Authors
Kotaro Hara, Jin Sun, Jonah Chazan, David Jacobs, Jon E. Froehlich
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 visionbased curb ramp detectors) in concert with human computation to improve the overall scalability of our approach.
Paper
Hara_AnInitialStudyOfAutomaticCurbRampDetectionWithCrowdsourcedVerificationUsingGoogleStreetViewImages_HCOMP2013.pdf346.6KB
Poster
Hara_AnInitialStudyOfAutomaticCurbRampDetectionWithCrowdsourcedVerificationUsingGoogleStreetViewImages_HCOMP2013PosterPrintVer.pdf28078.1KB