ReCog: Supporting Blind People in Recognizing Personal Objects
Dragan Ahmetovic, Daisuke Sato, Uran Oh, Tatsuya Ishihara, Kris Kitani, Chieko Asakawa
Abstract
We present ReCog, a mobile app that enables blind users to recognize objects by training a deep network with their own photos of such objects. This functionality is useful to differentiate personal objects, which cannot be recognized with pre-trained recognizers and may lack distinguishing tactile features. To ensure that the objects are well-framed in the captured photos, ReCog integrates a camera-aiming guidance that tracks target objects and instructs the user through verbal and sonification feedback to appropriately frame them.
Topics & Concepts
SonificationComputer scienceFrame (networking)Artificial intelligenceHuman–computer interactionMobile deviceComputer visionMultimediaWorld Wide WebTelecommunicationsTactile and Sensory InteractionsAdvanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning