Sensors (Feb 2020)

Employing Shadows for Multi-Person Tracking Based on a Single RGB-D Camera

  • Wei Gai,
  • Meng Qi,
  • Mingcong Ma,
  • Lu Wang,
  • Chenglei Yang,
  • Juan Liu,
  • Yulong Bian,
  • Gerard de Melo,
  • Shijun Liu,
  • Xiangxu Meng

DOI
https://doi.org/10.3390/s20041056
Journal volume & issue
Vol. 20, no. 4
p. 1056

Abstract

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Although there are many algorithms to track people that are walking, existing methods mostly fail to cope with occluded bodies in the setting of multi-person tracking with one camera. In this paper, we propose a method to use people’s shadows as a clue to track them instead of treating shadows as mere noise. We introduce a novel method to track multiple people by fusing shadow data from the RGB image with skeleton data, both of which are captured by a single RGB Depth (RGB-D) camera. Skeletal tracking provides the positions of people that can be captured directly, while their shadows are used to track them when they are no longer visible. Our experiments confirm that this method can efficiently handle full occlusions. It thus has substantial value in resolving the occlusion problem in multi-person tracking, even with other kinds of cameras.

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