This project aims to automatically control the headlights of automobiles using sensors such as camera. Specifically, by analyzing the videos captured at real-time using a forward-facing camera mounted on the windshield, we attempt to develop a system that can automatically control the switch between high beam and low beam during nighttime drive by detecting headlight, taillight and street light, so as to increase the road safetly.
The core part of the project lies in image and video content analysis and machine learning. Both SVM (support vector machine) and AdaBoost learning approaches have been explored.
Members: Ying Li, Norm Haas, Jonathan Connell, Sharath Pankanti