Abstract
Player location is one of the most informative cues for obtaining tactics arrangement and collecting descriptive game statistics. However, state-of-the-art supervised learning-based methods for player localization require a large amount of labeled training data. Hence, the development of automatic systems for player localization becomes indispensable. Volleyball games reach a huge audience base and contain a variety of tactical strategies, necessitating the implementation of systems for inferring tactics and analyzing formations automatically. Therefore, a novel 2D histogram-based player localization method capable of locating players with occlusions is developed and presented in this paper. The proposed system is able to automatically detect the court lines for camera calibration, extract players by calculating both x and y histograms of extracted player masks, and visualize the team formations on real-world court model. The experiments on broadcast volleyball videos demonstrate efficient and effective results against a traditional object segmentation method (connected component analysis) and a supervised learning approach utilizing histogram of oriented gradient features.














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References
Bialkowski, A., Lucey, P., Carr, P., Yue, Y., Matthews, I.: Win at home and draw away: automatic formation analysis highlighting the difference in home and away team behaviors. In Procedings of MIT Sloan Sports Analytics (2014)
Cervone, D., D’Amour, A., Bornn, L., Goldsberry, K.: POINTWISE: predicting points and valuing decisions in real time with NBA Optical Tracking Data. In Proceedings MIT Sloan Sports Analytics (2014)
Perse, M., Kristan, M., Kovacic, S., Vuckovic, G., Pers, J.: A trajectory-based analysis of coordinated team activity in a basketball game. Comput. Vis. Image Understand. (2009)
Kim, K. Grundmann, M., Shamir, A., Matthews, I., Hodgins, J., Essa, I.: Motion fields to predict play evolution in dynamic sport scenes. In Proceedings CVPR (2010)
Wei, X. Sha, L. Lucey, P., Morgan, S. Sridharan, S. Large-scale analysis of formations in Soccer. In: Proceedings DICTA (2013)
Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. In: Proceedings CVPR (2001)
Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In Proceedings of CVPR (2005)
Zhu, Q., Avidan, S., Yeh, M., Cheng, K.: Fast human detection using a cascade of histograms of oriented gradients. In: Proceedings of CVPR (2006)
Felzenszwalb, P., McAllester, D., Ramanan, D.: A discriminatively trained, Multiscale, Deformable Part Model. In: Proceedings of CVPR (2008)
Morais, E., Ferreira, A., Cunha, S.A., Barros, R.M.L., Rocha, A., Goldenstein, S.: A multiple camera methodology for automatic localization and tracking of futsal players Pattern Recognit. (2014)
Sun, S.W., Cheng, W.H., Hung, Y.L., Fan, I., Liu, C., Hung, J., Lin, C.K., Liao, H.Y.M.: Who’s who in a sports video? An individual level sports video indexing system. In: Proceedings of ICME, pp. 937–942 (2012)
Lu, W.L. Ting, J.A., Little, J.J., Murphy, K.P.: Learning to track and identify playersfrom broadcast sports videos. IEEE Trans Pattern Anal. Mach. Intel., 35(7) (July 2013)
Suzuki, K., Horiba, I., Sugie, N.: Linear-time connected-component labeling based on sequential local Operations. Comput. Vis. Image Understand. (2003)
Chang, M.H., Tien, M.C., Wu, J.L.: WOW: wild-open warning for broadcast basketball video based on player trajectory. In: Proceedings of 17th ACM MM, pp. 821–824 (2009)
Fu, T.S., Chen, H.T., Chou, C.L., Lee, S.Y.: Screen-strategy analysis in broadcast basketball video using playertracking. In: Proceedings of VCIP, pp. 1–4 (2011)
Tien, M.C., Chen, H.T., Chen, Y.W., Hsiao, M.H, Lee, S.Y.: Shot classification of basketball videos and its applications in shooting position extraction. In: Proceedings of IEEE ICASSP, pp. I-1085–1088 (2007)
Hanjalic, A.: Shot-boundary detection: unraveled and resolved? IEEE Trans. Circuits Syst Video Technol. 12(2), 90–105 (2002)
Duan, L.Y., Xu, M., Tian, Q., Xu, C.S., Jin, J.S.: A unified framework for semantic shot classification in sports video. IEEE Trans. Multimedia 7(6), 1066–1083 (2005)
Fleischman, M., Roy, B., Roy, D.: Temporal feature induction for baseball highlight classification. In: Proceedings of 15th ACM MM, pp. 333–336 (2007)
Chen, H.S., Chen, H.T., Tsai, W.J., Lee, S.Y., Yu, J.Y.: Pitch-by-pitch extraction from single view baseball video sequences. In Proceedings of ICME, pp. 1423–1426 (2007)
Assfalg, J., Bertini, M., Colombo, C., Del Bimbo, A., Nunziati, W.: Semantic annotation of soccer videos: automatic highlights identification. Comput. Vis. Image Underst. 92(2–3), 285–305 (2003)
Chen, H.T., Chou, C.L., Tsai, W.J., Lee, S.Y., Yu, J.Y.: Extraction and representation of human body for pitching style recognition in broadcast baseball video. In: Proceedings of IEEE ICME, pp. 1–4 (2011)
Xiong, Z., Radhakrishnan, R., Divakaran, A., Huang, T.S., Highlights extraction from sports video based on an audio-visual marker detection framework. In: Procedings of IEEE ICME (2005)
Cheng, C.C., Hsu, C.T.: Fusion of audio and motion information on hmm-based highlight extraction for baseball games. IEEETrans.Multime. 8(3), 585–599 (2006)
Duan, L.Y., Xu, M., Chua, T.S., Tian, Q., Xu, C.: A mid-level representation framework for semantic sports video analysis. In: Proceedings of 11th ACM MM, pp. 33–44 (2003)
Jiang, S., Ye, Q., Gao, W., Huang, T.: A new method to segment playfield and its applications in match analysis in sports video. In: Proceedings of 12th ACM MM, pp. 292–295 (2004)
Chen, H.T., Tien, M.C., Chen, Y.W., Tsai, W.J., Lee, S.Y.: Physics-based ball tracking and 3D trajectory reconstruction with applications to shooting location estimation in basketball video. J. Vis. Commun. Image Represent. 20(3), 204–216 (2009)
Wei, X., Lucey, P., Morgan, S., Sirdharan, S.: Predicting shot locations in tennis using spatiotemporal data. In: Proceedings of DICTA (2013)
Xing, J., Ai, H., Liu, L., Lao, S.: Multiple player tracking in sports video: a dual-mode two-way bayesian inference approach with progressive observation modeling. IEEE Trans. Multimed. 20(6), 1652–1667 (2011)
Liu, J., Carr, P., Collins, R.T., Liu, Y.: Tracking sports players with context-conditioned motion models. In: Proceedings of CVPR (2013)
Niu, Z., Gao, X., Tian, Q.: Tactic analysis based on real-world ball trajectory in soccer video. Pattern Recogn. 45(5), 1937–1947 (2012)
Hsu, C.C., Chen, H.T., Chou, C.L., Lee, S.Y.: Spiking and blocking events detection and analysis in volleyball videos. In: Proceedings of ICME, pp. 19–24 (2012)
Zhu, G., Xu, C., Huang, Q., Gao, W., Xin, L.: Player action recognition in broadcast tennis video with applications to semantic analysis of sports game. In: Proceedings of 14th ACM MM, pp. 431–440 (2006)
Lucey, P., Oliver, D., Carr, P., Roth, J., Matthews, I.:Assessing team strategy using spatiotemporal data. In: Proceedings of KDD (2013)
Zhu, G., Xu, C., Huang, Q., Rui, Y., Jiang, S., Gao, W., Yao, H.: Event tactic analysis based on broadcast sports video. IEEETrans. Multimed. 11(1), 49–67 (2009)
Xu, M., Orwell, J., Lowey, L., Thirde, D.: Architecture and algorithms for tracking football players with multiple cameras. In Proceedings of IEEE workshop on intelligent distributed surveillance systems, London, 2004, pp. 51–56 (2004)
Hamid, R., Kumar, R.K., Grundmann, M., Kim, K., Essa, I. Hodgins, J.: Player localization using multiple static cameras for sports visualization. In: Proceedings of CVPR (2010)
Farin, D., Krabbe, S., de With, P.H.N., Effelsberg, W.: Robust camera calibration for sport videos using court models. SPIE Storag. Retriev. Methods Appl. Multimed. 5307, 80–91 (2004)
Hu, M.C., Chang, M.H., Wu, J.L., Chi, L.: Robust camera calibration and player tracking in broadcast basketball video. IEEE Trans. Multimed. 13(2), 266–279 (2011)
Hsu, C.C., Chen, H.T., Chou, C.L., Lee, S.Y., Ho, C.P.: Serve receive-to-attack period extraction and histogram-based player localization in broadcast volleyball videos. In Proceedings of VCIP, pp. 1–6 (2013)
Liu, Y., Jiang, S., Ye, Q., Gao, W., Huang, Q.: Playfield detection using adaptive gmm and its application. In: Proceedings of ASSP, vol. 2, pp. 421–424 (2005)
Acknowledgment
This research is supported in part by NSC-101-2221-E-009-087-MY3, MOST-103-2221-E-009-154, MOST-103-2218-E-009 -020, ICTL-103-Q528, and ATU-103-W958.
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Communicated by C. Xu.
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Hsu, CC., Chen, HT., Chou, CL. et al. 2D Histogram-based player localization in broadcast volleyball videos. Multimedia Systems 22, 325–341 (2016). https://doi.org/10.1007/s00530-015-0463-8
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DOI: https://doi.org/10.1007/s00530-015-0463-8