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• Case Study: In-the-Field Accessibility Information Collection Using Gamification

  Akihiro Miyata, Kazuki Okugawa, Yusaku Murayama, Akihiro Furuta, Keihiro Ochiai, Yuko Murayama · 2023 · Proceedings of the 20th International Web for All Conference (W4A '23)

  This study introduces and evaluates a crowdsourcing platform designed to collect real-world accessibility information for constructing accessibility maps that support people with mobility disabilities. Accessibility maps are critical for safe navigation by wheelchair users and…

  crowdsourcing · gamification · accessible maps · physical accessibility · pedestrian infrastructure

• A Demonstration of RASSAR: Room Accessibility and Safety Scanning in Augmented Reality

  Xia Su, Kaiming Cheng, Han Zhang, Jaewook Lee, Wyatt Olson, Jon E. Froehlich · 2023 · Proceedings of the 25th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS)

  This demo paper introduces RASSAR (Room Accessibility and Safety Scanning in Augmented Reality), a mobile AR application that semi-automatically identifies, localizes, and visualizes indoor accessibility and safety issues using iPhone LiDAR sensors and real-time computer vision.…

  augmented reality · computer vision · indoor accessibility · object detection · LiDAR

• Understanding Personalized Accessibility through Teachable AI: Designing and Evaluating Find My Things for People who are Blind or Low Vision

  Cecily Morrison, Martin Grayson, Rita Faia Marques, Daniela Massiceti, Camilla Longden, Linda Wen, Edward Cutrell · 2023 · Proceedings of the 25th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '23)

  This paper from Microsoft Research presents Find My Things, one of the first fully realized end-to-end teachable AI applications for accessibility. The app allows people who are blind or low vision to teach their phone to recognize personal objects — keys, earbuds, lip balm,…

  teachable AI · object recognition · blind and low vision · personalization · few-shot learning

• The Sem-Lex Benchmark: Modeling ASL Signs and their Phonemes

  Lee Kezar, Jesse Thomason, Naomi Caselli, Zed Sehyr, Elana Pontecorvo · 2023 · ASSETS '23: Proceedings of the 25th International ACM SIGACCESS Conference on Computers and Accessibility

  This paper introduces the Sem-Lex Benchmark, the largest curated dataset of its kind for American Sign Language (ASL) isolated sign recognition, containing over 84,000 videos of isolated sign productions from 41 deaf ASL signers. The dataset addresses two critical barriers in…

  sign language recognition · American Sign Language · machine learning · phonology · dataset

• What do Blind and Low-Vision People Really Want from Assistive Smart Devices? Comparison of the Literature with a Focus Study

  Bhanuka Gamage, Thanh-Toan Do, Nicholas Seow Chiang Price, Arthur Lowery, Kim Marriott · 2023 · Proceedings of the 25th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '23)

  This paper investigates whether the tasks and devices explored by researchers developing AI-based assistive smart devices actually align with what blind and low-vision (BLV) people want. The authors conducted a three-part study combining a scoping literature review with…

  blind and low vision · assistive technology · smart devices · computer vision · wearable technology

• TouchPilot: Designing a Guidance System that Assists Blind People in Learning Complex 3D Structures

  Xiyue Wang, Seita Kayukawa, Hironobu Takagi, Chieko Asakawa · 2023 · Proceedings of the 25th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2023)

  This paper introduces TouchPilot, a step-by-step guidance system designed to help blind people independently learn complex 3D structures through interactive 3D printed models (I3Ms). While existing I3Ms allow blind users to trigger audio labels by pointing at specific elements,…

  3D printed models · tactile learning · blindness · computer vision · guidance systems

• VisPhoto: Photography for People with Visual Impairments via Post-Production of Omnidirectional Camera Imaging

  Naoki Hirabayashi, Masakazu Iwamura, Zheng Cheng, Kazunori Minatani, Koichi Kise · 2023 · Proceedings of the 25th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS)

  This paper introduces VisPhoto, a novel photography system that fundamentally reimagines how people with visual impairments (PVI) take photographs. Rather than helping users aim a conventional camera at a target in real-time (the dominant approach in prior work), VisPhoto…

  visual impairment · blindness · photography · computer vision · object detection

• Machine Generation of Audio Description for Blind and Visually Impaired People

  Virgínia P. Campos, Tiago M. U. de Araújo, Guido L. de Souza Filho, Luiz M. G. Gonçalves · 2023 · ACM Transactions on Accessible Computing

  This paper presents an extension to CineAD, a system for automatically generating audio descriptions (AD) for videos. The authors address a critical accessibility gap: most videos, films, and cultural programming lack audio descriptions, leaving blind and visually impaired (BVI)…

  audio description · blind and visually impaired · computer vision · machine learning · video accessibility

• Never-ending Learning of User Interfaces

  Jason Wu, Rebecca Krosnick, Eldon Schoop, Amanda Swearngin, Jeffrey P. Bigham, Jeffrey Nichols · 2023 · Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology (UIST)

  This paper introduces the Never-ending UI Learner, an automated system that continuously crawls real mobile applications to learn semantic properties of user interfaces. The system addresses a fundamental limitation of current approaches to UI understanding: most machine…

  machine learning · mobile accessibility · UI semantics · automated crawling · tappability

• WebUI: A Dataset for Enhancing Visual UI Understanding with Web Semantics

  Jason Wu, Siyan Wang, Siman Shen, Yi-Hao Peng, Jeffrey Nichols, Jeffrey P. Bigham · 2023 · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

  This paper introduces WebUI, a large-scale dataset of approximately 400,000 web pages automatically crawled and paired with visual, semantic, and stylistic metadata extracted from the browser engine. The dataset addresses a critical bottleneck in UI understanding research:…

  machine learning · computer vision · UI modeling · web semantics · transfer learning

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