Automatic visual recognition of gestures made by motor-impaired computer users

Issue title: Bringing AT Professionals Together

Guest editors: Jane Seale and Alan Turner-Smith

Article type: Research Article

Authors: Morrison, K. | McKenna, S.J.

Affiliations: Department of Applied Computing, University of Dundee, Dundee DD1 4HN, Scotland, UK. Tel.: +44 1382 344146; Fax: +44 1382 345509; E-mail: [email protected], [email protected]

Abstract: The use of gesture recognition as a means of Human Computer Interaction for physically disabled users is discussed. The ability of motor-impaired computer users to make distinct, recognisable gestures is not exploited by current assistive technologies. A real-time computer vision system for recognition of one- and two-handed gestures defined by such users is described. An investigation into the feasibility of real-time, unencumbered recognition of gestures defined by motor-impaired users by means of Hidden Markov Models, trained with relatively few examples is performed and reported. Different feature vectors are compared and the trade-off between accuracy and training set size is explored: an important issue for such interactively trained systems.

DOI: 10.3233/TAD-2002-14408

Journal: Technology and Disability, vol. 14, no. 4, pp. 197-203, 2002