People with Visual Impairment Training Personal Object Recognizers: Feasibility and Challenges

By Hernisa Kacorri, Kris M. Kitani, Jeffrey P. Bigham, C. Asakawa. 2017

136 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Cognitive Neuroscience, Computer Vision and Pattern Recognition, Human-Computer Interaction

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Citations in the corpus

ORBIT: A Real-World Few-Shot Dataset for Teachable Object Recognition (2021, background): “of possible applications, from recognizers that rapidly adapt to novel objects [20, 18], medical imageing tools that learn to classify/segment from a few scans [53, 27], and techniques that render talking faces [52] and 3D scenes/objects [9] from a few images.”
Teachable machines for accessibility (2017, methodology): “By analyzing the labels and photos from all the participants in [10] we observed:”
Future Person Localization in First-Person Videos (2017, unknown): “alized object recognition [15].”
Hands Holding Clues for Object Recognition in Teachable Machines (2019, methodology): “Subsequently, models trained by users with visual impairments have shown promise given well-framed training examples [4, 36, 62].”
Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors (2021, background): “Teachable object recognisers [30, 37] provide a way for people to “teach” an AI system about a new object that they may want to identify, by providing training examples themselves.”
Toward User-Driven Sound Recognizer Personalization with People Who Are d/Deaf or Hard of Hearing (2021, background): “, [41, 49, 69]) to support blind and low-vision people in training personal object recognizers, we explore the parallel question of how DHH people can train personal sound recognizers.”
What Do We Mean by “Accessibility Research”?: A Literature Survey of Accessibility Papers in CHI and ASSETS from 1994 to 2019 (2021, background): “[70], for example, compared images taken by blind and sighted users to “explore the benefits of having a sighted person training a blind user’s personal object recognizer.”