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

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  • Yue Wang
  • Liang Hong
  • Dewen Gu
  • Pingping Fu
  • Wei Zhang

Abstract

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.

Suggested Citation

  • Yue Wang & Liang Hong & Dewen Gu & Pingping Fu & Wei Zhang, 2022. "FH-YOLOv4 with Constrained Aspect Ratio Loss for Video Face Detection and Public Safety," Discrete Dynamics in Nature and Society, Hindawi, vol. 2022, pages 1-10, August.
    • Handle: RePEc:hin:jnddns:8355174
    DOI: 10.1155/2022/8355174
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