Eye Localization During Driving

In my research, I have independently developed a program specifically designed for detecting and localizing drivers' eye positions during vehicle operation. The implementation utilizes MATLAB's Image Processing Toolbox and Computer Vision System Toolbox to create a robust eye detection system. The core algorithm employs Haar-like feature cascades combined with template matching techniques to accurately identify eye regions in varying lighting conditions and head orientations. Through this program, I have successfully collected extensive datasets that facilitate deeper analysis of drivers' attention patterns and reaction capabilities during driving tasks. The system processes video frames in real-time, extracting eye movement metrics including gaze direction, blink rate, and pupil dilation measurements. I am currently working on integrating this program with additional hardware devices such as infrared cameras and steering angle sensors to create a comprehensive driver monitoring system. Future enhancements will incorporate machine learning classifiers to improve detection accuracy and enable predictive analytics for driver fatigue assessment. The code architecture modularizes key functions including image preprocessing, region-of-interest detection, and coordinate transformation for multi-camera setups.