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• The Future of Urban Accessibility: The Role of AI

  Jon E. Froehlich, Chu Li, Maryam Hosseini, Fabio Miranda, Andres Sevtsuk, Yochai Eisenberg · 2024 · Proceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '24)

  This workshop paper examines the emerging role of artificial intelligence in designing equitable and accessible cities, transportation systems, and navigation tools for people with disabilities. The authors — spanning HCI, urban planning, public health, and accessibility…

  urban accessibility · artificial intelligence · smart cities · autonomous vehicles · pedestrian infrastructure

• Vision-Based Assistive Technologies for People with Cerebral Visual Impairment: A Review and Focus Study

  Bhanuka Gamage, Leona Holloway, Nicola McDowell, Thanh-Toan Do, Nicholas Price, Arthur Lowery, Kim Marriott · 2024 · ASSETS '24: Proceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility

  This paper reveals a significant research gap in assistive technology for people with cerebral visual impairment (CVI) through a scoping review and focus studies. CVI is caused by damage to the brain's visual processing centres rather than the eyes themselves, making it…

  cerebral visual impairment · CVI · vision-based assistive technology · computer vision · augmented reality

• Understanding How Blind Users Handle Object Recognition Errors: Strategies and Challenges

  Jonggi Hong, Hernisa Kacorri · 2024 · ASSETS '24: Proceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility

  This paper investigates how blind and low-vision users interact with object recognition systems, specifically focusing on how they identify and handle recognition errors. While object recognition technologies powered by computer vision and machine learning have enormous…

  blind users · object recognition · AI errors · computer vision · camera-based assistive technology

• Using Convolutional Neural Networks for Visual Sign Language Recognition: Towards a system that provides instant feedback to learners of sign language

  Rami Aldahir, Ronald R. Grau · 2024 · Proceedings of the 21st International Web for All Conference (W4A)

  This short paper presents a prototype system that uses computer vision and a convolutional neural network (CNN) to recognize finger-spelled letters in British Sign Language (BSL), providing real-time feedback to learners. The system addresses a gap in sign language instruction:…

  sign language · British Sign Language · computer vision · deep learning · fingerspelling

• ImageExplorer Deployment: Understanding Text-Based and Touch-Based Image Exploration in the Wild

  Ruolin Xu, Yuxuan Cai, Shuying Hou, Yu-Jung Chang, Anhong Guo · 2024 · Proceedings of the 21st International Web for All Conference (W4A)

  This paper presents the real-world deployment and evaluation of ImageExplorer, an iOS application that enables blind and low-vision users to explore images through two complementary modalities: text-based sequential exploration and touch-based spatial exploration. The app was…

  image accessibility · screen readers · touch exploration · blind users · image description

• Co-design of Robotic Technology with Care Home Residents and Care Workers

  Helena Anna Frijns, Ralf Vetter, Matthias Hirschmanner, Reinhard Grabler, Laura Vogel, Sabine Theresia Koeszegi · 2024 · Proceedings of the 17th International Conference on PErvasive Technologies Related to Assistive Environments (PETRA)

  This paper documents a co-design workshop series conducted at two care homes in Austria, involving 25 participants: 13 care workers (mean age 43.5) and 12 care home residents (mean age 80.6). The research question was whether introducing technology components — rather than…

  co-design · participatory design · older adults · care homes · robotics

• UIClip: A Data-driven Model for Assessing User Interface Design

  Jason Wu, Yi-Hao Peng, Xin Yue Amanda Li, Amanda Swearngin, Jeffrey P. Bigham, Jeffrey Nichols · 2024 · Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology (UIST '24)

  This paper introduces UIClip, a computational model that automatically assesses UI design quality and visual relevance from a screenshot and natural language description. Built on OpenAI's CLIP B/32 architecture (151 million parameters), UIClip is fine-tuned on a novel…

  UI design · machine learning · design quality assessment · computer vision · CLIP

• Towards Automated Accessibility Report Generation for Mobile Apps

  Amanda Swearngin, Jason Wu, Xiaoyi Zhang, Esteban Gomez, Jen Coughenour, Rachel Stukenborg, Bhavya Garg, Greg Hughes, Adriana Hilliard, Jeffrey P. Bigham, Jeffrey Nichols · 2024 · ACM Transactions on Computer-Human Interaction

  This paper presents a system for automatically generating whole-app accessibility reports for mobile apps, addressing key limitations of existing accessibility scanning tools. The work begins with formative interviews with eight accessibility QA professionals at a large…

  automated testing · accessibility testing · mobile accessibility · app crawling · machine learning

• Snap&Nav: Smartphone-based Indoor Navigation System For Blind People via Floor Map Analysis and Intersection Detection

  Masaya Kubota, Masaki Kuribayashi, Seita Kayukawa, Hironobu Takagi, Chieko Asakawa, Shigeo Morishima · 2024 · Proceedings of the ACM on Human-Computer Interaction (MobileHCI)

  Snap&Nav is a smartphone-based indoor navigation system for blind travellers that works in any building with a visible floor map, without requiring the building owner to pre-build a digital map, install BLE beacons, or deploy any other localisation infrastructure. The authors…

  blindness and low vision · indoor navigation · wayfinding · map-less navigation · intersection detection

9 results.