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Vision-Based Driver’s Attention Monitoring System for Smart Vehicles

  • Lamia Alam
  • Mohammed Moshiul HoqueEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 866)

Abstract

Recent studies revealed that the driver’s inattention is one of the most prominent reasons for car accidents. Intelligent driving assistant system with real time monitoring of the driver’s attentional status may reduce the accident rate that mostly occurred due to lack of attention. In this paper, we presents a vision-based driver’s attention monitoring system that estimates the driver’s attentional status in terms of four categories: attentive, distracted, drowsy, and fatigue respectively. The attentional status is classified with a variety of parameters such as, percentage of eyelid closure over time (PERCLOS), yawn frequency and gaze direction. Experimental results with different subjects show that the system can classify the driver’s attentional status with a reasonable accuracy.

Keywords

Computer vision Human computer interaction Attentional status Yawn frequency Gaze direction 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computer Science & EngineeringChittagong University of Engineering & TechnologyChittagongBangladesh

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