A decision-theoretic generalization of on-line learning and an application to boosting
EuroCOLT '95 Proceedings of the Second European Conference on Computational Learning Theory
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
On Importance of Nose for Face Tracking
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Robust Real-Time Face Detection
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Emblem Detections by Tracking Facial Features
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Robust Pose Invariant Facial Feature Detection and Tracking in Real-Time
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Real-Time Multi-View Face Detection and Pose Estimation in Video Stream
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
Real-time eye blink detection with GPU-based SIFT tracking
CRV '07 Proceedings of the Fourth Canadian Conference on Computer and Robot Vision
Hi-index | 0.00 |
This paper describes current research combining computer vision, virtual reality and kinesiology for analyzing the cephalo-ocular behavior of drivers in realistic driving contexts. The different components of the system are described and results are provided for each one. The ultimate goal of the system is to achieve automatic analysis of drivers' behavior in order to design training programs tailored to their driving habits.