Recognition of Continuous Korean Sign Language Using Gesture Tension Model and Soft Computing Technique

Jung-Bae KIM  Zeungnam BIEN  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E87-D   No.5   pp.1265-1270
Publication Date: 2004/05/01
Online ISSN: 
DOI: 
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Human-computer Interaction
Keyword: 
sign language recognition,  gesture recognition,  continuous gesture,  gesture tension model,  soft computing.,  

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Summary: 
We present a method for recognition of continuous Korean Sign Language (KSL). In the paper, we consider the segmentation problem of a continuous hand motion pattern in KSL. For this, we first extract sign sentences by removing linking gestures between sign sentences. We use a gesture tension model and fuzzy partitioning. Then, each sign sentence is disassembled into a set of elementary motions (EMs) according to its geometric pattern. The hidden Markov model is adopted to classify the segmented individual EMs.