Monocular Vision-Based Target Detection on Dynamic Transport Infrastructures

This paper describes a target detection system on transport infrastructures, based on monocular vision. The goal is to detect and track vehicles and pedestrians, dealing with objects variability, different illumination conditions, shadows, occlusions and rotations. A background subtraction method, based on GMM and shadow detection algorithms are proposed to do the segmentation of the image. Finally a feature extraction, optical flow analysis and clustering methods are used for the tracking step. The algorithm requires no object model and prior knowledge and it is robust to illumination changes and shadows.