REAL-TIME FACE DETECTION AND HUMAN TRACKING SYSTEM ON FPGA CYCLONE-V

Face detection in image sequence (real-time video stream) has been an active research area in the computer vision field in recent years due to its potential applications such as surveillance cameras, human computer interfaces, smart rooms, intelligent robots and biomedical image analysis. Face detection is a process that determines whether an image has a face or not. In this paper, an embedded system for detecting and tracking human faces in real-time video stream implemented on FPGA DE10-NANO is proposed. The system can be divided into two parts: data streaming, data processing. Experimental results show that the system is capable of accurately detecting faces of up to 5 different people at a distance of up to 1.5 meters from the camera, coexisting in the same frame in resolution of 320x240 pixels with a detection speed of only several hundred milliseconds prove the feasibility of the system. A comparison with similar existing projects will be discussed for evaluation and conclusion as well