Please use this identifier to cite or link to this item:
|Title:||Understanding gestures with systematic variations in movement dynamics|
|Authors:||Ong, S.C.W. |
Sign language recognition
|Citation:||Ong, S.C.W., Ranganath, S., Venkatesh, Y.V. (2006-09). Understanding gestures with systematic variations in movement dynamics. Pattern Recognition 39 (9) : 1633-1648. ScholarBank@NUS Repository. https://doi.org/10.1016/j.patcog.2006.02.010|
|Abstract:||Sign language communication includes not only lexical sign gestures but also grammatical processes which represent inflections through systematic variations in sign appearance. We present a new approach to analyse these inflections by modelling the systematic variations as parallel channels of information with independent feature sets. A Bayesian network framework is used to combine the channel outputs and infer both the basic lexical meaning and inflection categories. Experiments using a simulated vocabulary of six basic signs and five different inflections (a total of 20 distinct gestures) obtained from multiple test subjects yielded 85.0% recognition accuracy. We also propose an adaptation scheme to extend a trained system to recognize gestures from a new person by using only a small set of data from the new person. This scheme yielded 88.5% recognition accuracy for the new person while the unadapted system yielded only 52.6% accuracy. © 2006 Pattern Recognition Society.|
|Source Title:||Pattern Recognition|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Jun 19, 2018
WEB OF SCIENCETM
checked on Jun 11, 2018
checked on Feb 27, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.