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Bien, Zeungnam
Intelligent Robot Control System Lab
Research Interests
  • Intelligent Control
  • Learning System Methodologies
  • Assistive Robotics
  • Smart Home System

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Recognition of continuous Korean sign language using gesture tension model and soft computing technique

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Title
Recognition of continuous Korean sign language using gesture tension model and soft computing technique
Author
Kim, JBBien, Zeungnam
Keywords
Continuous gesture;  Gesture recognition;  Sign language recognition;  Gesture tension model;  Soft computing
Issue Date
2004-05
Publisher
IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG
Citation
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, v.E87D, no.5, pp.1265 - 1270
Abstract
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.
URI
https://scholarworks.unist.ac.kr/handle/201301/9222
ISSN
0916-8532
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EE_Journal Papers
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