HandSight: Supporting Everyday Activities through Touch-Vision
Abstract
We are building and evaluating a new system called HandSight, which is aimed at supporting activities of daily living (ADLs) for people with severe visual impairments by sensing and feeding back non-tactile information about the physical world as it is touched. HandSight consists of tiny cameras and micro-haptic actuators integrated into one or more fingers,computer vision algorithms to support inference and recognition, and a smartwatch for processing, power, and speech output. We have two high-level goals: first, to develop the basic building blocks of an extensible HandSight platform that will support a range of ADL applications. Second, to explore and demonstrate the potential of HandSight through three proof-of-concept applications: reading, dressing, and technology access. In the first year of funded work, we have focused largely on the first goal, including: designing and iterating on physical form factors, developing computer vision algorithms to extract attributes of the physical world and to support on-body interaction for mobile technology accessibility, and experimenting with haptic feedback options to guide the user s finger/hand.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 2015
- Accession Number
- AD1002552
Entities
People
- David Ross
- Jon E. Froehlich
- Leah Findlater
- Rama Chellappa
Organizations
- University of Maryland