Automatic car detection in high resolution urban scenes based on an adaptive 3D-model

Abstract

This article introduces a new approach to automatic car detection in monocular high resolution aerial images. The extraction is based on a 3D-model that describes the prominent geometric features of cars by a wireframe representation. Furthermore, vehicle color, windshield color, and intensity of a car's shadow area are included as radiometric features. During extraction, the model automatically adapts the expected saliency of these features depending on vehicle color measured from the image and the actual illumination direction given a priori. 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 neither relies on external information like digital maps or site models, nor it is limited to one single vehicle model. Various examples illustrate the applicability of this approach. However, they also show the deficiencies which clearly define the next steps of our future work.