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Volumn 3, Issue 1, 2007, Pages 4-23

An algorithmic approach for static and dynamic gesture recognition utilising mechanical and biomechanical characteristics

Author keywords

American sign language; ASL; Bioinformatics; Device independent; Dynamic gesture; Gesture recognition; Multi stream human sensor data; Range of motion; Sensor data analysis; Static gesture; User independent

Indexed keywords

ALGORITHM; ARTICLE; BIOMECHANICS; FINGER; GESTURE; HAND MOVEMENT; MATHEMATICAL COMPUTING; MOTIVATION; RANGE OF MOTION; RECOGNITION; SIGN LANGUAGE;

EID: 33947500626     PISSN: 17445485     EISSN: 17445493     Source Type: Journal    
DOI: 10.1504/IJBRA.2007.011832     Document Type: Article
Times cited : (19)

References (15)
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    • Holden, E.J.1    Owens, R.2
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    • Gesture recognition using recurrent neural networks
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    • Murakami, K.1    Taguchi, H.2
  • 12
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    • Hand gesture coding based on experiments using a hand gesture interface device
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    • Takahashi, T.1    Kishino, F.2
  • 14
    • 33947526830 scopus 로고    scopus 로고
    • Yang, J. and Xu, Y. (1994) Hidden Markov Model for Gesture Recognition, Technical Report CMU-RI- TR-94-10, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA.
    • Yang, J. and Xu, Y. (1994) Hidden Markov Model for Gesture Recognition, Technical Report CMU-RI- TR-94-10, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.