Hierarchical scene understanding for intelligent vehicles

One of the main tasks of intelligent vehicles is the extraction of information from the vehicle´s surroundings and the understanding of the extracted information. The understanding of the environment allows the vehicle to drive autonomously or to support the driver in difficult or dangerous situations. In this paper we propose a vision-based hierarchical interpretation approach. First, we consider one single physical camera as a set of virtual sensors, where each virtual sensor gathers a type of 3d information. Then, the 3d information of this set is converted to high-level information that allows further reasoning. The interpretation is based on a hierarchical scene representation, where objects are recognized using nonparametric belief propagation. To demonstrate this approach we adopted the scene understanding to a parking spot finding application and show that it is real-time applicable and reliable even for multiple camera (on-board) systems.