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Titlebook: Gesture and Sign Language in Human-Computer Interaction; International Gestur Ipke Wachsmuth,Martin Fröhlich Conference proceedings 1998 Sp

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书目名称Gesture and Sign Language in Human-Computer Interaction
副标题International Gestur
编辑Ipke Wachsmuth,Martin Fröhlich
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Gesture and Sign Language in Human-Computer Interaction; International Gestur Ipke Wachsmuth,Martin Fröhlich Conference proceedings 1998 Sp
描述This book presents the thoroughly refereed post-workshop proceedings of an International Workshop on Gesture and Sign Language in Human-Computer Interaction held in Bielefeld, Germany, in 1997. .The book presents 25 revised papers together with two invited lectures. Recently, gesture and sign language have become key issues for advanced interface design in the humanization of computer interaction: AI, neural networks, pattern recognition, and agent techniques are having a significant impact on this area of research and development. The papers are organized in sections on semiotics for gesture movement, hidden Markov models, motion analysis and synthesis, multimodal interfaces, neural network methods, and applications.
出版日期Conference proceedings 1998
关键词3D; Performance; algorithms; anthropomorph; artificial intelligence; cognition; hidden Markov model; human-
版次1
doihttps://doi.org/10.1007/BFb0052983
isbn_softcover978-3-540-64424-8
isbn_ebook978-3-540-69782-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 1998
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https://doi.org/10.1007/978-3-642-41763-4 integration step the first-level symbols are integrated to second-level symbols describing a whole gesture. Second-level symbolic gesture descriptions are the entities which can be integrated with speech tokens to form multi-modal utterances.
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Gerhard Zauner,Reinhold Jahn,Karl Stahra virtual environment are discussed with respect to a required functionality, the implementation of a specific gesture detection module for distant pointing recognition is described, and the whole system design is tested for its task adequacy.
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Video-based sign language recognition using Hidden Markov Models,e feature vector on the recognition rate and thirdly an approach for the recognition of connected signs. The system achieves recognition rates up to 94% for isolated signs and 73% for a reduced vocabulary of connected signs.
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