Research on HOG-SVM pedestrian detection method based on FPGA

Abstract

At present, pedestrian detection technology has become a research hotspot in the field of image processing and computer vision, and has developed to open up a wide range of application prospects. This paper gives a comprehensive introduction to the algorithm and FPGA implementation of object detection algorithm including HOG and SVM. In the field of pedestrian detection, HOG-SVM pedestrian detection method based on FPGA has unique advantages compared with other various object detection methods. In the current research, this implementation method usually has a detection accuracy rate of more than 95% and a detection speed of more than 30 frames/s for the INRIA data sets, which perfectly meets the pedestrian detection requirement. FPGA with its parallel structure and a large amount of programmable logic sources greatly improve the HOG-SVM to perform real-time pedestrian detection. With the development of hardware acceleration and detection algorithms, more and more pedestrian detection methods with better performance will appear in the future.