Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
10-2012
Abstract
We explore the feasibility of using crowd workers from Amazon Mechanical Turk to identify and rank sidewalk accessibility issues from a manually curated database of 100 Google Street View images. We examine the effect of three different interactive labeling interfaces (Point, Rectangle, and Outline) on task accuracy and duration. We close the paper by discussing limitations and opportunities for future work.
Discipline
Software Engineering | Urban Studies and Planning
Research Areas
Software and Cyber-Physical Systems
Publication
ASSETS'12: Proceedings of the 14th International ACM SIGACCESS Conference on Computers and Accessibility, Boulder, CO, October 22-24
First Page
273
Last Page
274
ISBN
9781450313216
Identifier
10.1145/2384916.2384989
Publisher
ACM
City or Country
New York
Citation
Kotaro HARA; LE, Victoria; and FROEHLICH, Jon.
A feasibility study of crowdsourcing and Google street view to determine sidewalk accessibility. (2012). ASSETS'12: Proceedings of the 14th International ACM SIGACCESS Conference on Computers and Accessibility, Boulder, CO, October 22-24. 273-274.
Available at: https://ink.library.smu.edu.sg/sis_research/4009
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1145/2384916.2384989