A realization of semi-global matching stereo algorithm on GPU for real-time application

Abstract

Real-time stereo vision systems have many applications such as automotive and robotics. According to the Middlebury Stereo Database, Semi-Global Matching (SGM) is commonly regarded as the most efficient algorithm among the top-performing stereo algorithms. Recently, most effective real-time implementations of this algorithm are based on reconfigurable hardware (FPGA). However, with the development of General-Purpose computation on Graphics Processing Unit, an effective real-time implementation on general purpose PCs can be expected. In this paper, a real-time SGM realization on Graphics Processing Unit (GPU) is introduced. CUDA, a general purpose parallel computing architecture introduced by NVIDIA in November 2006, has been used to realize the algorithm. Some important optimizations according to CUDA and Fermi (the latest architecture of NVIDA GPUs) are also introduced in this paper.