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Published Articles >> Table of Contents >> Abstract
IEEE International Workshop on Analysis and Modeling of Faces and Gestures
p. 181
Extraction of 3D Hand Shape and Posture from Image Sequences for Sign Language Recognition
Holger Fillbrandt, Aachen University (RWTH), Germany
Suat Akyol, Aachen University (RWTH), Germany
Karl-Friedrich Kraiss, Aachen University (RWTH), Germany
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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AMFG.2003.1240841
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| Abstract |
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We propose a novel method for extracting natural
hand parameters from monocular image sequences. The
purpose is to improve a vision-based sign language
recognition system by providing detail information about
the finger constellation and the 3D hand posture.
Therefor the hand is modelled by a set of 2D appearance
models, each representing a limited variation range of 3D
hand shape and posture. The single models are linked to
each other according to the natural neighbourhood of the
corresponding hand status. During an image sequence,
necessary model transitions are executed towards one of
the current neighbour models. The natural hand
parameters are calculated from the shape and texture
parameters of the current model, using a relation
estimated by linear regression. The method is robust
against large differences between subsequent frames and
also against poor image quality. It can be implemented in
real-time and offers good properties to handle occlusion
and partly missing image information.
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 Additional Information
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Citation:
Holger Fillbrandt, Suat Akyol, Karl-Friedrich Kraiss,
"Extraction of 3D Hand Shape and Posture from Image Sequences for Sign Language Recognition,"
amfg,
p. 181,
IEEE International Workshop on Analysis and Modeling of Faces and Gestures,
2003
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