NEROvideo: a general-purpose CNN-UM video processing system

摘要

Emulations of cellular nonlinear networks (CNN) on digital reconfigurable hardware have proved to be adequate for highly-efficient computation of massive data, exceeding the accuracy and flexibility of full-custom designs. Based on a recently-proposed architecture for the emulation of a large-scale CNN universal machine, a new real-time video processing system has been developed. Due to its free programmability and massively-parallel architecture the system is very suitable for high-speed computation of complex algorithms that follow the idea of spatio-temporal computing. Implemented on a state-of-the-art Xilinx Zynq system-on-chip, the proposed setup is capable of processing a p video stream with up to 1,700 fps, depending on the respective algorithm.