Driver Monitoring
Overview
Driver monitoring studies how to detect states such as drowsiness, distraction, fatigue, impairment, and emotion, and how these signals can inform warnings or vehicle assistance. Methods include facial and gaze analysis, temporal video models, multimodal vision-language systems, and physiological sensing with cameras, wearables, or in-vehicle sensors. Researchers evaluate these approaches on driving datasets and benchmarks such as Drive&Act, AIDE, and DMD, while also testing real-time performance on embedded devices and in naturalistic settings. A central challenge is making systems reliable across drivers, lighting, noise, and changing road conditions without excessive false alarms or sacrificing privacy and efficiency.
Latest papers
30 papers3 papers in the last four weeks, down 40% on the four weeks before. 0.0% of all new papers.