ML Anthology

Active Crowd Analysis for Pandemic Risk Mitigation for Blind or Visually Impaired Persons

Samridha Shrestha, Daohan Lu, Hanlin Tian, Qiming Cao, Julie Liu, John-Ross Rizzo, William H. Seiple, Maurizio Porfiri, Yi Fang
ECCVW 2020 pp. 422-439
doi:10.1007/978-3-030-66823-5_25 /eccvw/2020/shrestha2020eccvw-active/

Abstract

During pandemics like COVID-19, social distancing is essential to combat the rise of infections. However, it is challenging for the visually impaired to practice social distancing as their low vision hinders them from maintaining a safe physical distance from other humans. In this paper, we propose a smartphone-based computationally-efficient deep neural network to detect crowds and relay the associated risks to the Blind or Visually Impaired (BVI) user through directional audio alerts. The system first detects humans and estimates their distances from the smartphone’s monocular camera feed. Then, the system clusters humans into crowds to generate density and distance maps from the crowd centers. Finally, the system tracks detections in previous frames creating motion maps predicting the motion of crowds to generate an appropriate audio alert. Active Crowd Analysis is designed for real-time smartphone use, utilizing the phone’s native hardware to ensure the BVI can safely maintain social distancing.

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Cite

Text

Shrestha et al. "Active Crowd Analysis for Pandemic Risk Mitigation for Blind or Visually Impaired Persons." European Conference on Computer Vision Workshops, 2020. doi:10.1007/978-3-030-66823-5_25

Markdown

[Shrestha et al. "Active Crowd Analysis for Pandemic Risk Mitigation for Blind or Visually Impaired Persons." European Conference on Computer Vision Workshops, 2020.](https://mlanthology.org/eccvw/2020/shrestha2020eccvw-active/) doi:10.1007/978-3-030-66823-5_25

BibTeX

@inproceedings{shrestha2020eccvw-active,
  title     = {{Active Crowd Analysis for Pandemic Risk Mitigation for Blind or Visually Impaired Persons}},
  author    = {Shrestha, Samridha and Lu, Daohan and Tian, Hanlin and Cao, Qiming and Liu, Julie and Rizzo, John-Ross and Seiple, William H. and Porfiri, Maurizio and Fang, Yi},
  booktitle = {European Conference on Computer Vision Workshops},
  year      = {2020},
  pages     = {422-439},
  doi       = {10.1007/978-3-030-66823-5_25},
  url       = {https://mlanthology.org/eccvw/2020/shrestha2020eccvw-active/}
}