Car Detection in Aerial Images of Dense Urban Areas

With the ever-increasing demand in the analysis and understanding of aerial images in order to remotely recognize targets, this paper introduces a robust system for the detection and localization of cars in images captured by air vehicles and satellites. The system adopts a sliding-window approach. It compromises a window-evaluation and a window-classification subsystems. The performance of the proposed framework was evaluated on the Vaihingen dataset. Results demonstrate its superiority to the state of the art.