HOG feature extractor circuit for real-time human and vehicle detection
Seon-Young Lee, Haengseon Son, Jong Chan Choi, Kyoungwon Min · 2012
Smart vehicle technologies such as ADAS are growing concern about. Especially, pedestrian and vehicle recognition system based on machine vision is a big issue. In this paper, we propose the hardwired HOG feature extractor circuit for real-time human and vehicle detection, and describe the hardware implementation results. Our HOG feature extractor supports weighted gradient value, 2D histogram interpolation and block normalization. We have used the simplified methods of the square root and division operation for the hardware implementation. Our HOG feature extractor circuit was verified on FPGA environment and can be processed 33 frames per seconds for 640×480 VGA images in real-time.