An integrated approach to the recognition of a wide class of continuous hand gestures

Bhuyan, Manas Kamal, Bora, Prabin Kumar and Ghosh, Debashis (2011) An integrated approach to the recognition of a wide class of continuous hand gestures. International Journal of Pattern Recognition and Artificial Intelligence, 25 2: 227-252. doi:10.1142/S0218001411008592


Author Bhuyan, Manas Kamal
Bora, Prabin Kumar
Ghosh, Debashis
Title An integrated approach to the recognition of a wide class of continuous hand gestures
Journal name International Journal of Pattern Recognition and Artificial Intelligence   Check publisher's open access policy
ISSN 0218-0014
1793-6381
Publication date 2011-03-01
Sub-type Article (original research)
DOI 10.1142/S0218001411008592
Open Access Status DOI
Volume 25
Issue 2
Start page 227
End page 252
Total pages 26
Place of publication Singapore, Singapore
Publisher World Scientific Publishing
Language eng
Subject 1702 Cognitive Sciences
1712 Software
1707 Computer Vision and Pattern Recognition
Formatted abstract
The gesture segmentation is a method that distinguishes meaningful gestures from unintentional movements. Gesture segmentation is a prerequisite stage to continuous gesture recognition which locates the start and end points of a gesture in an input sequence. Yet, this is an extremely difficult task due to both the multitude of possible gesture variations in spatio-temporal space and the co-articulation/movement epenthesis of successive gestures. In this paper, we focus our attention on coping with this problem associated with continuous gesture recognition. This requires gesture spotting that distinguishes meaningful gestures from co-articulation and unintentional movements. In our method, we first segment the input video stream by detecting gesture boundaries at which the hand pauses for a while during gesturing. Next, every segment is checked for movement epenthesis and co-articulation via finite state machine (FSM) matching or by using hand motion information. Thus, movement epenthesis phases are detected and eliminated from the sequence and we are left with a set of isolated gestures. Finally, we apply different recognition schemes to identify each individual gesture in the sequence. Our experimental results show that the proposed scheme is suitable for recognition of continuous gestures having different spatio-temporal behavior.
Keyword Hand gesture
Co-articulation and movement epenthesis
Finite state machine
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: School of Information Technology and Electrical Engineering Publications
 
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