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• 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

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