Auto-Zooming CNN-Based Framework for Real-Time Pedestrian Detection in Outdoor Surveillance Videos

@article{Alfasly2019AutoZoomingCF,
  title={Auto-Zooming CNN-Based Framework for Real-Time Pedestrian Detection in Outdoor Surveillance Videos},
  author={Saghir Alfasly and Beibei Liu and Yongjian Hu and Yufei Wang and Chang-Tsun Li},
  journal={IEEE Access},
  year={2019},
  volume={7},
  pages={105816-105826}
}
One of the challenges faced by surveillance video analysis is to detect objects from the frames. For outdoor surveillance, detection of small object like pedestrian is of particular interest. This paper proposes a fast, lightweight, and auto-zooming-based framework for small pedestrian detection. An attentive virtual auto-zooming scheme is proposed to adaptively zoom-in the input frame by splitting it into non-overlapped tiles and pay attention to the only important tiles. Without sacrificing… CONTINUE READING

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