A Novel Algorithm for Vehicle Detection and Tracking in Airborne Videos

Real time detection and tracking of multi vehicles in airborne videos is still a challenging problem due to the camera motion and low resolution. In this paper, a real time technique for simultaneously detecting, tracking and counting vehicles in airborne and stationary camera videos is proposed. First, feature points are extracted and tracked through video frames. A new strategy is used for removing the non-stationary background points by measuring the changes in the histogram of the pixels around each feature point with time. The obtained foreground features are clustered and grouped into separate trackable vehicles based on their motion properties. Experimental results performed on videos representing airborne and fixed cameras confirm the excellent properties of the proposed algorithm.