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This paper investigates the tools and practices used by Orientation and Mobility (O&M) specialists in instructing people who are blind or have low vision in concepts, skills, and techniques for safe and independent travel. Based on interviews with experienced instructors who practice in different O&M settings we find that a shortage of qualified specialists and restrictions on in-person activities during COVID-19 has accelerated interest in remote instruction and assessment, while widespread adoption of smartphones with accessibility support has driven interest in assistive apps. This presents both opportunities and challenges for a practice that is traditionally conducted in-person and assessed through qualitative observations. In response we identify multiple opportunities for HCI research in service of O&M, including: supporting a 'physician's assistant' model of remote O&M instruction and assessment, matching O&M instructors' clients with guide dogs, highlighting clients' progress towards O&M goals, and collaboratively planning routes and monitoring clients' independent travel progress.
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Clew3D: Automated Generation of O&M Instructions Using LIDAR-Equipped Smartphones
Certified orientation and mobility specialists (COMS) work with clients who are blind or visually impaired (BVI) to help them travel independently with confidence. Part of this process involves creating a narrative description of a route and using specific techniques to help the client internalize it. We focus on the problem of automatically generating a narrative description of an indoor route based on a recording from a smartphone. These automatically generated narrations could be used in cases where a COMS is not available or to enable clients to independently practice routes that were originally learned with the help of a COMS. Specifically, we introduce Clew3D, a mobile app that leverages LIDAR-equipped iOS devices to identify orientation and mobility (O&M) landmarks and their relative location along a recorded route. The identified landmarks are then used to provide a spoken narration modeled after traditional O&M techniques. Our solution is co-designed with COMS and uses methods and language that they employ when creating route narrations for their clients. In addition to presenting Clew3D, we report the results of an analysis conducted with COMS regarding techniques and terminology used in traditional, in-person O&M instruction. We also discuss challenges posed by vision-based systems to achieve automatic narrations that are reliable. Finally, we provide an example of an automatically generated route description and compare it with the same route provided by a COMS.
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- Award ID(s):
- 2007824
- PAR ID:
- 10358206
- Date Published:
- Journal Name:
- ASSETS '21: The 23rd International ACM SIGACCESS Conference on Computers and Accessibility
- Page Range / eLocation ID:
- 1 to 3
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3441852.3476564
