An Efficient Application of Gesture Recognition from a 2D Camera for Rehabilitation of Patients with Impaired Dexterity
G. Ushaw, E. Ziogas, J. Eyre, G. Morgan
2013
Abstract
An efficient method for utilising a 2D camera to recognise hand gestures in 3D space is described. The work is presented within the context of a recuperation aid for younger children with impaired movement of the upper limbs on a standard Android tablet device. The hand movement recognition is achieved through attaching brightly coloured models to the child’s fingers, providing easily trackable elements of the image. The application promotes repeated use of specific hand skills identified by the medical profession to stimulate and assess rehabilitation of patients with impaired upper limb dexterity.
References
- Bowden, R., Windridge, D., Kadir, T., Zisserman, A., and Bradyi, M. (2004). A linguistic feature vector for the visual interpretation of sign language. Proc. 8th Eur. Conf. Comput. Vis.
- Chien, C. W., Brown, T., and McDonaldi, R. (2009). A framework of children's hand skills for assessment and intervention. Child care health and development., (35):873-884.
- Hong, P., Turk, M., and Huangi, T. (2000). Gesture modeling and recognition using finite state machinesl. Proc. 4th IEEE Int. Conf. Autom. Face Gesture recogn.
- Lillestrand, R. (1972). Techniques for change detection. IEEE Trans. Comput, 21(7):654-659.
- Mitra, S. and Acharya, T. (2007). Gesture recognition: a survey. IEEE Transactions on Systems, Man and Cybernetics, 37(3):311-324.
- Radke, R. J., Andra, S., Al-Kofah, O., and Roysam, B. (2005). Image change detection algorithms: a systematic survey. IEEE Transactions on Image Processing, 14(3):394-307.
- Rosin, P. (2002). Thresholding for change detection. Comput. Vis. Image Understanding, 86(2):79-95.
- Starner, T. and Pentland, A. (1996). Real-time american sign language recognition from video using hidden markov models.
- Yamato, J., Ohya, J., and Ishii, K. (1992). Recognizing human action in time sequential images using hidden markov model. Proc. IEEE Int. Conf. Comput. Vis. Pattern recogn., pages 379-385.
- Ziogas, E., Ushaw, G., Eyre, J., and Morgan, G. (2012). http://homepages.cs.ncl.ac.uk/2010- 11/games/tyney/videos/.
- Zitova, B. and Flusser, J. (2003). Image registration methods: a survey. Image Vis. Comput, 21:9771000.
Paper Citation
in Harvard Style
Ushaw G., Ziogas E., Eyre J. and Morgan G. (2013). An Efficient Application of Gesture Recognition from a 2D Camera for Rehabilitation of Patients with Impaired Dexterity . In Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2013) ISBN 978-989-8565-37-2, pages 315-318. DOI: 10.5220/0004190103150318
in Bibtex Style
@conference{healthinf13,
author={G. Ushaw and E. Ziogas and J. Eyre and G. Morgan},
title={An Efficient Application of Gesture Recognition from a 2D Camera for Rehabilitation of Patients with Impaired Dexterity},
booktitle={Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2013)},
year={2013},
pages={315-318},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004190103150318},
isbn={978-989-8565-37-2},
}
in EndNote Style
TY - CONF
JO - Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2013)
TI - An Efficient Application of Gesture Recognition from a 2D Camera for Rehabilitation of Patients with Impaired Dexterity
SN - 978-989-8565-37-2
AU - Ushaw G.
AU - Ziogas E.
AU - Eyre J.
AU - Morgan G.
PY - 2013
SP - 315
EP - 318
DO - 10.5220/0004190103150318