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.
Keywords
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Adams MA, Todd M, Kurka J, Conway TL, Cain KL, Frank LD, Sallis JF (2015) Patterns of walkability, transit, and recreation environment for physical activity. Am J Prev Med 49(6):878–887
Adlakha D, Budd EL, Gernes R, Sequeira S, Hipp JA (2014) Use of emerging technologies to assess differences in outdoor physical activity in St. Louis, Missouri. Front Public Health 2:41
Bader MDM, Mooney SJ, Lee YJ, Sheehan D, Neckerman KM, Rundle AG, Teitler JO (2015) Development and deployment of the Computer Assisted Neighborhood Visual Assessment System (CANVAS) to measure health-related neighborhood conditions. Health Place 31:163–172
Badland HM, Opit S, Witten K, Kearns RA, Mavoa S (2010) Can virtual streetscape audits reliably replace physical streetscape audits? J Urban Health 87:1007–1016
Baran PK, Smith WR, Moore RC, Floyd MF, Bocarro JN, Cosco NG, Danninger TM (2013) Park use among youth and adults: examination of individual, social, and urban form factors. Environ Behav. doi:10.1177/0013916512470134
Barrett MA, Humblet O, Hiatt RA, Adler NE (2013) Big data and disease prevention: from quantified self to quantified communities. Big Data 1:168–175
Bedimo-Rung A, Gustat J, Tompkins BJ, Rice J, Thomson J (2006) Development of a direct observation instrument to measure environmental characteristics of parks for physical activity. J Phys Act Health 3:S176–S189
Berinsky AJ, Huber GA, Lenz GS (2012) Evaluating online labor markets for experimental research: Amazon.com’s Mechanical Turk. Polit Anal 20:351–368
Bohannon J (2011) Social science for pennies. Science 334:307
Brownson RC, Hoehner CM, Day K, Forsyth A, Sallis JF (2009) Measuring the built environment for physical activity: state of the science. Am J Prev Med 36: S99–S123.e12
Buhrmester M, Kwang T, Gosling SD (2011) Amazon’s Mechanical Turk: a new source of inexpensive, yet high-quality, data? Perspect Psychol Sci 6:3–5
CDC (2009) Division of Nutrition, Physical Activity and Obesity. http://www.cdc.gov/nccdphp/dnpa/index.htm
CDC (2011) Guide to community preventive services. Epidemiology Program Office, CDC, Atlanta, GA
Cerin E, Conway TL, Saelens BE, Frank LD, Sallis JF (2009) Cross-validation of the factorial structure of the Neighborhood Environment Walkability Scale (NEWS) and its abbreviated form (NEWS-A). Int J Behav Nutr Phys Act 6:32
Charreire H, Mackenbach JD, Ouasti M, Lakerveld J, Compernolle S, Ben-Rebah M, McKee M, Brug J, Rutter H, Oppert JM (2014) Using remote sensing to define environmental characteristics related to physical activity and dietary behaviours: a systematic review (the SPOTLIGHT project). Health Place 25:1–9
Clarke P, Ailshire J, Melendez R, Bader M, Morenoff J (2010) Using Google Earth to conduct a neighborhood audit: reliability of a virtual audit instrument. Health Place 16:1224–1229
Cohen DA, Marsh T, Williamson S, Golinelli D, McKenzie TL (2012) Impact and cost-effectiveness of family Fitness Zones: a natural experiment in urban public parks. Health Place 18:39–45
Crandall DJ, Backstrom L, Huttenlocher D, Kleinberg J (2009) Mapping the world’s photos. In: Proceedings of the 18th international conference on World Wide Web
Day K, Boarnet M, Alfonzo M, Forsyth A (2006) The Irvine–Minnesota inventory to measure built environments: development. Am J Prev Med 30:144–152
Ding D, Gebel K (2012) Built environment, physical activity, and obesity: what have we learned from reviewing the literature? Health Place 18:100–105
Dyck DV, Cerin E, Conway TL, Bourdeaudhuij ID, Owen N, Kerr J, Cardon G, Frank LD, Saelens BE, Sallis JF (2012) Perceived neighborhood environmental attributes associated with adults’ transport-related walking and cycling: findings from the USA, Australia and Belgium. Int J Behav Nutr Phys Act 9:70
Edwards N, Hooper P, Trapp GSA, Bull F, Boruff B, Giles-Corti B (2013) Development of a Public Open Space Desktop Auditing Tool (POSDAT): a remote sensing approach. Appl Geogr 38:22–30
Ewing R, Meakins G, Hamidi S, Nelson A (2003) Relationship between urban sprawl and physical activity, obesity, and morbidity. Am J Health Promot 18:47–57
Feng J, Glass TA, Curriero FC, Stewart WF, Schwartz BS (2010) The built environment and obesity: a systematic review of the epidemiologic evidence. Health Place 16:175–190
Ferdinand AO, Sen B, Rahurkar S, Engler S, Menachemi N (2012) The relationship between built environments and physical activity: a systematic review. Am J Public Health 102:e7–e13
Ginsberg J, Mohebbi MH, Patel RS, Brammer L, Smolinski MS, Brilliant L (2009) Detecting influenza epidemics using search engine query data. Nature 457:1012–1014
Graham DJ, Hipp JA (2014) Emerging technologies to promote and evaluate physical activity: cutting-edge research and future directions. Front Public Health 2:66
Handy S, Boarnet M, Ewing R, Killingsworth R (2002) How the built environment affects physical activity: views from urban planning. Am J Prev Med 23:64–73
Harris JK, Lecy J, Parra DC, Hipp A, Brownson RC (2013) Mapping the development of research on physical activity and the built environment. Prev Med 57:533–540
Hipp JA (2013) Physical activity surveillance and emerging technologies. Braz J Phys Act Health 18:2–4
Hipp JA, Adlakha D, Eyler AA, Chang B, Pless R (2013a) Emerging technologies: webcams and crowd-sourcing to identify active transportation. Am J Prev Med 44:96–97
Hipp JA, Adlakha D, Gernes R, Kargol A, Pless R (2013b) Do you see what I see: crowdsource annotation of captured scenes. In: Proceedings of the 4th international SenseCam & pervasive imaging conference. San Diego, CA: ACM
Hirsch JA, James P, Robinson JR, Eastman KM, Conley KD, Evenson KR, Laden F (2014) Using MapMyFitness to place physical activity into neighborhood context. Front Public Health 2:19
Hurvitz PM, Moudon AV, Kang B, Saelens BE, Duncan GE (2014) Emerging technologies for assessing physical activity behaviors in space and time. Front Public Health 2:2
Ilushin D, Richardson A, Toomey M, Pless R, Shapiro A (2013) Comparing the effects of different remote sensing techniques for extracting deciduous broadleaf phenology. In: AGU Fall Meeting abstracts
Jackson RJ (2003) The impact of the built environment on health: an emerging field. Am J Public Health 93:1382–1384
Jackson RJ, Dannenberg AL, Frumkin H (2013) Health and the built environment: 10 years after. Am J Public Health 103:1542–1544
Jacobs J (1961) The death and life of great American cities. Random House LLC, New York
Jacobs N, Roman N, Pless R (2007) Consistent temporal variations in many outdoor scenes. In: IEEE conference on computer vision and pattern recognition, 2007, CVPR ’07, 17–22 June 2007. pp 1–6
Jacobs N, Roman N, Pless R (2008) Toward fully automatic geo-location and geo-orientation of static outdoor cameras. In: Proc. IEEE workshop on video/image sensor networks
Jacobs N, Burgin W, Fridrich N, Abrams A, Miskell K, Braswell BH, Richardson AD, Pless R (2009) The global network of outdoor webcams: properties and applications. In: ACM international conference on advances in geographic information systems (SIGSPATIAL GIS)
James P, Berrigan D, Hart JE, Hipp JA, Hoehner CM, Kerr J, Major JM, Oka M, Laden F (2014) Effects of buffer size and shape on associations between the built environment and energy balance. Health Place 27:162–170
Kaczynski AT, Henderson KA (2007) Environmental correlates of physical activity: a review of evidence about parks and recreation. Leis Sci 29:315–354
Kaczynski AT, Wilhelm Stanis SA, Hipp JA (2014) Point-of-decision prompts for increasing park-based physical activity: a crowdsource analysis. Prev Med 69:87–89
Kamel Boulos MN, Resch B, Crowley DN, Breslin JG, Sohn G, Burtner R, Pike WA, Jezierski E, Chuang KY (2011) Crowdsourcing, citizen sensing and sensor web technologies for public and environmental health surveillance and crisis management: trends, OGC standards and application examples. Int J Health Geogr 10:67
Kelly C, Wilson J, Baker E, Miller D, Schootman M (2013) Using Google Street View to audit the built environment: inter-rater reliability results. Ann Behav Med 45(Suppl 1):S108–S112
Kelly C, Wilson JS, Schootman M, Clennin M, Baker EA, Miller DK (2014) The built environment predicts observed physical activity. Front Public Health 2:52
Kerr J, Duncan S, Schipperijn J (2011) Using global positioning systems in health research: a practical approach to data collection and processing. Am J Prev Med 41:532–540
Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33:159–174
Lynch K (1960) The image of the city. MIT Press, Cambridge
Mckenzie TL, Cohen DA (2006) System for observing play and recreation in communities (SOPARC). In: Center for Population Health and Health Disparities (ed) RAND
Milgram S, Sabini JE, Silver ME (1992) The individual in a social world: essays and experiments. McGraw-Hill Book Company, New York
Naaman M (2011) Geographic information from georeferenced social media data. SIGSPATIAL Special 3:54–61
National Center for Safe Routes to School (2010) Retrieved from http://www.saferoutesinfo.org/.
Odgers CL, Caspi A, Bates CJ, Sampson RJ, Moffitt TE (2012) Systematic social observation of children’s neighborhoods using Google Street View: a reliable and cost-effective method. J Child Psychol Psychiatry 53:1009–1017
Office of the Surgeon General, Overweight and obesity: at a glance (2011) Retrieved from http://www.cdc.gov/nccdphp/sgr/ataglan.htm.
Oldenburg R (1989) The great good place: cafés, coffee shops, community centers, beauty parlors, general stores, bars, hangouts, and how they get you through the day. Paragon House, New York
Pless R, Jacobs N (2006) The archive of many outdoor scenes, media and machines lab, Washington University in St. Louis and University of Kentucky
Reed JA, Price AE, Grost L, Mantinan K (2012) Demographic characteristics and physical activity behaviors in sixteen Michigan parks. J Community Health 37:507–512
Renalds A, Smith TH, Hale PJ (2010) A systematic review of built environment and health. Fam Community Health 33:68–78
Richardson A, Friedl M, Frolking S, Pless R, Collaborators P (2011) PhenoCam: a continental-scale observatory for monitoring the phenology of terrestrial vegetation. In: AGU Fall Meeting abstracts
Rundle AG, Bader MDM, Richards CA, Neckerman KM, Teitler JO (2011) Using Google Street View to audit neighborhood environments. Am J Prev Med 40:94–100
Sadanand S, Corso JJ (2012) Action bank: a high-level representation of activity in video. In: IEEE conference on computer vision and pattern recognition (CVPR), 2012
Saelens BE, Handy S (2008) Built environment correlates of walking: a review. Med Sci Sports Exerc 40:S550–S566
Saelens BE, Frank LD, Auffrey C, Whitaker RC, Burdette HL, Colabianchi N (2006) Measuring physical environments of parks and playgrounds: EAPRS instrument development and inter-rater reliability. J Phys Act Health 3:S190–S207
Sampson RJ, Raudenbush SW (1999) Systematic social observation of public spaces: a new look at disorder in urban neighborhoods. Am J Sociol 105:603
Sandercock G, Angus C, Barton J (2010) Physical activity levels of children living in different built environments. Prev Med 50:193–198
Schipperijn J, Kerr J, Duncan S, Madsen T, Klinker CD, Troelsen J (2014) Dynamic accuracy of GPS receivers for use in health research: a novel method to assess GPS accuracy in real-world settings. Front Public Health 2:21
Sequeira S, Hipp A, Adlakha D, Pless R (2013) Effectiveness of built environment interventions by season using web cameras. In: 141st APHA annual meeting, 2–6 Nov 2013
Silva TH, Melo PO, Almeida JM, Salles J, Loureiro AA (2012) Visualizing the invisible image of cities. In: IEEE international conference on green computing and communications (GreenCom), 2012
Stauffer C, Grimson WEL (2000) Learning patterns of activity using real-time tracking. IEEE Trans Pattern Anal Mach Intell 22:747–757
Taylor JR, Lovell ST (2012) Mapping public and private spaces of urban agriculture in Chicago through the analysis of high-resolution aerial images in Google Earth. Landsc Urban Plan 108:57–70
Taylor BT, Peter F, Adrian EB, Anna W, Jonathan CC, Sally R (2011) Measuring the quality of public open space using Google Earth. Am J Prev Med 40:105–112
Whyte WH (1980) The social life of small urban spaces. The Conservation Foundation, Washington, DC
Wilson JS, Kelly CM (2011) Measuring the quality of public open space using Google Earth: a commentary. Am J Prev Med 40:276–277
Wilson JS, Kelly CM, Schootman M, Baker EA, Banerjee A, Clennin M, Miller DK (2012) Assessing the built environment using omnidirectional imagery. Am J Prev Med 42:193–199
Xu Z, Weinberger KQ, Chapelle O (2012) Distance metric learning for kernel machines. arXiv preprint arXiv:1208.3422
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.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing Switzerland
About this chapter
Cite this chapter
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
Download citation
DOI: https://doi.org/10.1007/978-3-319-40902-3_26
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-40900-9
Online ISBN: 978-3-319-40902-3
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)