Detection and counting of cars in aerial images

This paper introduces a new approach to automatic car detection in monocular large scale aerial images. The extraction is based on a hierarchical 3D-model that describes the prominent geometric features of cars or different levels of detail. Furthermore, vehicle color, windshield color, and intensity of a car\´s shadow area are included as radiometric features. The model automatically adapts the expected saliency of different features depending on vehicle color and the current illumination direction which are measured from the image during extraction or given a priori, respectively. Car extraction is carried out by matching the model "top-down" to the image and evaluating the support found in the image. In contrast to most of the related work, our approach does not rely on external information like digital maps or site models. Various examples illustrate the applicability of this approach. However, they also show the deficiencies which clearly define the next steps of our future work.