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• DiG-Net: Enhancing Human–Robot Interaction through Hyper-Range Dynamic Gesture Recognition in Assistive Robotics

  Eran Bamani Beeri, Eden Nissinman, Avishai Sintov · 2026 · ACM Transactions on Human-Robot Interaction

  DiG-Net (Distance-aware Gesture Network) addresses a fundamental limitation in gesture-controlled assistive robotics: existing dynamic gesture recognition systems work reliably only within about seven metres of the camera, severely constraining their usefulness in real-world…

  assistive robotics · gesture recognition · human-robot interaction · mobility impairment · accessibility

• SignStreamNet: Streaming Sign Language Video-to-Text Translation for Accessibility

  Warfa Ahmed · 2025 · Proceedings of the 27th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2025)

  This paper introduces SignStreamNet, a hybrid neural network architecture designed to translate sign language video into written text in near real-time. The system addresses a fundamental accessibility barrier: over 70 million Deaf and Hard-of-Hearing (DHH) people worldwide rely…

  sign language translation · deaf and hard of hearing · real-time translation · deep learning · computer vision

• Image Recognition Tools for Blind and Visually Impaired Users: An Emphasis on the Design Considerations

  Sandra Fernando, Chiemela Ndukwe, Bal Virdee, Ramzi Djemai · 2025 · ACM Transactions on Accessible Computing

  This research examines the current landscape of image recognition tools (IRT) designed for blind and visually impaired users, evaluating their capabilities against user needs and ISO ergonomic design standards. The authors conducted both a comprehensive review of 21 existing…

  image recognition · computer vision · blind and low vision · assistive technology · AI

• Beyond Sight: Empowering Visually Impaired Users with Audible Graphs

  Wajdi Aljedaani, Uday Kiran Chimpiri, Durgasantosh Gaddam, Vaseem Ahammed Shaik, Yaswitha Karasala, Marcelo M. Eler · 2024 · Proceedings of the 21st International Web for All Conference (W4A)

  This technical note presents a tool designed to make data visualizations accessible to people with visual impairments by converting them into audible and textual representations. The tool addresses a significant gap: while data visualization is central to modern information…

  data visualization · visual impairments · sonification · screen readers · optical character recognition

• 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

• 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

• Accessible PDFs: Applying Artificial Intelligence for Automated Remediation of STEM PDFs

  Felix M. Schmitt-Koopmann, Elaine M. Huang, Alireza Darvishy · 2022 · Proceedings of the 24th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2022)

  This Ph.D. research paper presents a plan to leverage artificial intelligence to automate the remediation of PDF documents from STEM fields, addressing one of the most significant barriers to information access for people with visual impairments. The Portable Document Format…

  PDF accessibility · document remediation · artificial intelligence · STEM accessibility · mathematical formulae

• Deep Learning Methods for Sign Language Translation

  Tejaswini Ananthanarayana, Priyanshu Srivastava, Akash Chintha, Akhil Santha, Brian Landy, Joseph Panaro, Andre Webster, Nikunj Kotecha, Shagan Sah, Thomastine Sarchet, Raymond Ptucha, Ifeoma Nwogu · 2021 · ACM Transactions on Accessible Computing

  This comprehensive study evaluates deep learning methods for translating sign language video directly to spoken/written text—critically, without requiring the intermediate step of gloss-based recognition (manual sign-for-sign transcription). The researchers systematically…

  sign language · machine translation · deep learning · transformer · neural network

• 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

• SoundWatch: Exploring Smartwatch-based Deep Learning Approaches to Support Sound Awareness for Deaf and Hard of Hearing Users

  Dhruv Jain, Hung Ngo, Pratyush Patel, Steven Goodman, Leah Findlater, Jon Froehlich · 2020 · Proceedings of the 22nd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '20)

  This paper presents SoundWatch, a smartwatch-based sound awareness system that uses deep learning to classify environmental sounds in real time and provide visual and haptic notifications to deaf and hard of hearing (DHH) users. The research addresses the finding from prior…

  deaf accessibility · hard of hearing · sound awareness · deep learning · wearable technology

• A Portable Hong Kong Sign Language Translation Platform with Deep Learning and Jetson Nano

  Zhenxing Zhou, Yisiang Neo, King-Shan Lui, Vincent W.L. Tam, Edmund Y. Lam, Ngai Wong · 2020 · Proceedings of the 22nd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS)

  This demonstration paper presents a portable platform for translating Hong Kong Sign Language (HKSL) into spoken language using deep learning and edge computing hardware. The system addresses a significant communication gap: Hong Kong has over 155,000 deaf or hard of hearing…

  sign language recognition · deep learning · edge computing · mobile accessibility · deaf and hard of hearing

• 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

• Deep Learning Compensation of Rotation Errors During Navigation Assistance for People with Visual Impairments or Blindness

  Dragan Ahmetovic, Sergio Mascetti, Cristian Bernareggi, João Guerreiro, Uran Oh, Chieko Asakawa · 2019 · ACM Transactions on Accessible Computing (TACCESS)

  This paper addresses a critical but often overlooked problem in turn-by-turn navigation assistance for people with visual impairments or blindness (VIB): rotation errors at turning points. While much navigation research focuses on improving localization accuracy, this work…

  navigation assistance · visual impairment · blindness · deep learning · turn-by-turn navigation

• Revisiting Blind Photography in the Context of Teachable Object Recognizers

  Kyungjun Lee, Jonggi Hong, Simone Pimento, Ebrima Jarjue, Hernisa Kacorri · 2019 · Proceedings of the 21st International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS)

  This paper introduces a real-time audio-haptic feedback system to help people with visual impairments frame objects in their smartphone camera when training teachable object recognizers. The challenge is that teachable recognizers — which let users train personalized models to…

  blind photography · teachable object recognizer · computer vision · deep learning · visual impairment

• Deep Learning for Automatically Detecting Sidewalk Accessibility Problems Using Streetscape Imagery

  Galen Weld, Esther Jang, Anthony Li, Aileen Zeng, Kurtis Heimerl, Jon E. Froehlich · 2019 · Proceedings of the 21st International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2019)

  This paper presents the first application of deep learning to automatically assess sidewalk accessibility from Google Street View (GSV) panoramas, addressing four types of accessibility problems: curb ramps, missing curb ramps, sidewalk obstructions, and surface problems.…

  computer vision · deep learning · sidewalk accessibility · curb ramps · crowdsourcing

• A TensorFlow-based Assistive Technology System for Users with Visual Impairments

  Davide Mulfari · 2018 · Proceedings of the 15th International Web for All Conference (W4A 2018)

  This extended abstract presents a wearable computer vision system that uses deep learning to classify objects in a blind user’s surroundings and provide audio descriptions via text-to-speech. The system addresses a limitation of smartphone-based object recognition apps: people…

  computer vision · deep learning · blind · visual impairment · wearable technology

• Accessify: An ML Powered Application to Provide Accessible Images on Web Sites

  Shivam Singh, Anurag Bhandari, Nishith Pathak · 2018 · Proceedings of the 15th International Web for All Conference (W4A 2018)

  This demonstration paper presents Accessify, a browser plugin that uses machine learning to automatically generate alternative text descriptions for all images on a website, injecting them into the page’s DOM so screen readers can access them. The system addresses the persistent…

  alternative text · image accessibility · machine learning · browser extension · computer vision

• Multi-view Mouth Renderization for Assisting Lip-reading

  Andrea Britto Mattos, Dario Augusto Borges Oliveira · 2018 · Proceedings of the 15th International Web for All Conference (W4A)

  This paper presents an assistive tool that uses Generative Adversarial Networks (GANs) to enhance video for people who rely on lip-reading. The core problem is that lip-readers generally prefer a frontal view of a speaker's face, but in real-world video the speaker may be…

  lip-reading · hearing impairment · Deaf and hard of hearing · deep learning · generative adversarial networks

• Modeling Expertise in Assistive Navigation Interfaces for Blind People

  Eshed Ohn-Bar, João Guerreiro, Dragan Ahmetovic, Kris M. Kitani, Chieko Asakawa · 2018 · Proceedings of the 23rd International Conference on Intelligent User Interfaces (IUI)

  This short IUI paper asks a question most assistive-navigation research leaves unasked: what happens as a blind user becomes an expert on a route? Existing smartphone guidance apps deliver the same instruction set on a user's tenth trip down a corridor as on their first,…

  blind navigation · indoor navigation · turn-by-turn navigation · visual impairment · blindness

19 results.