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Driver Distraction Using Visual-Based Sensors and Algorithms.

Alberto Fernández1, Rubén Usamentiaga2, Juan Luis Carús3

  • 1Grupo TSK, Technological Scientific Park of Gijón, 33203 Gijón, Asturias, Spain. alberto.fernandez@grupotsk.com.

Sensors (Basel, Switzerland)
|November 2, 2016
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Summary

Driver distraction monitoring systems use computer vision to detect visual, biomechanical, and cognitive distractions. Combining multiple visual cues enhances system robustness for safer driving.

Keywords:
driver distraction detectionimage processingvisual-based sensors

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Area of Science:

  • Road safety
  • Human-computer interaction
  • Computer vision

Background:

  • Driver distraction is a major cause of road accidents.
  • In-vehicle information systems increase distraction risks.
  • Vision-based systems offer non-intrusive distraction monitoring.

Purpose of the Study:

  • Review computer vision techniques for driver distraction detection.
  • Highlight challenges in developing robust monitoring systems.
  • Discuss sensor development and implementation requirements.

Main Methods:

  • Utilizing video-based algorithms for distraction detection.
  • Extracting visual cues from face, hands, and body.
  • Integrating distraction detection with in-vehicle systems.

Main Results:

  • Commonly detected distractions include biomechanical, visual, and cognitive types.
  • Single-cue systems are vulnerable to occlusion and illumination changes.
  • Combining multiple visual cues is crucial for robust detection.

Conclusions:

  • Computer vision is key for advanced driver distraction monitoring.
  • Robust systems require multi-cue analysis and embedded solutions.
  • Future work should address challenges in real-time, reliable, and cost-effective implementation.