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Learning from Outdoor Webcams: Surveillance of Physical Activity Across Environments

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Seeing Cities Through Big Data

Part of the book series: Springer Geography ((SPRINGERGEOGR))

Abstract

Publicly available, outdoor webcams continuously view the world and share images. These cameras include traffic cams, campus cams, ski-resort cams, etc. The Archive of Many Outdoor Scenes (AMOS) is a project aiming to geolocate, annotate, archive, and visualize these cameras and images to serve as a resource for a wide variety of scientific applications. The AMOS dataset has archived over 750 million images of outdoor environments from 27,000 webcams since 2006. Our goal is to utilize the AMOS image dataset and crowdsourcing to develop reliable and valid tools to improve physical activity assessment via online, outdoor webcam capture of global physical activity patterns and urban built environment characteristics.

This project’s grand scale-up of capturing physical activity patterns and built environments is a methodological step forward in advancing a real-time, non-labor intensive assessment using webcams, crowdsourcing, and eventually machine learning. The combined use of webcams capturing outdoor scenes every 30 min and crowdsources providing the labor of annotating the scenes allows for accelerated public health surveillance related to physical activity across numerous built environments. The ultimate goal of this public health and computer vision collaboration is to develop machine learning algorithms that will automatically identify and calculate physical activity patterns.

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Acknowledgements

This work was funded by the Washington University in St. Louis University Research Strategic Alliance pilot award and the National Cancer Institute of the National Institutes of Health under award number 1R21CA186481. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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Authors and Affiliations

  1. Department of Parks, Recreation, and Tourism Management and Center for Geospatial Analytics, North Carolina State University, 2820 Faucette Dr., Campus Box 8004, Raleigh, NC, 27695, USA

    J. Aaron Hipp Ph.D.

  2. Brown School, Washington University in St. Louis, St. Louis, MO, USA

    Deepti Adlakha M.U.D., Amy A. Eyler Ph.D. & Rebecca Gernes M.S.W., M.P.H.

  3. Prevention Research Center, Washington University in St. Louis, St. Louis, MO, USA

    Deepti Adlakha M.U.D., Amy A. Eyler Ph.D. & Rebecca Gernes M.S.W., M.P.H.

  4. Computer Science and Engineering, Washington University in St. Louis, St. Louis, MO, USA

    Agata Kargol, Abigail H. Stylianou & Robert Pless Ph.D.

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  1. J. Aaron Hipp Ph.D.
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  2. Deepti Adlakha M.U.D.
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  3. Amy A. Eyler Ph.D.
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  6. Abigail H. Stylianou
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  7. Robert Pless Ph.D.
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Correspondence to J. Aaron Hipp Ph.D. .

Editor information

Editors and Affiliations

  1. Urban Studies and Urban Big Data Centre, University of Glasgow, Glasgow, United Kingdom

    Piyushimita (Vonu) Thakuriah

  2. Department of Urban Planning and Policy, University of Illinois at Chicago, Chicago, Illinois, USA

    Nebiyou Tilahun

  3. Department of Urban Planning and Policy, University of Illinois at Chicago, Chicago, Illinois, USA

    Moira Zellner

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Hipp, J.A. et al. (2017). Learning from Outdoor Webcams: Surveillance of Physical Activity Across Environments. In: Thakuriah, P., Tilahun, N., Zellner, M. (eds) Seeing Cities Through Big Data. Springer Geography. Springer, Cham. https://doi.org/10.1007/978-3-319-40902-3_26

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