GESTURE RECOGNITION - Control of a Computer with Natural Head Movements

Kornél Bertók, Attila Fazekas

Abstract

The topic of this article is a basic research considering a human-computer interaction. The system is still under construction, however its basis – facial features tracking and head pose estimation – is ready to use, thus it could bring a head gesture controlled system into reality. We present an approach to control applications with head movements. We construct an Active Appearance Model (AAM) for facial feature extraction. Based on the landmarks of AAM shape, the head pose is modelled in the three-dimensional space by three Euler angles of rotation around the three axes orthogonal to each other, and three orthogonal translation directions. Regarding all the above mentioned facts, we are capable of recognizing gestures like head pointing, nodding, and shaking, blinking, opening and closing mouth.

References

  1. Microsoft Corporation: Bing Maps. In: Bing Maps. (Accessed 2011) Available at: http://www.bing.com/ maps/
  2. Edwards, G., Taylor, C., Cootes, T.: Active appearance models. IEEE Transactions on Pattern Analysis and Machine Intelligence 23(6), 681-685 (2001)
  3. DeMenthon, D. and Davis, L.: Model-based object pose in 25 lines of code. International Journal of Computer Vision 15(1-2), 123-141 (June 1995)
  4. Meynet, J., Arsan, T., Mota, J., Thiran, J.: Fast multiview tracking with pose estimation. 7th IEEE-RAS International Conference on Humanoid Robots, 330-335 (2009)
  5. Dornaika, F. and Ahlberg, J.: Fast and reliable active appearance model search for 3D face tracking. IEEE Transactions on Systems, Man, and Cybernetics, Part B 34(4), 1838-1853 (2004)
  6. Kass, M., Witkin, A., Terzopoulos, D.: Snakes: Active contour models. International Journal of Computer Vision 1(4), 321-331 (1988)
  7. Cootes, T., Taylor, C., Cooper, D., Graham, J.: Active shape models - their training and application. Computer Vision and Image Understanding 61(1), 38-59 (1995)
  8. Goodall, C.: Procrustes methods in the statistical analysis of shape. Journal of the Royal Statistical Society, Series B 53(2), 285-339 (1991)
  9. Lucas, B. and Kanade, T.: An Iterative Image Registration Technique with an Application to Stereo Vision. International Joint Conference on Artificial Intelligence, 674-679 (1981)
  10. Tomasi, C. and Kanade, T.: Detection and Tracking of Point Features. Technical Report CMU-CS-91-132, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA (1991 April)
  11. Willow Garage: OpenCV. In: Open Source Computer Vision Library. (Accessed 2010) Available at: http://opencv.willowgarage.com
Download


Paper Citation


in Harvard Style

Bertók K. and Fazekas A. (2012). GESTURE RECOGNITION - Control of a Computer with Natural Head Movements . In Proceedings of the International Conference on Computer Graphics Theory and Applications and International Conference on Information Visualization Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2012) ISBN 978-989-8565-02-0, pages 527-530. DOI: 10.5220/0003943105270530


in Bibtex Style

@conference{grapp12,
author={Kornél Bertók and Attila Fazekas},
title={GESTURE RECOGNITION - Control of a Computer with Natural Head Movements},
booktitle={Proceedings of the International Conference on Computer Graphics Theory and Applications and International Conference on Information Visualization Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2012)},
year={2012},
pages={527-530},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003943105270530},
isbn={978-989-8565-02-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Graphics Theory and Applications and International Conference on Information Visualization Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2012)
TI - GESTURE RECOGNITION - Control of a Computer with Natural Head Movements
SN - 978-989-8565-02-0
AU - Bertók K.
AU - Fazekas A.
PY - 2012
SP - 527
EP - 530
DO - 10.5220/0003943105270530