REAL-TIME HAND LOCATING BY MONOCULAR VISION

Li Ding, Jiaxin Wang, Christophe Chaillou, Chunhong Pan

2010

Abstract

The research on real-time hand locating by monocular vision has a considerable challenge that to track hands correctly under occlusion situation. This paper proposes a robust hand locating method which generates a possibility support map by integrating information from color model, position model and motion model. For better accuracy, hands are modeled as ellipses. The PSM depends on both previous model information and the relationship between models. Hand pattern search is then processed on the generated map by two steps which firstly locates the center position of hand and secondly determines the size and orientation. Our experimental results show that the proposed method is efficient under situation that one hand is occluded by the other one. Our current prototype system processes image at 10~14 frames per second.

References

  1. Tamura, S., Kawasaki, S., 1988. Recognition of Signlanguage Motion Images. Pattern Recognition, 21:343- 353.
  2. Starner, T., Pentland, A., 1995. Real-time American Sign Language Recognition from Video using Hidden Markov Models. In Proc. International Symposium on Computer Vision, pp. 265-270.
  3. Hasanuzzaman, M. et al., 2004. Real-time Vision-based Gesture Recognition for human robot interaction. In IEEE International Conference on Robotics and Biomimetics, pp. 413-418.
  4. Han, J. et al., 2006. Automatic Skin Segmentation for Gesture Recognition Combining Region and Support Vector Machine Active Learning. In International Conference on Automatic Face and Gesture Recognition, pp. 237-242.
  5. Lee, M. W., Cohen, I., 2004. Human Upper Body Pose Estimation in Static Images. In European Conference on Computer Vision, pp. 126-138.
  6. Askar, S. et al., 2004. Vision-based Skin-colour Segmentation of Moving Hands for Real-time Applications. In European Conference on Visual Media Production, pp. 79-85.
  7. Comaniciu, D., Ramesh, V., 2000. Mean Shift and Optimal Prediction for Efficient Object Tracking. In International Conference on Image Processing, pp. 70-73.
  8. Bradski, G. R., 1998. Computer Vision Face Tracking for Use in a Perceptual User Interface. Intel Technology Journal 2:12-21.
  9. Vacavant, A., Chateau, T., 2005. Realtime Head and Hands Tracking by Monocular Vision. In IEEE International Conference on Image Processing, pp. II302-5.
  10. Schreer, A. et al., 2005. Real-time Avatar Animation Steered by Live Body Motion. In International Conference on Image Analysis and Processing, pp. 147-154.
  11. Kirubarajan, T., Bar-Shalom Y., 2001. Combined Segmentation and Tracking of Overlapping Objects with Feedback. In IEEE Workshop on Multi-Object Tracking, pp. 77-84.
  12. Coogan, T. et al., 2006. Real Time Hand Gesture Recognition Including Hand Segmentation and Tracking. In International Symposium on Computer Vision, pp. 495-504.
  13. Imagawa, K. et al., 1998. Real-time Tracking of Human Hands from a Sign Language Image Sequence. In Asian Conference on Computer Vision, pp. 698-705.
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Paper Citation


in Bibtex Style

@conference{visapp10,
author={Li Ding and Jiaxin Wang and Christophe Chaillou and Chunhong Pan},
title={REAL-TIME HAND LOCATING BY MONOCULAR VISION},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2010)},
year={2010},
pages={406-412},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002816304060412},
isbn={978-989-674-028-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2010)
TI - REAL-TIME HAND LOCATING BY MONOCULAR VISION
SN - 978-989-674-028-3
AU - Ding L.
AU - Wang J.
AU - Chaillou C.
AU - Pan C.
PY - 2010
SP - 406
EP - 412
DO - 10.5220/0002816304060412


in Harvard Style

Ding L., Wang J., Chaillou C. and Pan C. (2010). REAL-TIME HAND LOCATING BY MONOCULAR VISION . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2010) ISBN 978-989-674-028-3, pages 406-412. DOI: 10.5220/0002816304060412