Motion-Based Object Detection for Automotive Applications using Multidimensional Wave Digital Filters

Vision-based object detection is a core part of many automotive collision warning systems. Especially due to the extensive information an image can hold and the decreasing costs of computational power, it has attracted more and more interest in the last decade. In this paper we propose a motion-based approach to simplify the detection of moving objects in order to improve available methods and make them more efficient. We interpret the image sequence containing the moving object (e.g. a vehicle or a crossing pedestrian) as a three-dimensional signal, not just as a sequence of image matrices. That way we can benefit from the advanced theoretical knowledge on system description and handling from the field of signal processing. In detail, three-dimensional velocity filters implemented using wave digital filters are used to oppress every object in the image that is not moving in a certain direction at a certain velocity.