ICCHP 2008: Computers Helping People with Special Needs pp 1122-1128 | Cite as
Crosswatch: A Camera Phone System for Orienting Visually Impaired Pedestrians at Traffic Intersections
Abstract
Urban intersections are the most dangerous parts of a blind or visually impaired person’s travel. To address this problem, this paper describes the novel “Crosswatch” system, which uses computer vision to provide information about the location and orientation of crosswalks to a blind or visually impaired pedestrian holding a camera cell phone. A prototype of the system runs on an off-the-shelf Nokia camera phone in real time, which automatically takes a few images per second, uses the cell phone’s built-in computer to analyze each image in a fraction of a second and sounds an audio tone when it detects a crosswalk. Tests with blind subjects demonstrate the feasibility of the system and its ability to provide useful crosswalk alignment information under real-world conditions.
Keywords
Cell Phone Blind Subject Camera Phone Audio Feedback Urban IntersectionPreview
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References
- 1.Barlow, J.M., Bentzen, B.L., Tabor, L.: Accessible pedestrian signals: Synthesis and guide to best practice. National Cooperative Highway Research Program (2003)Google Scholar
- 2.Burton, D.: You Get to Choose: An Overview of Accessible Cell Phones. Access Issues 6(2) (2005), http://www.afb.org/afbpress/pub.asp?DocID=aw060206&select=1#1
- 3.Coughlan, J., Shen, H.: A Fast Algorithm for Finding Crosswalks using Figure-Ground Segmentation. In: Proc. 2nd Workshop on Applications of Computer Vision, a satellite workshop of European Conference on Computer Vision, Graz, Austria (2006)Google Scholar
- 4.Crandall, W., Bentzen, B., Myers, L., Brabyn, J.: New orientation and accessibility option for persons with visual impairment: transportation applications for remote infrared audible signage. Clinical and Experimental Optometry 84(3), 120–131 (2001)CrossRefGoogle Scholar
- 5.Ivanchenko, V., Coughlan, J., Shen, H.: Detecting and Locating Crosswalks using a Camera Phone. In: Fourth Workshop on Embedded Computer Vision (ECVW), associated with Computer Vision and Pattern Recognition (submitted, 2008)Google Scholar
- 6.Loomis, J., Klatzky, R., Golledge, R.: Navigating without vision: basic and applied research. Optom. Vis. Sci. 78(5), 282–289 (2001)CrossRefGoogle Scholar
- 7.Se, S., Brady, M.: Road Feature Detection and Estimation. Machine Vision and Applications Journal 14(3), 157–165 (2003)Google Scholar
- 8.Shioyama, T., Wu, H., Nakamura, N., Kitawaki, S.: Measurement of the pedestrian crossings and detection of traffic lights from image data. Meas. Sci. Technol. 13, 1450–1457 (2002)CrossRefGoogle Scholar
- 9.Uddin, M.S., Shioyama, T.: Bipolarity- and Projective Invariant-Based Zebra-Crossing Detection for the Visually Impaired. In: 1st IEEE Workshop on Computer Vision Applications for the Visually Impaired, a satellite workshop of Computer Vision and Pattern Recognition (2005)Google Scholar
- 10.Utcke, S.: Grouping based on Projective Geometry Constraints and Uncertainty. In: Internation Conference on Computer Vision, Bombay, India (1998)Google Scholar