Human Motion Analysis under Actual Sports Game Situations - Sequential Multi-decay Motion History Image Matching

Dan Mikami, Toshitaka Kimura, Koji Kadota, Harumi Kawamura, Akira Kojima

Abstract

This paper proposes a sequential multi-decay motion history image matching with the aim of analyzing human motions captured in actual game situations without subjecting people to any intrusive measures. The motion history image (MHI) is a well- known motion representation method, which can be used without foreground detection. In MHIs, pixels on which motion is detected have large pixel values. As time elapses following the latest motion detection, the values decrease according to a decay parameter. Two improvements were made to enable MHI-based template matching to be applied to motion analysis; introducing a template MHI sequence matching process that enables analysis of the temporal development of motions and extending MHIs to include multiple decay parameters. Due to the MHI sequence, a reference motion includes target motions of various speeds. Since the appropriate decay parameter varies with motion speed, no one predefined decay parameter can be the best one. These improvements enable our method to effectively analyze human motions in actual game situations. Experiments carried out indoors with capturing of 3D motion data and outdoors under real games situations verified the effectiveness of the proposed method.

References

  1. Ahad, M. A. R., Tan, J. K., Kim, H., and Ishikawa, S. (2012). Motion history image: its variants and applications. Machine Vision and Applications, 23(2):255 - 281.
  2. Bobick, A. F. and Davis, J. W. (1996). Real-time recognition of activity using temporal templates. In Proc. of 3rd IEEE workshop on Applications of Computer Vision (WACV), pages 39 - 42.
  3. Bobick, A. F. and Davis, J. W. (2001). The recognition of human movement using temporal templates. IEEE Trans. PAMI, 23(3):257 - 267.
  4. Bradski, G. R. and Davis, J. W. (2002). Motion segmentation and pose recognition with motion history gradients. Machine Vision and Applications, 13(3):174 - 184.
  5. Mikami, D., Konya, S., and Morimoto, M. (2007). Pitch by pitch event detection using impulse sound detection and moving image clustering. IEICE Trans. Information and Systems, J90-D(2):526-534.
  6. Mikami, D., Otsuka, K., and Yamato, J. (2009). Memorybased particle filter for face pose tracking robust under complex dynamics. In Proc. of IEEE Computer Vision and Pattern Recognition (CVPR), pages 999 - 1006.
  7. Oikonomidis, I., Kyriazis, N., and Argyros, A. A. (2011). Efficient model-based 3D tracking of hand articulations using Kinect. In Proc. of BMVC.
  8. Shotton, J., Fitzgibbon, A., Cook, M., Sharp, T., Finocchio, M., Moore, R., Kipman, A., and Blake, A. (2011). Real-time human pose recognition in parts from a single depth image. In Proc. of IEEE Computer Vision and Pattern Recognition (CVPR).
  9. Valstar, M., Pantic, M., and Patras, I. (2004). Motion history for facial action detection in video. In Proc. of IEEE Int'l conf. on System, Man and Cybernetics, volume 1, pages 635-640.
  10. Vasconcelos, M. J. M. and Tavares, J. M. R. (2008). Human motion analysis: Methodologies and applications. In Proc. of Int'l Symposium on Computer Methods in Biomechanics and Biomedical Engineering.
  11. Weinland, D., Ronfard, R., and Boyer, E. (2006). Free view point action recognition using motion history volumes. Computer Vsion and Image Understanding, 104(2-3):249-257.
Download


Paper Citation


in Harvard Style

Mikami D., Kimura T., Kadota K., Kawamura H. and Kojima A. (2013). Human Motion Analysis under Actual Sports Game Situations - Sequential Multi-decay Motion History Image Matching . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-48-8, pages 229-236. DOI: 10.5220/0004272202290236


in Bibtex Style

@conference{visapp13,
author={Dan Mikami and Toshitaka Kimura and Koji Kadota and Harumi Kawamura and Akira Kojima},
title={Human Motion Analysis under Actual Sports Game Situations - Sequential Multi-decay Motion History Image Matching},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013)},
year={2013},
pages={229-236},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004272202290236},
isbn={978-989-8565-48-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013)
TI - Human Motion Analysis under Actual Sports Game Situations - Sequential Multi-decay Motion History Image Matching
SN - 978-989-8565-48-8
AU - Mikami D.
AU - Kimura T.
AU - Kadota K.
AU - Kawamura H.
AU - Kojima A.
PY - 2013
SP - 229
EP - 236
DO - 10.5220/0004272202290236