Performance Comparison of Multiples and Target Detection with Imager-driven Processing Mode for Ultrafast-Imager: (Abstract Only)

Abstract

Latest vision tasks trend to be the real-time processing with high throughput frame rate and low latency. High spatiotemporal resolution imagers continue to spring up but only a few of them can be used in real applications owing to the excessive computational burden and lacking of suitable architecture. This paper presents a solution for target detection task in imager-driven processing mode (IMP), which takes shorter time in processing than the time gap between frames, even if the ulreafast imager run at full frame rate. High throughput pixel stream outputted from imager is analyzed base on multi features in a fully pipelined and bufferless architecture in FPGA. A pyramid shape model consisting of 2-D Processing Element (PE) array is proposed to search the connected regions of target candidates distributed at different time slices, and extract corresponding features when the stream pass through. A Label based 1-D PE Array collects the feature flow generated by the pyramid according to their labels, and output the feature vector of each target candidate in real time. The proposed model has been tested in simulation and experiments for target detection with 0.8Gpixel/sec (2320×1726 with 192FPS) data stream input, and the latency is less than 1 microsecond.