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Deploying VizLens: Characterizing User Needs, Preferences, and Challenges of Physical Interfaces Usage in the Wild

Published: 22 October 2023 Publication History

Abstract

Blind or Visually Impaired (BVI) people often encounter flat, inaccessible interfaces. Current solutions lack cost-effectiveness, portability, and robustness in real-world settings. We introduce VizLens, a fully-automated, full-stack mobile application powered by computer vision algorithms. The system is deployed and publicly available through the Apple App Store (https://vizlens.org/). From May to August 2023, we had 665 users, who uploaded 1,320 interface images. We aim to use it to study usage patterns and possible challenges BVI users may encounter with flat interfaces through a large-scale study in real-world settings. With in-depth analysis of user data and activity logs, our study will provide insights into BVI users’ interface interests, preferred assistance modes, and potential challenges due to system limitations or users’ diverse abilities. Our goal is to enhance the understanding of how BVI users interact with inaccessible, flat interfaces, and inform future assistive technology design.

References

[1]
Herbert Bay, Tinne Tuytelaars, and Luc Van Gool. 2006. SURF: Speeded Up Robust Features. In Computer Vision – ECCV 2006, Aleš Leonardis, Horst Bischof, and Axel Pinz (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 404–417.
[2]
Google Cloud. 2023. Google Cloud Vision. https://cloud.google.com/vision
[3]
Aira Tech Corp. 2022. Aira. https://aira.io/
[4]
Be My Eyes. 2023. Be My Eyes. https://www.bemyeyes.com/
[5]
Giovanni Fusco, Ender Tekin, R.E. Ladner, and James Coughlan. 2014. Using Computer Vision to Access Appliance Displays. ASSETS / Association for Computing Machinery. ACM Conference on Assistive Technologies 2014. https://doi.org/10.1145/2661334.2661404
[6]
Anhong Guo, Xiang ‘Anthony’ Chen, Haoran Qi, Samuel White, Suman Ghosh, Chieko Asakawa, and Jeffrey P. Bigham. 2016. VizLens: A Robust and Interactive Screen Reader for Interfaces in the Real World. In Proceedings of the 29th Annual Symposium on User Interface Software and Technology (Tokyo, Japan) (UIST ’16). Association for Computing Machinery, New York, NY, USA, 651–664. https://doi.org/10.1145/2984511.2984518
[7]
Anhong Guo, Jeeeun Kim, Xiang ‘Anthony’ Chen, Tom Yeh, Scott E. Hudson, Jennifer Mankoff, and Jeffrey P. Bigham. 2017. Facade: Auto-Generating Tactile Interfaces to Appliances. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (Denver, Colorado, USA) (CHI ’17). Association for Computing Machinery, New York, NY, USA, 5826–5838. https://doi.org/10.1145/3025453.3025845
[8]
Anhong Guo, Junhan Kong, Michael Rivera, Frank F. Xu, and Jeffrey P. Bigham. 2019. StateLens: A Reverse Engineering Solution for Making Existing Dynamic Touchscreens Accessible. In Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology (New Orleans, LA, USA) (UIST ’19). Association for Computing Machinery, New York, NY, USA, 371–385. https://doi.org/10.1145/3332165.3347873
[9]
Apple Machine Learning. 2023. Apple Machine Learning Vision. https://developer.apple.com/documentation/vision/
[10]
Chen Liang, Yasha Iravantchi, Thomas Krolikowski, Ruijie Geng, Alanson P. Sample, and Anhong Guo. 2023. BrushLens: Hardware Interaction Proxies for Accessible Touchscreen Interface Actuation. In Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology (San Francisco, CA, USA) (UIST ’23). Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/3586183.3606730
[11]
Tim Morris, Paul Blenkhorn, Luke Crossey, Quang Ngo, Martin Ross, David Werner, and Christina Wong. 2006. Clearspeech: A Display Reader for the Visually Handicapped. IEEE Transactions on Neural Systems and Rehabilitation Engineering 14, 4 (2006), 492–500. https://doi.org/10.1109/TNSRE.2006.881538
[12]
Vladimir Vezhnevets, Vassili Sazonov, and Alla Andreeva. 2004. A Survey on Pixel-Based Skin Color Detection Techniques. (03 2004).

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      cover image ACM Conferences
      ASSETS '23: Proceedings of the 25th International ACM SIGACCESS Conference on Computers and Accessibility
      October 2023
      1163 pages
      ISBN:9798400702204
      DOI:10.1145/3597638
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Published: 22 October 2023

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      Author Tags

      1. accessibility
      2. appliances
      3. blind
      4. computer vision
      5. deployment
      6. physical interfaces
      7. visually impaired people

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