RACKET: Real-time autonomous computation of kinematic elements in tennis

2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009

Volumn , Issue , 2009, Pages 773-779

  Pansiot, Julien ^a   Elsaify, Ahmed ^a   Lo, Benny ^a   Yang, Guang Zhong ^a  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

CALIBRATION ALGORITHM; FRAMES PER SECONDS; IMAGE PLANE; MULTIPLE NODES; STATISTICAL BACKGROUND MODEL; TENNIS PLAYERS; TRACKING ACCURACY; TRAINING SESSIONS; VISUAL SENSOR NETWORKS;

CALIBRATION; MOBILE DEVICES; TENNIS COURTS;

COMPUTER VISION;

EID: 77953195947     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCVW.2009.5457624     Document Type: Conference Paper

References (18)

1. Analog Devices. Blackfin BF537. http://www.analog.com.
2. S. Apewokin, B. Valentine, D. Forsthoefel, L.Wills, S.Wills, and A. Gentile. Embedded real-time surveillance using multimodal mean background modeling. Embedded Computer Vision, pages 163-175, 2009.
3. T. Bloom. Player tracking and stroke recognition in tennis video. In Proceddings of WDIC, pages 93-97, 2003.
4. D. Brown. Close-range camera calibration. Photogrammetric Engineering, 37(8):855-866, 1971.
5. D. Gould, R. Medbery, N. Damarjian, and L. Lauer. A survey of mental skills training knowledge, opinions, and practices of junior tennis coaches. Journal of Applied Sport Psychology, 11:28-50, 1999.
6. D. Gutchess, M. T. C, E. Cohen-solal, D. Lyons, and A. K. Jain. A background model initialization algorithm for video surveillance. In Proceedings of the IEEE International Conference on Computer Vision (ICCV), pages 733-740, 2001.
7. Hawkeye. http://www.hawkeyeinnovations.co.uk.
8. Lantronix. Matchport. http://www.lantronix.com.
9. D.-S. Lee. Effective gaussian mixture learning for video background subtraction. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 27(5):827-832, 2005. (Pubitemid 40608416)
10. Omnivision. OV9655. http://www.ovt.com.
11. C. Petersen and N. Nittinger. Fit to play: making better players, on & off court. Medicine and Science in Tennis, 9(1):20-21, 2004.
12. G. Pingali, Y. Jean, and I. Carlbom. Real time tracking for enhanced tennis broadcasts. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 260-265, Jun 1998.
13. G. Sudhir, J. Lee, and A. Jain. Automatic classification of tennis video for high-level content-based retrieval. In Proceedings of the IEEE International Workshop on Content-Based Access of Image and Video Database, pages 81-90, Jan 1998.
14. United States Tennis Association (USTA). Tennis Tactics: Winning Patterns of Play. Human Kinetics, 1996.
15. P. C. W. Van Wieringen, H. H. Emmen, R. J. Bootsma, M. Hoogesteger, and H. T. A. Whiting. The effect of video-feedback on the learning of the tennis service by intermediate players. Journal of Sports Sciences, 7:153-162, 1989.
16. VICON. Motion capture systems. http://www.vicon.com.
17. J.Wang and N. Parameswaran. Analyzing tennis tactics from broadcasting tennis video clips. In Proceedings of the 11th International Multimedia Modelling Conference, pages 102-106, Jan. 2005.
18. Xsens. Moven. http://www.moven.com.