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Bayesian fusion of hidden Markov models for understanding bimanual movements |
Shamaie, Atid; Sutherland, Alistair
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Understanding hand and body gestures is a part of a wide spectrum of current research in computer vision and human-computer interaction. A part of this can be the recognition of movements in which the two hands move simultaneously to do something or imply a meaning. We present a Bayesian network for fusing hidden Markov models in order to recognise a bimanual movement. A bimanual movement is tracked and segmented by a tracking algorithm. Hidden Markov models are assigned to the segments in order to learn and recognize the partial movement within each segment. A Bayesian network fuses the HMMs in order to perceive the movement of the two hands as a single entity.
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Keyword(s):
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Digital video; belief networks; computer vision; gesture recognition; hidden Markov models; human computer interaction; image segmentation |
Publication Date:
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2004 |
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Type:
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Other |
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Peer-Reviewed:
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Unknown |
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Language(s):
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English |
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Institution:
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Dublin City University |
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Citation(s):
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Shamaie, Atid and Sutherland, Alistair (2004) Bayesian fusion of hidden Markov models for understanding bimanual movements. In: FGR 2004 - 6th IEEE International Conference on Automatic Face and Gesture Recognition, 17-19 May 2004, Seoul, Korea. |
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Publisher(s):
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Institute of Electrical and Electronics Engineers |
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File Format(s):
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application/pdf |
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Related Link(s):
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http://doras.dcu.ie/243/1/ieee_fgr_2004.pdf,
http://dx.doi.org/10.1109/AFGR.2004.1301599 |
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First Indexed:
2009-11-05 02:00:27 Last Updated:
2019-02-09 07:04:50 |
