Bayesian fusion of hidden Markov models for understanding bimanual movements
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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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.
|Item Type:||Conference or Workshop Item (Paper)|
|Uncontrolled Keywords:||belief networks; computer vision; gesture recognition; hidden Markov models; human computer interaction; image segmentation; |
|Subjects:||Computer Science > Digital video|
|DCU Faculties and Centres:||Research Initiatives and Centres > Centre for Digital Video Processing (CDVP)|
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
|Publisher:||Institute of Electrical and Electronics Engineers|
|Copyright Information:||Copyright © 2004 IEEE. Reprinted from FGR 2004 - 6th IEEE International Conference on Automatic Face and Gesture Recognition. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Dublin City University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to firstname.lastname@example.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.|
|Deposited On:||06 Mar 2008 by DORAS Administrator. Last Modified 06 May 2010 15:39|
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