Zebra Crossing Spotter: Automatic Population of Spatial Databases for Increased Safety of Blind Travelers
Dragan Ahmetovic, Roberto Manduchi, James M. Coughlan and Sergio Mascetti
The 17th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2015)
Lisbon, Portugal, October 26-28, 2015
In this contribution we propose a computer vision-based technique that mines existing spatial image databases for discovery of zebra crosswalks in urban settings. Knowing the location of crosswalks is critical for a blind person planning a trip that includes street crossing. By augmenting existing spatial databases (such as Google Maps or OpenStreetMap) with this information, a blind traveler may make more informed routing decisions, resulting in greater safety during independent travel.
Our algorithm first searches for zebra crosswalks in satellite images; all candidates thus found are validated against spatially registered Google Street View images. This cascaded approach enables fast and reliable discovery and localization of zebra crosswalks in large image datasets. While fully automatic, our algorithm could also be complemented by a final crowdsourcing validation stage for increased accuracy.
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