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

TY - JOUR

T1 - Automatic visual recognition of gestures made by motor-impaired computer users

AU - Morrison, K.

AU - McKenna, S.J.

N1 - Copyright 2008 Elsevier B.V., All rights reserved.

PY - 2002

Y1 - 2002

N2 - 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 technoloqies. 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.

AB - 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 technoloqies. 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.

UR - https://www.scopus.com/pages/publications/0036459851

M3 - Article

AN - SCOPUS:0036459851

SN - 1055-4181

VL - 14

SP - 197

EP - 203

JO - Technology and Disability

JF - Technology and Disability

IS - 4

ER -