This paper presents a silicon retina-based stereo vision system, which is used for a pre-crash warning application for side impacts. We use silicon retina imagers for this task, because the advantages of the camera, derived from the human vision system, are high temporal resolution up to 1ms and the handling of various lighting conditions with a dynamic range of ~120dB. A silicon retina delivers asynchronous data which are called address events (AE). Different stereo matching algorithms are available, but these algorithms normally work with full frame images. In this paper we evaluate how the AE data from the silicon retina sensors must be adapted to work with full-frame area-based and feature-based stereo matching algorithms.