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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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Velocity profile based recognition of dynamic gestures with discrete Hidden Markov Models,e input data. The segmentation problem is addressed by extracting two velocity profiles from the gesture data and using their extrema as segmentation cues. Gestures are captured with a TUB-SensorGlove. The paper focuses on the description of the gesture recognition method (including data preprocessi
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Video-based sign language recognition using Hidden Markov Models,gner dependent recognition of 262 different signs taken from Sign Language of the Netherlands. For Hidden Markov Modelling a sign is considered a doubly stochastic process, represented by an unobservable state sequence. The observations emitted by the states are regarded as feature vectors, that are
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Corpus of 3D natural movements and sign language primitives of movement,The structure of the corpus is defined for natural pointing movements carried out in different directions, heights and amplitudes. It is then extended to movement primitives habitually used in sign language communication. The corpus is based on movements recorded using an optoelectronic recording sy
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Automatic estimation of body regions from video images, (handshape, hand orientation, location and movement) and non-manual (trunk, head, gaze, facial expression, mouth) parameters. This paper introduces a software module which is as a part of the developed automatic sign language recognition system able to extract relevant body regions from digitised v
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Investigating the role of redundancy in multimodal input systems, communication is to capitalise on the way human beings use speech and gesture in a complementary manner, exploiting the . of information between these modes. Redundant data input via multiple modalities, give considerable scope for the resolution of error and ambiguity. This paper describes impleme
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