Abstract
In our previous research, we examined whether minimally trained crowd workers could find, categorize, and assess sidewalk accessibility problems using Google Street View (GSV) images. This poster paper presents a first step towards combining automated methods (e.g., machine vision-based curb ramp detectors) in concert with human computation to improve the overall scalability of our approach.
Cite
CITATION STYLE
Hara, K., Sun, J., Chazan, J., Jacobs, D., & Froehlich, J. E. (2013). An Initial Study of Automatic Curb Ramp Detection with Crowdsourced Verification Using Google Street View Images. In Proceedings of the 1st AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2013 (pp. 32–33). AAAI Press. https://doi.org/10.1609/hcomp.v1i1.13109
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