Real-time, 3-D multi object position estimation and tracking

Abstract

For autonomously acting robots and driver assistance systems, powerful optical stereo sensor systems are required. Object positions and environmental conditions have to be acquired in real-time. A hardware-software co-design is applied, acting within the presented stereophotogrammetric system. For calculation of the depth map, an optimized algorithm is implemented as a hierarchical parallel hardware solution. By adapting the image resolution to the distance, real-time processing is possible. The object clustering and the tracking is realized in a processor. The density distribution of the disparity in the depth map (disparity histogram) is used for object detection. A Kalman filter stabilizes the parameters of the results.