Real-time stereo vision on a reconfigurable system

Abstract

Real-time three-dimensional vision would support various applications including a passive system for collision avoidance. It is a good alternative of active systems, which are subject to interference in noisy environments. In this paper, we investigate the optimization of real-time stereo vision with respect to resource usage. Correlation techniques using a simple sum of absolute differences(SAD) is popular having good performance. However, processing even a small image takes seconds. In order to provide depth maps at frame rate around 30fps, which typical cameras can provide, hardware accelerations are necessary. Regular structures, linear data flow and abundant parallelism make the correlation algorithm a good candidate for reconfigurable hardware. We implemented versions of SAD algorithms in VHDL and synthesized them to determine resource requirements and performance. By decomposing a SAD correlator into column SAD calculator and row SAD calculator with buffers in between we showed around 50% savings in resource usage. By altering the shape of correlation windows we found that a 'short and wide' rectangular window reduced storage requirements without sacrificing quality compared to a square one.