The trinocular stereo vision system could overcome the occlusion problem of the binocular stereo vision system. The measurement accuracy of the stereo vision system can be further improved. However, the large number of sensors may lead to the high computation load of the matching algorithm and affect the real-time performance of the system. Hence, the practical application of trinocular stereo vision systems is limited in various fields. In this article, a trinocular semi-global stereo matching algorithm and its hardware computational framework are proposed. Firstly, based on the in-depth analysis of the basic model of the trinocular stereo vision system, a hardware-friendly semi-global matching algorithm is proposed. Then, the overall framework of the on-chip system and the structure of each computational module are designed according to the parallelization and pipeline processing characteristics of field programmable gate array (FPGA) hardware computation. Finally, a complete hardware experiment system is established, which is based on Zynq-7000 SoC FPGA for algorithm implementation. The algorithm is evaluated by using dataset images and real scene images, respectively. Compared with the traditional binocular semi-global matching algorithm, experimental results show that the effective pixel filling rate of this algorithm is increased by 17. 31% , the error rate is reduced by 13. 06% , and the real-time stereo matching can be achieved at 60 fps in real scenes, which could meet the practical needs of various application scenarios.