A miniature embedded stereo vision system for automotive applications

Dependable 3D perception modules are essential for safe operation of autonomous systems. Therefore, we present a highly compact stereo vision system that gets along without a dedicated processing platform, having the DSPs integrated in the cameras. To enable the computation of dense and accurate depth maps, we implement a Sparse Census Transform, reducing the complexity of the stereo matching procedure by a factor of four while still ensuring highly accurate results. Besides the detection of false positives, wrong matches are highly reduced due to the computation and analysis of a dedicated confidence value. Furthermore, the algorithm allows for the computation of camera images with up to 16 bit camera resolution, leading just to minor increases in computational time.