VizWiz
Author(s)
Bigham, Jeffrey P.
Yeh, Tom
Jayant, Chandrika
Ji, Hanjie
Miller, Andrew
White, Brandyn
White, Samuel
Little, Danny Greg
Miller, Robert C
Tatarowicz, Aubrey L
Date Issued
April 2010
Journal
Proceedings of the 2010 International Cross Disciplinary Conference on Web Accessibility (W4A) - W4A '10
Publisher
Association for Computing Machinery (ACM)
Citation
Bigham, Jeffrey P.; Yeh, Tom; Jayant, Chandrika; Ji, Hanjie; Little, Greg; Miller, Andrew; Miller, Robert C.; Tatarowicz, Aubrey; White, Brandyn and White, Samuel. “VizWiz.” Proceedings of the 2010 International Cross Disciplinary Conference on Web Accessibility (W4A), April 26-27 2010, Raleigh, North Carolina, Association for Computing Machinery (ACM), April 2010.
Version
Author's final manuscript
Abstract
The lack of access to visual information like text labels, icons,and colors can cause frustration and decrease independence for blind people. Current access technology uses automatic approaches to address some problems in this space, but the technology is error-prone, limited in scope, and quite expensive. In this paper, we introduce VizWiz, a talking application for mobile phones that offers a new alternative to answering visual questions in nearly real-time—asking multiple people on the web. To support answering questions quickly, we introduce a general approach for intelligently recruiting human workers in advance called quikTurkit so that workers are available when new questions arrive. A field deployment with 11 blind participants illustrates that blind people can effectively use VizWiz to cheaply answer questions in their everyday lives, highlighting issues that automatic approaches will need to address to be useful. Finally, we illustrate the potential of using VizWiz as part of the participatory design of advanced tools by using it to build and evaluate VizWiz::LocateIt, an interactive mobile tool that helps blind people solve general visual search problems.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Attribution-Noncommercial-Share Alike 3.0
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/1805986.1806020
