TOWARDS LOW-COST ROBUST AND STABLE HAND TRACKING FOR EXERCISE MONITORING

Rui Liu, Burkhard Wuensche

2010

Abstract

Applications for home-based care are rapidly increasing in importance due to spiraling health care and elderly care costs. An important aspect of home-based care is exercises for rehabilitation and improving general health. However, without caregivers supervising these exercises it is difficult tomonitor them, i.e., to determine whether the exercises have been performed correctly and for the prescribed duration. In this paper we present the first steps toward a computer-based tool for monitoring hand exercises. Hand exercises are important for various diseases such as Parkinson disease. While many algorithms exist for gesture recognition, most of them do require special set-ups and are difficult to use for very inexperienced users in home-based environments. In this paper we present a robust hand region segmentation method which represents the first step toward a hand-tracking algorithm. Our solution requires no calibration and is easily set-up. We evaluate its robustness with regard to complex backgrounds, changes in illuminations, and different hand colours. Our results indicate that the robust hand region segmentation provides a solid foundation for monitoring hand exercises.

References

  1. Chen, Q., Georganas, N., and Petriu, E. (2007). Real-time vision-based hand gesture recognition using haar-like features. In Instrumentation and Measurement Technology Conference Proceedings, 2007. IMTC 2007. IEEE, pages 1-6.
  2. Chong, H. Y., Gortler, S. J., and Zickler, T. (2008). A perception-based color space for illuminationinvariant image processing. ACM Trans. Graph., 27(3):1-7.
  3. Hsu, R.-L., Abdel-Mottaleb, M., and Jain, A. K. (2002). Face detection in color images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24:696- 706.
  4. Kakumanu, P., Makrogiannis, S., and Bourbakis, N. (2007). A survey of skin-color modeling and detection methods. Pattern Recogn., 40(3):1106-1122.
  5. Kovac, J., Peer, P., and Solina, F. (2003). Human skin color clustering for face detection. In EUROCON 2003. Computer as a Tool., volume 2, pages 144-148.
  6. Mahmoudi, F. and Parviz, M. (2006). Visual hand tracking algorithms. In GMAI, pages 228-232.
  7. Stauffer, C. and Grimson, W. (1999). Adaptive background mixture models for real-time tracking. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition, volume 2, page 252.
  8. Stenger, B., Mendona, P. R. S., and Cipolla, R. (2001). Model-based 3d tracking of an articulated hand. Computer Society Conference on Computer Vision and Pattern Recognition, 2:310.
  9. Stenger, B., Thayananthan, A., Torr, P. H. S., and Cipolla, R. (2006). Model-based hand tracking using a hierarchical bayesian filter. IEEE Transactions on Pattern Analysis and Machine Intelligence, 28(9):1372-1384.
  10. UK Department of Health (2009). UK telecare policy and strategy. http://www.pasa.nhs.uk/PASAWeb/ Productsandservices/Telecare/ Governmentpriorities.htm.
  11. Vassili, V. V., Sazonov, V., and Andreeva, A. (2003). A survey on pixel-based skin color detection techniques. In Proc. Graphicon-2003, pages 85-92.
  12. Wang, R. Y. and Popovic, J. (2009). Real-time handtracking with a color glove. In SIGGRAPH 7809: ACM SIGGRAPH 2009 papers, pages 1-8, New York, NY, USA. ACM.
  13. Wessel, J. (2004). The effectiveness of hand exercises for persons with rheumatoid arthritis: A systematic review. Journal of Hand Therapy, 17(2):174-180.
  14. Yang, J., Lu, W., and Waibel, A. (1998). Skin-color modeling and adaptation. In ACCV 7898: Proceedings of the Third Asian Conference on Computer Vision-Volume II, pages 687-694, London, UK. Springer-Verlag.
Download


Paper Citation


in Harvard Style

Liu R. and Wuensche B. (2010). TOWARDS LOW-COST ROBUST AND STABLE HAND TRACKING FOR EXERCISE MONITORING . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2010) ISBN 978-989-674-029-0, pages 263-266. DOI: 10.5220/0002850002630266


in Bibtex Style

@conference{visapp10,
author={Rui Liu and Burkhard Wuensche},
title={TOWARDS LOW-COST ROBUST AND STABLE HAND TRACKING FOR EXERCISE MONITORING},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2010)},
year={2010},
pages={263-266},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002850002630266},
isbn={978-989-674-029-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2010)
TI - TOWARDS LOW-COST ROBUST AND STABLE HAND TRACKING FOR EXERCISE MONITORING
SN - 978-989-674-029-0
AU - Liu R.
AU - Wuensche B.
PY - 2010
SP - 263
EP - 266
DO - 10.5220/0002850002630266