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Cited by 398

The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.

Electronic frog eye: Counting crowd using WiFi

Xi, Wei, Zhao, Jizhong, Li, Xiang-Yang, Zhao, Kun, Tang, Shaojie, Liu, Xue, Jiang, Zhiping·2014·IEEE INFOCOM 2014 - IEEE Conference on Computer Communications
DOI 10.1109/infocom.2014.6847958
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Abstract

Crowd counting, which count or accurately estimate the number of human beings within a region, is critical in many applications, such as guided tour, crowd control and marketing research and analysis. A crowd counting solution should be scalable and be minimally intrusive (i.e., device-free) to users. Image-based solutions are device-free, but cannot work well in a dim or dark environment. Non-image based solutions usually require every human being carrying device, and are inaccurate and unreliable in practice. In this paper, we present FCC, a device-Free Crowd Counting approach based on Channel State Information (CSI). Our design is motivated by our observation that CSI is highly sensitive to environment variation, like a frog eye. We theoretically discuss the relationship between the number of moving people and the variation of wireless channel state. A major challenge in our design of FCC is to find a stable monotonic function to characterize the relationship between the crowd number and various features of CSI. To this end, we propose a metric, the Percentage of nonzero Elements (PEM), in the dilated CSI Matrix. The monotonic relationship can be explicitly formulated by the Grey Verhulst Model, which is used for crowd counting without a labor-intensive site survey. We implement FCC using off-the-shelf IEEE 802.11n devices and evaluate its performance via extensive experiments in typical real-world scenarios. Our results demonstrate that FCC outperforms the state-of-art approaches with much better accuracy, scalability and reliability.

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Research works printed but not linked: 6

  1. 10.1109/INFCOM.2007.147 · doi:10.1109/infcom.2007.147
  2. arai, 0, Estimation of zigbee's rssi fluctuated by crowd behavior in indoor space, Proc SICE 2010, 696
  3. 10.1109/PERCOM.2011.5767585 · doi:10.1109/percom.2011.5767585
  4. 10.1109/MASS.2012.6502524 · doi:10.1109/mass.2012.6502524
  5. 10.1109/TIFS.2011.2146774 · doi:10.1109/tifs.2011.2146774
  6. weppner, 0, Collaborative crowd density estimation with mobile phones, Proceedings of Sensys 2011

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Metadata

Authors
Xi, W., Zhao, J., Li, X.-Y., Zhao, K., Tang, S., Liu, X., & Jiang, Z.
Venue
IEEE INFOCOM 2014 - IEEE Conference on Computer Communications
Publisher
IEEE
Published
2014-04
Pages
361-369
DOI
10.1109/infocom.2014.6847958
OpenAlex
W1989115430
Cited by
398
References
24
FWCI
40.63
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Electronic frog eye: Counting crowd using WiFi. https://app.cochat.ai/papers/10.1109/infocom.2014.6847958
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Xi, W., Zhao, J., Li, X.-Y., Zhao, K., Tang, S., Liu, X., & Jiang, Z. (2014). Electronic frog eye: Counting crowd using WiFi. IEEE INFOCOM 2014 - IEEE Conference on Computer Communications. https://doi.org/10.1109/infocom.2014.6847958

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