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Mind your crossings: Mining GIS imagery for crosswalk localization
Dragan Ahmetovic1, Roberto Manduchi2, James M Coughlan3
1Carnegie Mellon University.
ACM Transactions on Accessible Computing
|August 1, 2017
Summary
Blind travelers need better ways to find crosswalks. A new computer vision method identifies zebra crossings using satellite and street view imagery, improving safety for independent travel.
Area of Science:
- Computer Vision
- Human-Computer Interaction
- Urban Planning
Background:
- Blind travelers face challenges locating and navigating crosswalks.
- Standard Orientation & Mobility (O&M) techniques can be enhanced with more intersection information.
- Regional differences in O&M expert opinions highlight diverse traveler needs.
Purpose of the Study:
- To investigate the role of crosswalks in blind pedestrian travel.
- To develop a computer vision technique for discovering zebra crosswalks.
- To improve safety and comfort for blind travelers during street crossings.
Main Methods:
- Surveyed O&M experts in the U.S. and Italy regarding crosswalk usage.
- Developed a computer vision algorithm to detect zebra crosswalks in satellite imagery.
- Validated crosswalk candidates using Google Street View images and a crowdsourcing web service (PCHV).
Main Results:
- U.S. experts emphasized O&M at all legal crossings; Italian experts prioritized marked crossings.
- The computer vision algorithm efficiently detects and localizes zebra crosswalks in urban areas.
- Crowdsourcing validation via PCHV can further refine detection accuracy.
Conclusions:
- Automated crosswalk detection using computer vision can aid blind travelers.
- Addressing regional differences in traffic regulations and pedestrian needs is crucial.
- Combining automated detection with crowdsourcing offers a robust solution for identifying pedestrian infrastructure.
Keywords:
Autonomous navigationCrowdsourcingOrientation and MobilitySatellite and street-level imageryVisual impairments and blindness•Computing methodologies → Object detection; Epipolar geometry•Human-centered computing → Accessibility technologies; Web-based interaction; Collaborative filtering•Information systems → Geographic information systems; Data extraction and integration;Crowdsourcing•Social and professional topics → People with disabilities
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