Research on Methods for Processing Large-Baseline Stereo Camera Data for Long Range 3D Environmental Perception

Depth perception and 3D object recognition with stereo cameras has a variety of applications. For example, the technology enables to sense ob-jects and possible dangers on automated cars using passive and cheap sen-sors. However, sensing range corresponds to camera baseline, and rigid camera mounting is only available to rather small baseline setups. Thus, typical systems do not exceed sensing ranges of around 50m. To enable higher ranges with baselines of about 1-2m on moving and vibrating plat-forms, non-rigidity of the setup (i.e. a variable relative camera orientation) must be considered. Hence, calibration and depth image processing must be extended with re-calibration with every stereo pair along the image se-quence. Ideally, this re-calibration works in real-time and on arbitrary im-age sequences, however this must still be evaluated.