Look at the Driver, Look at the Road: No Distraction! No Accident!

Mahdi Rezaei, Reinhard Klette; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014, pp. 129-136

Abstract


The paper proposes an advanced driver-assistance system that correlates the driver's head pose to road hazards by analyzing both simultaneously. In particular, we aim at the prevention of rear-end crashes due to driver fatigue or distraction. We contribute by three novel ideas: Asymmetric appearance-modeling, 2D to 3D pose estimation enhanced by the introduced Fermat-point transform, and adaptation of Global Haar (GHaar) classifiers for vehicle detection under challenging lighting conditions. The system defines the driver's direction of attention (in 6 degrees of freedom), yawning and head-nodding detection, as well as vehicle detection, and distance estimation. Having both road and driver's behaviour information, and implementing a fuzzy fusion system, we develop an integrated framework to cover all of the above subjects. We provide real-time performance analysis for real-world driving scenarios.

Related Material


[pdf]
[bibtex]
@InProceedings{Rezaei_2014_CVPR,
author = {Rezaei, Mahdi and Klette, Reinhard},
title = {Look at the Driver, Look at the Road: No Distraction! No Accident!},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2014}
}