data and statistics of the World Health Organization. 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