Abstract
It is difficult to track multiple people effectively for a long time in a complex environment because people’s clothes and body shapes may be similar, and their postures may be constantly changing. This paper proposes a novel method for multiple people tracking in crowded places where people can be partially or completely occluded. The people are detected by the deep learning method ConvNet from the color image first, and detection results are integrated with the depth information so that the accurate human areas can be extracted. The accurate personal color information can be extracted then without any background color information. multiple people tracking is proceeded by using particle filter based on the color information. the effectiveness of the proposed method is verified through experiments of tracking multiple children in a classroom.
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Xia, H. et al. (2020). User Behavior Tracking for Education Assisting System by Using an RGB-D Sensor. In: Liu, Y., Wang, L., Zhao, L., Yu, Z. (eds) Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. ICNC-FSKD 2019. Advances in Intelligent Systems and Computing, vol 1075. Springer, Cham. https://doi.org/10.1007/978-3-030-32591-6_101
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DOI: https://doi.org/10.1007/978-3-030-32591-6_101
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