Multi-channel video acquisition and AI acceleration based on FPGA
This study realized the acceleration of multi-channel source video collection,splicing,and AI collaborative processing based on the MES50HP development board and PC host.The proposed system can support the simultaneous collection of four-channel video data from HDMI,network port,camera,and optical fiber.After the video is collected and spliced,it will be scaled and stored in double data rate synchronous dynamic random access memory.The output part is divided into two channels,one of which is used for HDMI loop-back output,and the other is transmitted to the PC host through peripheral component interconnect express(PCIE)for result display,and the data returned by PCIE is read on the PC side and the target detection results are displayed.The video acquisition and target recognition acceleration parts are mainly composed of two MES50HP development boards.This system implements a convolution accelerator on FPGA,the convolution accelerator calculates one layer of the neural network and then transmits it to the host through PCIE for the results display.The convolution calculation is deeply fused with image acquisition,which is real-time and low-cost and can be widely used in edge computing and other fields.The results showed that for the traffic light data set,this method achieved a maximum mean average precision value of 0.746 and a maximum frame rate of 45 on a PC host.
万方数据
维普
