Skip to main content
Log in

Ball tracking and 3D trajectory approximation with applications to tactics analysis from single-camera volleyball sequences

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

Providing computer-assisted tactics analysis in sports is a growing trend. This paper presents an automatic system for ball tracking and 3D trajectory approximation from single-camera volleyball sequences as well as demonstrates several applications to tactics analysis. Ball tracking in volleyball video has great complexity due to the high density of players on the court and the complicated overlapping of ball-player. The 2D-to-3D inference is intrinsically challenging due to the loss of 3D information in projection to 2D frames. To overcome these challenges, we propose a two-phase ball tracking algorithm in which we first detect ball candidates for each frame, and then use them to compute the ball trajectories. With the aid of camera calibration, we involve physical characteristics of ball motion to approximate the 3D ball trajectory from the 2D trajectory. The visualization of 3D trajectory and the applications to trajectory-based tactics analysis not only assist the coaches and players in game study but also make game watching a whole new experience. The experiments on international volleyball games show encouraging results. We believe that the proposed framework can be extended and applied to various kinds of sports games.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16

Similar content being viewed by others

References

  1. Assfalg J, Bertini M, Colombo C, Bimbo AD, Nunziati W (2003) Semantic annotation of soccer videos: automatic highlights identification. Comput Vis Image Underst 92(23):285–305

    Article  Google Scholar 

  2. Cheng CC, Hsu CT (2006) Fusion of audio and motion information on HMM-based highlight extraction for baseball games. IEEE Trans Multimed 8(3):585–599

    Article  Google Scholar 

  3. Chen HT, Hsiao MH, Chen HS, Tsai WJ, Lee SY (2008) A baseball exploration system using spatial pattern recognition. In: Proc IEEE Int Symp Circuits and Systems 2008:3522–3525

    Google Scholar 

  4. Chen HT, Chen HS, Hsiao MH, Tsai WJ, Lee SY (2008) A trajectory-based ball tracking framework with enrichment for broadcast baseball videos. J Inf Sci Eng 24(1):143–157

    Google Scholar 

  5. Chen HT, Tien MC, Chen YW, Tsai WJ, Lee SY (2009) Physics-based ball tracking and 3D trajectory reconstruction with applications to shooting location estimation in basketball video. J Vis Commun Image Representation 20(3):204–216

    Article  Google Scholar 

  6. Chen HT, Chen HS, Lee SY (2007) Physics-based ball tracking in volleyball videos with its applications to set type recognition and action detection. In: Proc. IEEE Int. Conf. on Acoustic Speech Signal Process 2007, pp. I-1097–1100

  7. Duan LY, Xu M, Tian Q (2005) A unified framework for semantic shot classification in sports video. IEEE Trans Multimed 7(6):1066–1083

    Article  Google Scholar 

  8. Duan LY, Xu M, Chua TS, Tian Q, Xu CS (2003) A mid-level representation framework for semantic sports video analysis. In: Proc. 11th ACM Int. Conf. Multimedia, pp.33–44

  9. Ekin A, Tekalp AM, Mehrotra R (2003) Automatic soccer video analysis and summarization. IEEE Trans Image Process 12(7):796–807

    Article  Google Scholar 

  10. Farin D, Krabbe S, Peter HN, Effelsberg W (2004) Robust camera calibration for sport videos using court models. SPIE Storage Retrieval Meth Appl Multimedia 5307:80–91

    Google Scholar 

  11. Farin D, Han J, Peter HN (2005) Fast camera calibration for the analysis of sport sequences. In: Proc IEEE Int Conf Multimedia and Expo 2005:482–485

    Article  Google Scholar 

  12. Forlines C, Peker KA, Divakaran A (2006) Subjective assessment of consumer video summarization. In: Proc. SPIE Int. Soc. Opt. Eng. (6073), pp. 170–177

  13. Gueziec A (2002) Tracking pitches for broadcast television. Computer 35:38–43

    Article  Google Scholar 

  14. Gonzalez RC, Woods RE (2002), Digital image processing, Prentice Hall (2nd edition)

  15. Hartley R, Zisserman A (2003) Multiple view geometry in computer vision, 2nd edn. Cambridge University Press, UK

    Google Scholar 

  16. Lu H, Tan YP (2003) Unsupervised clustering of dominant scenes in sports video. Pattern Recogn Lett 24(15):2651–2662

    Article  Google Scholar 

  17. Loui A, Luo J, Chang S, Ellis D, Jiang W, Kennedy L, Lee K, Yanagawa A (2007) Kodak 's consumer video benchmark data set: concept definition and annotation. In: Proc Int Workshop Multimedia Inform Retrieval 2007:245–254

    Article  Google Scholar 

  18. Mei T, Hua XS (2008) Structure and event mining in sports video with efficient mosaic. Multimedia Tools Appl 40(1):89–110

    Article  Google Scholar 

  19. Oami R, Benitez AB, Chang SF, Dimitrova N (2004) Understanding and modeling user interests in consumer videos. In: Proc IEEE Int Conf Multimedia and Expo 2004:1475–1478

    Google Scholar 

  20. Owens N, Harris C, Stennett C (2003) Hawk-eye tennis system. In: Proc Inf Conf Visual Information Engineering 2003:182–185

    Google Scholar 

  21. QuesTec-Umpire Information System. [Online]. Available: http://www.questec.com/q2001/prod_uis.htm

  22. Seo Y, Choi S, Kim H, Hong KS (1997) Where are the ball and players? Soccer game analysis with color-based tracking and image mosaick In: Proc Image Analysis and Processing 1997(1331):196–203

    Google Scholar 

  23. Tien MC, Chen HT, Chen YW, Hsiao MH, Lee SY (2007) Shot classification of basketball videos and its applications in shooting position extraction. In: Proc. IEEE Int. Conf. Acoust. Speech Signal Process 2007, pp. I-1085–1088.

  24. Watanabe T, Haseyama M, Kitajima H (2004) A soccer field tracking method with wire frame model from TV images. In: Proc IEEE Int Conf Image Process 2004:1633–1636

    Google Scholar 

  25. Xu M, Maddage NC, Xu C, Kankanhalli M, Tian Q (2003) Creating audio keywords for event detection in soccer video. In: Proc. IEEE Int. Conf. Multimedia and Expo 2003, pp. II-281–284

  26. Xu M, Duan L, Chia L, Xu C (2004), Audio keyword generation for sports video analysis. In: Proc. 12th Annual ACM Int. Conf. Multimedia, pp.758–759

  27. Yu X, Xu C, Leong HW, Tian Q, Tang Q, Wan KW (2003) Trajectory-based ball detection and tracking with applications to semantic analysis of broadcast soccer video. In: Proc. 11th ACM Int. Conf. Multimedia, pp.11–20

  28. Yu X, Leong HW, Xu C, Tian Q (2006) Trajectory-based ball detection and tracking in broadcast soccer video. IEEE Trans Multimed 8(6):1164–1178

    Article  Google Scholar 

  29. Yu X, Jiang N, Cheong LF, Leong HW, Yan X (2008) Automatic camera calibration of broadcast tennis video with applications to 3 d virtual content insertion and ball detection and tracking. Comput Vis Image Underst 113(5):643–652

    Article  Google Scholar 

  30. Yu X, Jiang N, Cheong LF (2007) Accurate and stable camera calibration of broadcast tennis video. In: Proc Int IEEE Conf Image Process 2007:93–96

    Google Scholar 

  31. Yu X, Tu X, Ang EL (2007) Trajectory-based ball detection and tracking in broadcast soccer video with the aid of camera motion recovery. In: Proc IEEE ICME 2007:1543–1546

    Google Scholar 

  32. Zhu G, Huang Q, Xu C, Xing L, Gao W, Yao H (2007) Human behavior analysis for highlight ranking in broadcast racket sports video. IEEE Trans Multimed 9(6):1167–1182

    Article  Google Scholar 

  33. Zhu G, Huang Q, Xu C, Rui Y, Jiang S, Gao W, Yao H (2007) Trajectory based event tactics analysis in broadcast sports video. In: Proc. 15th ACM Int. Conf. Multimedia, pp.58–67

  34. Zhang T, Kuo J (2001) Audio content analysis for online audiovisual data segmentation and classification. IEEE Trans Speech Audio Process 9(4):441–457

    Article  Google Scholar 

Download references

Acknowledgement

The research is partially supported by the National Science Council of Taiwan, R.O.C, under the grant No. NSC 95-2221-E-009-076-MY3 and partially supported by Lee and MTI center for Networking Research at National Chiao Tung University, Taiwan.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hua-Tsung Chen.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chen, HT., Tsai, WJ., Lee, SY. et al. Ball tracking and 3D trajectory approximation with applications to tactics analysis from single-camera volleyball sequences. Multimed Tools Appl 60, 641–667 (2012). https://doi.org/10.1007/s11042-011-0833-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-011-0833-y

Keywords

Navigation