FH-YOLOv4 with Constrained Aspect Ratio Loss for Video Face Detection and Public Safety

Video face detection is a crucial first step in many facial recognition and face analysis systems. It should serve postprocessing steps as much as possible while satisfying high-accuracy real-time detection. In this paper, we first introduce the constrained aspect ratio loss (CARLoss) for better facial boxes regression and incorporate it into the modified FH-YOLOv4, then the IoU Tracker-based video face image deduplication algorithm is proposed on the detection level. Extensive experiments and comparative tests show the effectiveness of our method.