A moving object extraction and classification system based on Zynq and IBM SuperVessel

In this demonstration, we develop a moving object extraction and classification system based on a heterogeneous acceleration platform that consists of a local Zynq terminal and FPGA clusters on the IBM SuperVessel cloud. Extraction of the moving object from the streaming video input is offloaded to the Zynq terminal, while the classification is executed on the cloud. FPGA high level synthesis and Xilinx SDSoC Environment are applied to develop the extraction part of the system. In evaluation, the extraction and classification parts of our system achieve performance of 30 fps and 1 fps respectively for 1080P streaming video input. This demonstration displays a feasible framework for the hardware acceleration of computer vision applications and a possible job division between the terminal and the cloud.