Advertisement

Artificial Intelligence Review

, Volume 52, Issue 3, pp 1655–1705 | Cite as

Ball tracking in sports: a survey

  • Paresh R. KambleEmail author
  • Avinash G. Keskar
  • Kishor M. Bhurchandi
Article

Abstract

Increase in the number of sport lovers in games like football, cricket, etc. has created a need for digging, analyzing and presenting more and more multidimensional information to them. Different classes of people require different kinds of information and this expands the space and scale of the required information. Tracking of ball movement is of utmost importance for extracting any information from the ball based sports video sequences. Based on the literature survey, we have initially proposed a block diagram depicting different steps and flow of a general tracking process. The paper further follows the same flow throughout. Detection is the first step of tracking. Dynamic and unpredictable nature of ball appearance, movement and continuously changing background make the detection and tracking processes challenging. Due to these challenges, many researchers have been attracted to this problem and have produced good results under specific conditions. However, generalization of the published work and algorithms to different sports is a distant dream. This paper is an effort to present an exhaustive survey of all the published research works on ball tracking in a categorical manner. The work also reviews the used techniques, their performance, advantages, limitations and their suitability for a particular sport. Finally, we present discussions on the published work so far and our views and opinions followed by a modified block diagram of the tracking process. The paper concludes with the final observations and suggestions on scope of future work.

Keywords

Tracking set ups Ball detection Shape and size features Tracking performance evaluation Ball tracking Tracking techniques classification 

References

  1. Almajai I, Yan F, de Campos T, Khan A, Christmas W, Windridge D, Kittler J (2012) Anomaly detection and knowledge transfer in automatic sports video annotation. In: Detection and identification of rare audiovisual cues. Springer, pp 109–117Google Scholar
  2. Ancona N, Cicirelli G, Stella E, Distante A (2003) Ball detection in static images with support vector machines for classification. Image Vis Comput 21:675–692CrossRefGoogle Scholar
  3. Ariki Y, Takiguchi T, Yano K (2008) Digital camera work for soccer video production with event recognition and accurate ball tracking by switching search method. In: 2008 IEEE international conference on multimedia and expo. IEEE, pp 889–892Google Scholar
  4. Arulampalam MS, Maskell S, Gordon N, Clapp T (2002) A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking. IEEE Trans Signal Process 50:174–188CrossRefGoogle Scholar
  5. Bar-Shalom Y (1987) Tracking and data association. Academic Press, LondonzbMATHGoogle Scholar
  6. Barnard M, Odobez J-M (2004) Robust playfield segmentation using MAP adaptation. In: Proceedings of the 17th international conference on pattern recognition. ICPR 2004. IEEE, pp 610–613Google Scholar
  7. Batz G, Lee K-K, Wollherr D, Buss M (2009) Robot basketball: a comparison of ball dribbling with visual and force/torque feedback. In: IEEE international conference on robotics and automation. ICRA’09. IEEE, pp 514–519Google Scholar
  8. Beetz M, von Hoyningen-Huene N, Kirchlechner B, Gedikli S, Siles F, Durus M, Lames M (2009) Aspogamo: automated sports game analysis models. Int J Comput Sci Sport 8:1–21Google Scholar
  9. Birbach O, Frese UA (2009) Multiple hypothesis approach for a ball tracking system. In: International conference on computer vision systems. Springer, pp 435–444Google Scholar
  10. Birbach O, Frese U, Bäuml B (2011) Realtime perception for catching a flying ball with a mobile humanoid. In: 2011 IEEE international conference on robotics and automation (ICRA). IEEE, pp 5955–5962Google Scholar
  11. Bloom T, Bradley AP (2003) Player tracking and stroke recognition in tennis video. In: APRS workshop on digital image computing (WDIC’03). The University of Queensland, pp 93–97Google Scholar
  12. Chakraborty B, Meher S (2011) 2D trajectory-based position estimation and tracking of the ball in a basketball video. In: Second international conference on trends in optics and photonics, Kolkata, India, December 7–9, 2011, pp 537–545Google Scholar
  13. Chakraborty B, Meher S (2012a) Real-time position estimation and tracking of a basketball. In: 2012 IEEE international conference on signal processing, computing and control (ISPCC). IEEE, pp 1–6Google Scholar
  14. Chakraborty B, Meher S A (2012b) Trajectory-based ball detection and tracking system with applications to shot-type identification in volleyball videos. In: 2012 international conference on signal processing and communications (SPCOM). IEEE, pp 1–5Google Scholar
  15. Chakraborty B, Meher S (2013a) A real-time trajectory-based ball detection-and-tracking framework for basketball video. J Opt 42:156–170CrossRefGoogle Scholar
  16. Chakraborty B, Meher S A (2013b) Trajectory-based ball detection and tracking system with applications to shooting angle and velocity estimation in basketball videos. In: 2013 Annual IEEE India conference (INDICON). IEEE, pp 1–6Google Scholar
  17. Chang M-H, Tien M-C, Wu J-L (2009) WOW: wild-open warning for broadcast basketball video based on player trajectory. In: Proceedings of the 17th ACM international conference on multimedia. ACM, pp 821–824Google Scholar
  18. Chen B, Wang Z (2007) A statistical method for analysis of technical data of a badminton match based on 2-D seriate images. Tsinghua Sci Technol 12:594–601CrossRefGoogle Scholar
  19. Chen H-T, Chen H-S, Hsiao M-H, Tsai W-J, Lee S-Y (2008) A trajectory-based ball tracking framework with visual enrichment for broadcast baseball videos. J Inf Sci Eng 24:143–157Google Scholar
  20. Chen H-T, Chen H-S, Lee S-Y (2007) Physics-based ball tracking in volleyball videos with its applications to set type recognition and action detection. In: 2007 IEEE international conference on acoustics, speech and signal processing-ICASSP’07. IEEE, pp I-1097–I-1100Google Scholar
  21. Chen H-T, Tien M-C, Chen Y-W, Tsai W-J, Lee S-Y (2009) Physics-based ball tracking and 3D trajectory reconstruction with applications to shooting location estimation in basketball video. J Vis Commun Image Represent 20:204–216CrossRefGoogle Scholar
  22. Chen H-T, Tsai W-J, Lee S-Y, Yu J-Y (2012) Ball tracking and 3D trajectory approximation with applications to tactics analysis from single-camera volleyball sequences. Multimed Tools Appl 60:641–667CrossRefGoogle Scholar
  23. Chen W, Zhang Y-J (2006) Tracking ball and players with applications to highlight ranking of broadcasting table tennis video. In: IMACS multiconference on computational engineering in systems applications. IEEE, pp 1896–1903Google Scholar
  24. Cheng X, Honda M, Ikoma N, Ikenaga T (2016) Anti-occlusion observation model and automatic recovery for multi-view ball tracking in sports analysis. In: 2016 IEEE international conference on acoustics, speech and signal processing (ICASSP). IEEE, pp 1501–1505Google Scholar
  25. Cheng X, Zhuang X, Wang Y, Honda M, Ikenaga T (2015) Particle filter with ball size adaptive tracking window and ball feature likelihood model for ball’s 3D position tracking in volleyball analysis. In: Pacific Rim conference on multimedia. Springer, pp 203–211Google Scholar
  26. Choi K, Seo Y (2004) Probabilistic tracking of the soccer ball. In: International workshop on statistical methods in video processing. Springer, pp 50–60Google Scholar
  27. Choi K, Seo Y (2005) Tracking soccer ball in TV broadcast video. In: International conference on image analysis and processing. Springer, pp 661–668Google Scholar
  28. Choi K, Seo Y (2011) Automatic initialization for 3D soccer player tracking. Pattern Recogn Lett 32:1274–1282CrossRefGoogle Scholar
  29. Christmas W, Kolonias I, Kittler J, Yan F (2007) Improving the accuracy of automatic tennis video annotation by high level grammar. In: 14th international conference on image analysis and processing workshops. ICIAPW 2007. IEEE, pp 154–159Google Scholar
  30. Cigliano P, Lippiello V, Ruggiero F, Siciliano B (2015) Robotic ball catching with an eye-in-hand single-camera system. IEEE Trans Control Syst Technol 23:1657–1671CrossRefGoogle Scholar
  31. Conaire CÓ, Kelly P, Connaghan D, O’Connor NE (2009) Tennissense: a platform for extracting semantic information from multi-camera tennis data. In: 2009 16th international conference on digital signal processing. IEEE, pp 1–6Google Scholar
  32. D’Orazio T, Guaragnella C, Leo M, Distante A (2004) A new algorithm for ball recognition using circle Hough transform and neural classifier. Pattern Recogn 37:393–408CrossRefGoogle Scholar
  33. D’Orazio T, Leo M, Spagnolo P, Mazzeo PL, Mosca N, Nitti M, Distante A (2009) An investigation into the feasibility of real-time soccer offside detection from a multiple camera system. IEEE Trans Circuits Syst Video Technol 19:1804–1818CrossRefGoogle Scholar
  34. D’Orazio T, Leo M, Spagnolo P, Nitti M, Mosca N, Distante A (2009) A visual system for real time detection of goal events during soccer matches. Comput Vis Image Underst 113:622–632CrossRefGoogle Scholar
  35. Dearden A, Demiris Y, Grau O (2006) Tracking football player movement from a single moving camera using particle filters. In: Proceedings of the 3rd European conference on visual media production (CVMP), London, pp 29–37Google Scholar
  36. Desai UB, Merchant SN, Zaveri M, Ajishna G, Purohit M, Phanish H (2005) Small object detection and tracking: algorithm, analysis and application. In: International conference on pattern recognition and machine intelligence. Springer, pp 108–117Google Scholar
  37. Ekinci B, Gokmen MA (2008) Ball tracking system for offline tennis videos. In: International conference on visualization, imaging and simulationGoogle Scholar
  38. El Abed A, Dubuisson S, Béréziat D (2006) Comparison of statistical and shape-based approaches for non-rigid motion tracking with missing data using a particle filter. In: International conference on advanced concepts for intelligent vision systems. Springer, pp 185–196Google Scholar
  39. Farin D, de Han J (2005) With PH fast camera calibration for the analysis of sport sequences. In: 2005 IEEE international conference on multimedia and expo. IEEEGoogle Scholar
  40. Farin D, de Krabbe S, Withb PH, Effelsberga W (2004) Robust camera calibration for sport videos using court models. In: SPIE proceedings series, 2004. Society of Photo-Optical Instrumentation Engineers, pp 80–91Google Scholar
  41. Figueroa P, Leite N, Barros RM, Cohen I, Medioni G (2004) Tracking soccer players using the graph representation. In: Proceedings of the 17th international conference on pattern recognition. ICPR 2004. IEEE, pp 787–790Google Scholar
  42. Fischler MA, Bolles RC (1981) Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun ACM 24:381–395MathSciNetCrossRefGoogle Scholar
  43. Glover J, Kaelbling LP (2014) Tracking the spin on a ping pong ball with the quaternion Bingham filter. In: 2014 IEEE international conference on robotics and automation (ICRA). IEEE, pp 4133–4140Google Scholar
  44. Han M, Hua W, Chen T, Gong Y (2003) Feature design in soccer video indexing. In: Proceedings of the 2003 joint conference of the fourth international conference on information, communications and signal processing, 2003 and Fourth Pacific Rim conference on multimedia. IEEE, pp 950–954Google Scholar
  45. Hartley R, Zisserman A (2003) Multiple view geometry in computer vision. Cambridge University Press, CambridgezbMATHGoogle Scholar
  46. Hossein-Khani J, Soltanian-Zadeh H, Kamarei M, Staadt O (2011) Ball detection with the aim of corner event detection in soccer video. In: 2011 Ninth IEEE international symposium on parallel and distributed processing with applications workshops (ISPAW). IEEE, pp 147–152Google Scholar
  47. Hoyningen-Huene Nv, Beetz M (2009) Rao-blackwellized resampling particle filter for real-time player tracking in sports VISAPP, INSTICC, pp 464–471Google Scholar
  48. Hu M-C, Chang M-H, Wu J-L, Chi L (2011) Robust camera calibration and player tracking in broadcast basketball video. IEEE Trans Multimed 13:266–279CrossRefGoogle Scholar
  49. Huang Q, Cox S, Yan F, deCampos T, Windridge D, Kittler J, Christmas W (2011) Improved detection of ball hit events in a tennis game using multimodal information. In: 11th International conference on auditory-visual speech processing (AVSP)Google Scholar
  50. Huang Q, Cox S, Zhou X, Xie L (2012) Detection of ball hits in a tennis game using audio and visual information. In: 2012 Asia-Pacific signal and information processing association annual summit and conference (APSIPA ASC). IEEE, pp 1–10Google Scholar
  51. Huang Y, Llach J, Zhang C A (2008) method of small object detection and tracking based on particle filters. In: 19th international conference on pattern recognition. ICPR 2008. IEEE, pp 1–4Google Scholar
  52. Ishii N, Kitahara I, Kameda Y, Ohta Y (2007) 3D tracking of a soccer ball using two synchronized cameras. In: Pacific-Rim conference on multimedia. Springer, pp 196–205Google Scholar
  53. Iwase S, Saito H (2003) Tracking soccer players based on homography among multiple views. In: Visual communications and image processing. International Society for Optics and Photonics, pp 283–292Google Scholar
  54. Janssen R, Verrijt M, de Best J, van de Molengraft R (2012) Ball localization and tracking in a highly dynamic table soccer environment. Mechatronics 22:503–514CrossRefGoogle Scholar
  55. Kasiri-Bidhendi S, Safabakhsh R (2009) Effective tracking of the players and ball in indoor soccer games in the presence of occlusion. In: 14th International CSI computer conference. CSICC 2009. IEEE, pp 524–529Google Scholar
  56. Kasuya N, Kitahara I, Kameda Y, Ohta Y (2010) Real-time soccer player tracking method by utilizing shadow regions. In: Proceedings of the 18th ACM international conference on Multimedia. ACM, pp 1319–1322Google Scholar
  57. Kelly P et al (2010) A low-cost performance analysis and coaching system for tennis. In: Proceedings of ACM multimediaGoogle Scholar
  58. Kim J-Y, Kim T-Y (2009) Soccer ball tracking using dynamic kalman filter with velocity control. In: Sixth international conference on computer graphics, imaging and visualization. CGIV’09. IEEE, pp 367–374Google Scholar
  59. Kim T, Seo Y, Hong K-S (1998) Physics-based 3D position analysis of a soccer ball from monocular image sequences. In: Sixth international conference on computer vision. IEEE, pp 721–726Google Scholar
  60. Kittler J, Christmas WJ, Kostin A, Yan F, Kolonias I, Windridge DA (2005) memory architecture and contextual reasoning framework for cognitive vision. In: Scandinavian conference on image analysis. Springer, pp 343–358Google Scholar
  61. Kokaram A, Pitie F, Dahyot R, Rea N, Yeterian S (2005) Content controlled image representation for sports streaming. In: Proceedings of content-based multimedia indexing (CBMI’05)Google Scholar
  62. Kumar A, Chavan PS, Sharatchandra V, David S, Kelly P, O’Connor NE (2011) 3D estimation and visualization of motion in a multicamera network for sports. In: 2011 Irish machine vision and image processing conference (IMVIP). IEEE, pp 15–19Google Scholar
  63. Leo M, Mosca N, Spagnolo P, Mazzeo PL, D’Orazio T, Distante A (2008) Real-time multiview analysis of soccer matches for understanding interactions between ball and players. In: Proceedings of the 2008 international conference on content-based image and video retrieval. ACM, pp 525–534Google Scholar
  64. Lepetit V, Shahrokni A, Fua P (2003) Robust data association for online application. In: Proceedings. IEEE Computer Society conference on computer vision and pattern recognition. IEEE, pp I–IGoogle Scholar
  65. Li Y, Dore A, Orwell J (2005) Evaluating the performance of systems for tracking football players and ball. In: IEEE conference on advanced video and signal based surveillance. IEEE, pp 632–637Google Scholar
  66. Liang D, Huang Q, Liu Y, Zhu G, Gao W (2007) Video2Cartoon: a system for converting broadcast soccer video into 3D cartoon animation. IEEE Trans Consum Electron 53:1138–1146CrossRefGoogle Scholar
  67. Liang D, Liu Y, Huang Q, Gao WA (2005) Scheme for ball detection and tracking in broadcast soccer video. In: Pacific-Rim conference on multimedia. Springer, pp 864–875Google Scholar
  68. Liu J, Fang Z, Zhang K, Tan M (2014) Improved high-speed vision system for table tennis robot. In: 2014 IEEE international conference on mechatronics and automation. IEEE, pp 652–657Google Scholar
  69. Liu Y, Liang D, Huang Q, Gao W (2006) Extracting 3D information from broadcast soccer video. Image Vis Comput 24:1146–1162CrossRefGoogle Scholar
  70. Ltd. H-EI (2015) Ball tracking. https://www.hawkeyeinnovations.com/products/ball-tracking. Accessed 10 July 2017
  71. Maksai A, Wang X, Fua P (2015) What players do with the ball: a physically constrained interaction modeling. arXiv preprint arXiv:1511.06181
  72. Mauthner T, Koch C, Tilp M, Bischof H (2007) Visual tracking of athletes in beach volleyball using a single camera. Int J Comput Sci Sport 6:21–34Google Scholar
  73. Misu T, Matsui A, Naemura M, Fujii M, Yagi N (2007) Distributed particle filtering for multiocular soccer-ball tracking. In: 2007 IEEE international conference on acoustics, speech and signal processing-ICASSP’07, 2007. IEEE, pp III-937–III-940Google Scholar
  74. Miura J, Shimawaki T, Sakiyama T, Shirai Y (2009) Ball route estimation under heavy occlusion in broadcast soccer video. Comput Vis Image Underst 113:653–662CrossRefGoogle Scholar
  75. Miyamori H, Iisaku S-I (2000) Video annotation for content-based retrieval using human behavior analysis and domain knowledge. In: Fourth IEEE international conference on automatic face and gesture recognition. Proceedings. IEEE, pp 320–325Google Scholar
  76. Naidoo WC, Tapamo JR (2006) Soccer video analysis by ball, player and referee tracking. In: Proceedings of the 2006 annual research conference of the South African institute of computer scientists and information technologists on IT research in developing countries, 2006. South African Institute for Computer Scientists and Information Technologists, pp 51–60Google Scholar
  77. Ohno Y, Miura J, Shirai Y (2000) Tracking players and estimation of the 3D position of a ball in soccer games. In: 15th international conference on pattern recognition. Proceedings. IEEE, pp 145–148Google Scholar
  78. Ohno Y, Miurs J, Shirai Y (1999) Tracking players and a ball in soccer games. In: IEEE/SICE/RSJ international conference on multisensor fusion and integration for intelligent systems. MFI’99. Proceedings. IEEE, pp 147–152Google Scholar
  79. Pallavi V, Mukherjee J, Majumdar AK, Sural S (2008) Ball detection from broadcast soccer videos using static and dynamic features. J Vis Commun Image Represent 19:426–436CrossRefGoogle Scholar
  80. Pei C, Yang S, Gao L, Ma W (2009) A real time ball detection framework for soccer video. In: 2009 16th international conference on systems, signals and image processing. IEEE, pp 1–4Google Scholar
  81. Perše M, Kristan M, Perš J, Vuckovic G, Kovacic S (2005) Physics-based modelling of human motion using Kalman filter and collision avoidance algorithm. In: International symposium on image and signal processing and analysis, ISPA05, Zagreb, Croatia. Citeseer, pp 328–333Google Scholar
  82. Pingali G, Opalach A, Jean Y (2000) Ball tracking and virtual replays for innovative tennis broadcasts. In: 15th International conference on pattern recognition. Proceedings. IEEE, pp 152–156Google Scholar
  83. Pingali GS, Opalach A, Jean YD, Carlbom IB (2002) Instantly indexed multimedia databases of real world events. IEEE Trans Multimed 4:269–282CrossRefGoogle Scholar
  84. Poliakov A, Marraud D, Reithler L, Chatain C (2010) Physics based 3D ball tracking for tennis videos. In: 2010 international workshop on content-based multimedia indexing (CBMI). IEEE, pp 1–6Google Scholar
  85. Rea N, Dahyot R, Kokaram A (2004) Semantic event detection in sports through motion understanding. In: International conference on image and video retrieval. Springer, pp 88–97Google Scholar
  86. Reid ID, North A (1998) 3D Trajectories from a single viewpoint using shadows. In: BMVC, pp 51–52Google Scholar
  87. Ren J, Orwell J, Jones G (2006) Generating ball trajectory in soccer video sequencesGoogle Scholar
  88. Ren J, Orwell J, Jones G, Xu M (2004a) Real-time 3D soccer ball tracking from multiple cameras. In: Proceedings of the British Machine vision conference (BMVC’04), pp 829–838Google Scholar
  89. Ren J, Orwell J, Jones GA, Xu M (2004b) A general framework for 3D soccer ball estimation and tracking. In: 2004 international conference on image processing. ICIP’04. IEEE, pp 1935–1938Google Scholar
  90. Ren J, Orwell J, Jones GA, Xu M (2008) Real-time modeling of 3-d soccer ball trajectories from multiple fixed cameras. IEEE Trans Circuits Syst Video Technol 18:350–362CrossRefGoogle Scholar
  91. Ren J, Orwell J, Jones GA, Xu M (2009) Tracking the soccer ball using multiple fixed cameras. Comput Vis Image Underst 113:633–642CrossRefGoogle Scholar
  92. Santiago CB, Sousa A, Reis LP, Estriga ML (2011) Real time colour based player tracking in indoor sports. In: Computational vision and medical image processing. Springer, pp 17–35Google Scholar
  93. Seo Y, Choi S, Kim H, Hong K-S (1997) Where are the ball and players? Soccer game analysis with color-based tracking and image mosaick. In: International conference on image analysis and processing. Springer, pp 196–203Google Scholar
  94. Shah H, Chokalingam P, Paluri B, Pradeep N, Raman B (2007) Automated stroke classification in tennis. In: international conference image analysis and recognition. Springer, pp 1128–1137Google Scholar
  95. Shimawaki T, Miura J, Sakiyama T, Shirai Y (2006a) Ball route estimation in broadcast soccer video. In: Proceedings of ECCV-2006 workshop on computer vision based analysis in sport environments. Citeseer, pp 26–37Google Scholar
  96. Shimawaki T, Sakiyama T, Miura J, Shirai Y (2006b) Estimation of ball route under overlapping with players and lines in soccer video image sequence. In: 18th international conference on pattern recognition (ICPR’06). IEEE, pp 359–362Google Scholar
  97. Shum H, Komura TA (2004) Spatiotemporal approach to extract the 3D trajectory of the baseball from a single view video sequence. In: 2004 IEEE international conference on multimedia and expo. ICME’04. IEEE, pp 1583–1586Google Scholar
  98. Shum H, Komura T (2005) Tracking the translational and rotational movement of the ball using high-speed camera movies. In: IEEE international conference on image processing. IEEE, pp III-1084–III-1087Google Scholar
  99. Teachabarikiti K, Chalidabhongse TH, Thammano A (2010) Players tracking and ball detection for an automatic tennis video annotation. In: 2010 11th international conference on control automation robotics and vision (ICARCV). IEEE, pp 2461–2494Google Scholar
  100. Tong X-F, Lu H-Q, Liu Q-S (2004) An effective and fast soccer ball detection and tracking method. In: Proceedings of the 17th international conference on pattern recognition. ICPR 2004. IEEE, pp 795–798Google Scholar
  101. Tong X, Liu J, Wang T, Zhang Y (2011) Automatic player labeling, tracking and field registration and trajectory mapping in broadcast soccer video. ACM Trans Intell Syst Technol 2:15CrossRefGoogle Scholar
  102. Uchiyama H, Saito H (2007) AR display of visual aids for supporting pool games by online markerless tracking. In: 17th international conference on artificial reality and telexistence. IEEE, pp 172–179Google Scholar
  103. Wang X, Ablavsky V, Shitrit HB, Fua P (2014a) Take your eyes off the ball: improving ball-tracking by focusing on team play. Comput Vis Image Underst 119:102–115CrossRefGoogle Scholar
  104. Wang X, Türetken E, Fleuret F, Fua P (2014b) Tracking interacting objects optimally using integer programming. In: European conference on computer vision. Springer, pp 17–32Google Scholar
  105. Wang X, Türetken E, Fleuret F, Fua P (2016) Tracking interacting objects using intertwined flows. IEEE Trans Pattern Anal Mach Intell 38:2312–2326CrossRefGoogle Scholar
  106. Wei X, Lucey P, Vidas S, Morgan S, Sridharan S (2014) Forecasting events using an augmented hidden conditional random field. In: Asian conference on computer vision. Springer, pp 569–582Google Scholar
  107. Wong K, Dooley L (2010) High-motion table tennis ball tracking for umpiring applications. In: IEEE 10th international conference on signal processing proceedings. IEEE, pp 2460–2463Google Scholar
  108. Xing J, Ai H, Liu L, Lao S (2011) Multiple player tracking in sports video: a dual-mode two-way bayesian inference approach with progressive observation modeling. IEEE Trans Image Process 20:1652–1667MathSciNetCrossRefzbMATHGoogle Scholar
  109. Yamada A, Shirai Y, Miura J (2002) Tracking players and a ball in video image sequence and estimating camera parameters for 3D interpretation of soccer games. In: 16th international conference on pattern recognition. Proceedings. IEEE, pp 303–306Google Scholar
  110. Yan F, Christmas W, Kittler J (2005) A tennis ball tracking algorithm for automatic annotation of tennis match. In: British machine vision conference, pp 619–628Google Scholar
  111. Yan F, Christmas W, Kittler J (2006a) A maximum a posteriori probability viterbi data association algorithm for ball tracking in sports video. In: 18th international conference on pattern recognition. ICPR 2006. IEEE, pp 279–282Google Scholar
  112. Yan F, Christmas W, Kittler J (2008) Layered data association using graph-theoretic formulation with application to tennis ball tracking in monocular sequences. IEEE Trans Pattern Anal Mach Intell 30:1814–1830CrossRefGoogle Scholar
  113. Yan F, Christmas W, Kittler J (2014) Ball tracking for tennis video annotation. In: Computer vision in sports. Springer, pp 25–45Google Scholar
  114. Yan F, Kostin A, Christmas W, Kittler J (2006) A novel data association algorithm for object tracking in clutter with application to tennis video analysis. In: 2006 IEEE Computer Society conference on computer vision and pattern recognition (CVPR’06). IEEE, pp 634–641Google Scholar
  115. Yow D, Yeo B-L, Yeung M, Liu B (1995) Analysis and presentation of soccer highlights from digital video. In: Proceedings ACCV. Citeseer, pp 499–503Google Scholar
  116. Yu J, Tang Y, Wang Z, Shi L (2007a) Playfield and ball detection in soccer video. In: Advances in visual computing, pp 387–396Google Scholar
  117. Yu X, Hay TS, Yan X, Chng E (2005) A player-possession acquisition system for broadcast soccer video. In: 2005 IEEE international conference on multimedia and expo. IEEE, pp 522–525Google Scholar
  118. Yu X, Jiang N, Cheong L-F, Leong HW, Yan X (2009) Automatic camera calibration of broadcast tennis video with applications to 3D virtual content insertion and ball detection and tracking. Comput Vis Image Underst 113:643–652CrossRefGoogle Scholar
  119. Yu X, Leong HW, Xu C, Tian Q (2004a) A robust and accumulator-free ellipse Hough transform. In: Proceedings of the 12th annual ACM international conference on multimedia. ACM, pp 256–259Google Scholar
  120. Yu X, Leong HW, Xu C, Tian Q (2006) Trajectory-based ball detection and tracking in broadcast soccer video. IEEE Trans Multimed 8:1164–1178CrossRefGoogle Scholar
  121. Yu X, Sim C-H, Wang JR, Cheong LF (2004) A trajectory-based ball detection and tracking algorithm in broadcast tennis video. In: 2004 international conference on image processing. ICIP’04. IEEE, pp 1049–1052Google Scholar
  122. Yu X, Tian Q, Wan KW (2003a) A novel ball detection framework for real soccer video. In: 2003 international conference on multimedia and expo. ICME’03. Proceedings. IEEE, vol 262, pp II-265–II-268Google Scholar
  123. Yu X, Tu X, Ang EL (2007b) Trajectory-based ball detection and tracking in broadcast soccer video with the aid of camera motion recovery. In: 2007 IEEE international conference on multimedia and expo. IEEE, pp 1543–1546Google Scholar
  124. Yu X, Xu C, Leong HW, Tian Q, Tang Q, Wan KW (2003b) Trajectory-based ball detection and tracking with applications to semantic analysis of broadcast soccer video. In: Proceedings of the eleventh ACM international conference on multimedia. ACM, pp 11–20Google Scholar
  125. Yu X, Xu C, Tian Q, Leong HW (2003c) A ball tracking framework for broadcast soccer video. In: 2003 international conference on multimedia and expo. ICME’03. Proceedings. IEEE, vol 272, pp II-273–II-276Google Scholar
  126. Yu X, Xu C, Tian Q, Yan X, Wan KW, Jiang Z (2003d) Estimation of the ball size in broadcast soccer video using salient objects. In: Proceedings of the 2003 joint conference of the fourth international conference on information, communications and signal processing, 2003 and Fourth Pacific Rim conference on multimedia. IEEE, pp 930–934Google Scholar
  127. Yu X, Yan X, Hay TS, Leong HW (2004c) 3D reconstruction and enrichment of broadcast soccer video. In: Proceedings of the 12th annual ACM international conference on multimedia. ACM, pp 260–263Google Scholar
  128. Zaveri MA, Merchant SN, Desai UB (2004) Small and fast moving object detection and tracking in sports video sequences. In: 2004 IEEE international conference on multimedia and expo. ICME’04. IEEE, pp 1539–1542Google Scholar
  129. Zhang Y-h, Wei W, Yu D, Zhong C-w (2011) A tracking and predicting scheme for ping pong robot. J Zhejiang Univ Sci C 12:110–115CrossRefGoogle Scholar
  130. Zhang Z, Xu D, Tan M (2010) Visual measurement and prediction of ball trajectory for table tennis robot. IEEE Trans Instrum Meas 59:3195–3205CrossRefGoogle Scholar
  131. Zhou X, Huang Q, Xie L, Cox S (2013) A two layered data association approach for ball tracking. In: 2013 IEEE international conference on acoustics, speech and signal processing. IEEE, pp 2317–2321Google Scholar
  132. Zhou X, Xie L, Huang Q, Cox SJ, Zhang Y (2015) Tennis ball tracking using a two-layered data association approach. IEEE Trans Multimed 17:145–156CrossRefGoogle Scholar
  133. Zhu G, Xu C, Huang Q, Rui Y, Jiang S, Gao W, Yao H (2009) Event tactic analysis based on broadcast sports video. IEEE Trans Multimed 11:49–67CrossRefGoogle Scholar
  134. Zhu G, Xu C, Zhang Y, Huang Q, Lu H (2008) Event tactic analysis based on player and ball trajectory in broadcast video. In: Proceedings of the 2008 international conference on content-based image and video retrieval. ACM, pp 515–524Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  • Paresh R. Kamble
    • 1
    Email author
  • Avinash G. Keskar
    • 1
  • Kishor M. Bhurchandi
    • 1
  1. 1.Department of Electronics and Communication EngineeringVisvesvaraya National Institute of TechnologyNagpurIndia

Personalised recommendations