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CamIO

CamIO (short for “Camera Input-Output”) is a system to make physical objects (such as documents, maps, devices and 3D models) accessible to blind and visually impaired persons, by providing real-time audio feedback in response to the location on an object that the user is touching. CamIO currently works on iOS using the built-in camera.

See a video demonstration of CamIO here (using the Windows platform, with functionality similar to the iOS platform), showing how the system begins announcing information about a "hotspot" location (i.e., audio label) as soon as the stylus touches that location, and immediately ceases this announcement when the stylus moves away from the hotspot.

See a presentation (pdf available here) of the latest CamIO research on March 12, 2020 at the CSUN Assistive Technology 2020 conference in Anaheim. This research describes a new accessible annotation feature that allows a blind or visually impaired user to independently create and record their own audio labels. This research is described in our CSUN Journal paper, "Towards Accessible Audio Labeling of 3D Objects," which was awarded the 2020 Dr. Arthur I. Karshmer Award for Assistive Technology Research!

CamIO is supported by a four-year grant from NIH/NEI (R01EY025332) and by the NIDILRR RERC grant (90RE5024-01-00).

Tabs

Conference Papers
Mascetti, S., Gerino, A., Bernareggi, C., D’Acquisto, S., Ducci, M., & Coughlan, J.. (2017). JustPoint: Identifying Colors with a Natural User Interface. In 19th Int’l ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2017). ACM: Baltimore, MD.
Coughlan, J., & Miele, J.. (2017). Evaluating Author and User Experience for an Audio-Haptic System for Annotation of Physical Models. In 19th Int’l ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2017). ACM: Baltimore, MD.
Shen, H., Edwards, O., Miele, J., & Coughlan, J.. (2013). CamIO: a 3D computer vision system enabling audio/haptic interaction with physical objects by blind users. In Proceedings of the 15th International ACM SIGACCESS Conference on Computers and Accessibility (p. 41). ACM.
  • L to R: Huiying Shen, Ali Cheraghi, Brandon Biggs, James Coughlan, Charity Pitcher-Cooper, Giovanni Fusco

    Coughlan Lab

    The goal of our laboratory is to develop and test assistive technology for blind and visually impaired persons that is enabled by computer vision and other sensor technologies.

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