Crosswalk and traffic light detection via integral framework

This research is conducted to detect crosswalks and traffic lights with small false positive and negative errors. We propose an integral framework of the algorithms. Crosswalk and traffic light detection based on vision are challenging problem because brightness and hue value of scene can be easily changed, and it causes a number of false positive and negative errors. In order to solve it, we integrate those two algorithms with an assumption that traffic light and crosswalk exist together frequently. The proposed algorithm is tested with movies captured by cameras located on a vehicle and results are compared with ground truth which was chosen manually. The proposed algorithms run in real-time and can be easily installed on vehicle.