Efficient Real-Time Algorithms for Eye State and Head Pose Tracking in Advanced Driver Support Systems
Abstract
This article shows cutting-edge computer vision methods employed in advanced vision sensing technologies for medical, safety and security applications, where the human eye represents the object of interest for both the imager and the computer. As the eye scans the environment, or focuses on particular objects in the scene, the processor simultaneously localizes the eye position, tracks its position and movement over time, and infers counter measures such as fatigue level, attention level, and gaze direction in real-time and automatically. The focus of this demonstration is placed on four different algorithms: auto-initialization (RHED), eye position tracking (SIRAT), eye closure recognition (HRA), driver head pose categorization.
Cite
Text
Hammoud et al. "Efficient Real-Time Algorithms for Eye State and Head Pose Tracking in Advanced Driver Support Systems." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2005. doi:10.1109/CVPR.2005.142Markdown
[Hammoud et al. "Efficient Real-Time Algorithms for Eye State and Head Pose Tracking in Advanced Driver Support Systems." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2005.](https://mlanthology.org/cvpr/2005/hammoud2005cvpr-efficient/) doi:10.1109/CVPR.2005.142BibTeX
@inproceedings{hammoud2005cvpr-efficient,
title = {{Efficient Real-Time Algorithms for Eye State and Head Pose Tracking in Advanced Driver Support Systems}},
author = {Hammoud, Riad I. and Wilhelm, Andrew and Malawey, Phillip and Witt, Gerald J.},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2005},
pages = {1181},
doi = {10.1109/CVPR.2005.142},
url = {https://mlanthology.org/cvpr/2005/hammoud2005cvpr-efficient/}
}