ArticleInternational journal of environmental research and public health2022
Training Computers to See the Built Environment Related to Physical Activity: Detection of Microscale Walkability Features Using Computer Vision.
Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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The trial behind it
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Who cites it
10 citing papers in PubMed.
- Re-thinking Walkability: Synergizing the Pedestrian Environment and Land Use Patterns to Promote Physical Activity in Older Adults.Cities (London, England) · 2026Article
- A community case study of pedestrian environment features of neighborhood walkability and built environment-related 311 service requests surrounding public housing developments serving low-income Boston residents.Frontiers in public health · 2026Article
- Scaling up natural experimental studies: harnessing emerging technologies to transform physical activity and built environment research.The international journal of behavioral nutrition and physical activity · 2025Article
- Objectively-measured Environmental Support for Physical Activity, Healthy Eating, and Breastfeeding in the Rural United States: A Scoping Review to Inform Opportunities for Public Health Surveillance.Journal of healthy eating and active living · 2025Article
- Using Video Cameras to Assess Physical Activity and Other Well-Being Behaviors in Urban Environments: Feasibility, Reliability, and Participant Reactivity Studies.JMIR public health and surveillance · 2024Article
- Using Computer Vision to Annotate Video-Recoded Direct Observation of Physical Behavior.Sensors (Basel, Switzerland) · 2024Article
- Multi-Task Classification for Improved Health Outcome Prediction Based on Environmental Indicators.IEEE access : practical innovations, open solutions · 2023Article
- Using Convolutional Neural Networks to Derive Neighborhood Built Environments from Google Street View Images and Examine Their Associations with Health Outcomes.International journal of environmental research and public health · 2022Article
- The mitigating effect of street trees, urban flora, and the suburban environment on seasonal peak UV indices: A case study from Brisbane, Australia.Photochemistry and photobiologyArticle
- Neighborhood Socioeconomic Status, Green Space, and Walkability and Risk for Falls Among Postmenopausal Women: The Women's Health Initiative.Women's health issues : official publication of the Jacobs Institute of Women's HealthArticle
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
The study purpose was to train and validate a deep learning approach to detect microscale streetscape features related to pedestrian physical activity. This work innovates by combining computer vision techniques with Google Street View (GSV) images to overcome impediments to conducting audits (e.g., time, safety, and expert labor cost). The EfficientNETB5 architecture was used to build deep learning models for eight microscale features guided by the Microscale Audit of Pedestrian Streetscapes Mini tool: sidewalks, sidewalk buffers, curb cuts, zebra and line crosswalks, walk signals, bike symbols, and streetlights. We used a train−correct loop, whereby images were trained on a training dataset, evaluated using a separate validation dataset, and trained further until acceptable performance metrics were achieved. Further, we used trained models to audit participant (N = 512) neighborhoods in the WalkIT Arizona trial. Correlations were explored between microscale features and GIS-measured and participant-reported neighborhood macroscale walkability. Classifier precision, recall, and overall accuracy were all over >84%. Total microscale was associated with overall macroscale walkability (r = 0.30, p < 0.001). Positive associations were found between model-detected and self-reported sidewalks (r = 0.41, p < 0.001) and sidewalk buffers (r = 0.26, p < 0.001). The computer vision model results suggest an alternative to trained human raters, allowing for audits of hundreds or thousands of neighborhoods for population surveillance or hypothesis testing.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.