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• Toward Fairness in AI for People with Disabilities: A Research Roadmap

  Anhong Guo, Ece Kamar, Jennifer Wortman Vaughan, Hanna Wallach, Meredith Ringel Morris · 2020 · SIGACCESS Accessibility and Computing

  This position paper from Microsoft Research presents a systematic risk assessment of how major categories of AI systems may fail or discriminate against people with disabilities, proposing a four-point research roadmap for increasing AI fairness. The authors organize their…

  AI fairness · algorithmic bias · disability · computer vision · speech recognition

• What Is the Point of Fairness? Disability, AI and the Complexity of Justice

  Cynthia L. Bennett, Os Keyes · 2020 · SIGACCESS Accessibility and Computing

  This paper offers a critical disability studies challenge to the dominant "fairness" framing of AI ethics, arguing that fairness is insufficient and potentially harmful when applied to disability, and that justice must be centred instead. Drawing on Anna Lauren Hoffmann's…

  AI fairness · disability justice · critical disability studies · computer vision · autism diagnosis

• Game Changer: Accessible Audio and Tactile Guidance for Board and Card Games

  Gabriella M. Johnson, Shaun K. Kane · 2020 · Proceedings of the 17th International Web for All Conference (W4A)

  This paper presents Game Changer, an augmented workspace system that makes board and card games accessible to blind and visually impaired (BVI) players through a combination of audio descriptions and tactile modifications. The system uses an overhead webcam to track ArUco…

  game accessibility · blind and low vision · board games · tangible interaction · audio description

• Indoor Localization for Visually Impaired Travelers Using Computer Vision on a Smartphone

  Giovanni Fusco, James M. Coughlan · 2020 · Proceedings of the 17th International Web for All Conference (W4A)

  This paper presents a computer vision-based indoor localization system that runs as a real-time app on a conventional iPhone, designed to help blind and visually impaired travelers navigate indoor spaces where GPS is unavailable. The system combines several technologies into a…

  indoor navigation · wayfinding · computer vision · visual impairment · blindness

• A Saliency-Driven Video Magnifier for People with Low Vision

  Ali Selman Aydin, Shirin Feiz, Vikas Ashok, I V Ramakrishnan · 2020 · Proceedings of the 17th International Web for All Conference (W4A)

  This demonstration paper presents SViM (Saliency-driven Video Magnifier), a system that uses deep learning-based visual saliency prediction to automatically guide screen magnification to the most important regions of a video for people with low vision. Screen magnifiers are the…

  low vision · screen magnifier · video accessibility · computer vision · deep learning

• Exploring Collection of Sign Language Datasets: Privacy, Participation, and Model Performance

  Danielle Bragg, Oscar Koller, Naomi Caselli, William Thies · 2020 · Proceedings of the 22nd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2020)

  This paper tackles a fundamental tension in building machine learning systems for marginalized communities: the need for large training datasets versus the privacy risks of collecting data from small, identifiable populations. The authors focus on sign language video collection,…

  sign language · privacy · machine learning · data collection · Deaf culture

• Eyelid Gestures on Mobile Devices for People with Motor Impairments

  Mingming Fan, Zhen Li, Franklin Mingzhe Li · 2020 · Proceedings of the 22nd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2020)

  This paper presents a novel approach to mobile device interaction for people with severe motor impairments: using eyelid gestures detected by the smartphone's front-facing camera. While existing eye-based interaction research has primarily focused on gaze direction and simple…

  motor accessibility · mobile accessibility · input methods · gesture interaction · eye tracking

• Visual Content Considered Private by People Who are Blind

  Abigale Stangl, Kristina Shiroma, Bo Xie, Kenneth R. Fleischmann, Danna Gurari · 2020 · Proceedings of the 22nd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2020)

  This paper presents the first empirical study investigating what types of visual content people who are blind consider private, in the context of their use of Visual Interpreters or Description Services (VIDS) — services like Seeing AI, Aira, Be My Eyes, and TapTapSee that…

  visual accessibility · blindness and low vision · privacy · computer vision · artificial intelligence

• Privacy Considerations of the Visually Impaired with Camera Based Assistive Technologies: Misrepresentation, Impropriety, and Fairness

  Taslima Akter, Tousif Ahmed, Apu Kapadia, Swami Manohar Swaminathan · 2020 · Proceedings of the 22nd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2020)

  This paper investigates the privacy concerns of both visually impaired people (PVIs) and sighted bystanders regarding camera-based assistive technologies like smart glasses (Orcam, Aira, eSight) that can identify people and provide demographic and behavioral information about…

  visual accessibility · blindness and low vision · privacy · AI bias · AI fairness

• AIGuide: An Augmented Reality Hand Guidance Application for People with Visual Impairments

  Nelson Daniel Troncoso Aldas, Sooyeon Lee, Chonghan Lee, Mary Beth Rosson, John M. Carroll, Vijaykrishnan Narayanan · 2020 · Proceedings of the 22nd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2020)

  This paper presents AIGuide, a self-contained offline iOS smartphone application that uses augmented reality (ARKit) to help people with visual impairments locate, navigate to, and pick up objects in their surroundings. Unlike existing object detection apps (Seeing AI, Aipoly)…

  visual accessibility · augmented reality · blindness and low vision · mobile accessibility · computer vision

• Designing and Evaluating Head-based Pointing on Smartphones for People with Motor Impairments

  Muratcan Cicek, Ankit Dave, Wenxin Feng, Michael Xuelin Huang, Julia Katherine Haines, Jeffry Nichols · 2020 · Proceedings of the 22nd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '20)

  This paper presents a calibration-free head-based pointing (HBP) system for Android smartphones that uses the standard front-facing camera to enable people with motor impairments to control an on-screen cursor through head movements. The system was designed by a team including…

  motor accessibility · head tracking · alternative input · mobile accessibility · Fitts law

• Computer Vision-based Methodology to Support AAC

  Rúbia Eliza de Oliveira Schultz Ascari, Roberto Pereira, Luciano Silva · 2020 · ACM Transactions on Accessible Computing

  This paper presents a methodology for supporting augmentative and alternative communication (AAC) through personalized gestural interaction using computer vision and machine learning. The authors developed the PGCA (Personal Gesture Communication Assistant) system, which enables…

  AAC · augmentative and alternative communication · computer vision · machine learning · gesture recognition

• Twitter A11y: A Browser Extension to Make Twitter Images Accessible

  Cole Gleason, Amy Pavel, Emma McCamey, Christina Low, Patrick Carrington, Kris M. Kitani, Jeffrey P. Bigham · 2020 · CHI Conference on Human Factors in Computing Systems

  This paper presents Twitter A11y, a browser extension designed to address the widespread lack of alternative text on images posted to Twitter. The authors note that while around 12% of Twitter content consists of images, only 0.1% of those images include user-provided alt text,…

  social media accessibility · alternative text · screen readers · image accessibility · optical character recognition

• ReCog: Supporting Blind People in Recognizing Personal Objects

  Dragan Ahmetovic, Daisuke Sato, Uran Oh, Tatsuya Ishihara, Kris Kitani, Chieko Asakawa · 2020 · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

  ReCog is a smartphone application designed to help blind users recognize their own personal objects — items like specific clothing, handmade goods, medicines, or family photos that cannot be identified by general-purpose recognizers such as Seeing AI or TapTapSee. The authors…

  visual impairment · blindness · object recognition · computer vision · deep learning

14 results.