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• 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

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