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 - http://www.scopus.com/inward/record.url?scp=0036459851&partnerID=8YFLogxK
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 -