A trajectory-based ball detection and tracking system with applications to shot-type identification in volleyball videos

This paper presents a trajectory-based ball detection and tracking algorithm for volleyball videos to classify the different types of shots in the game. In case of volleyball games, the task of ball detection and tracking become more complex due to the presence of too many number of players in a rather small space. The direct detection methods often fail due to the high rate of occlusion of the ball image with players. The distortion of the ball image due to the effect of ball and camera motion leads to a number of wrong detection. In this paper, the trajectory information of a volleyball for different shot sequences is studied and used to estimate the ball locations. The ball candidates are generated using the shape and size features. A Kalman filter-based approach is used to generate a set of candidate trajectories. The actual ball trajectory is extracted by analysing the physical characteristics of the ball motion. The trajectory informations are then used to classify the different shot sequences in the volleyball game for better representation and analysis.

[1]  Mei Han,et al.  Baseball scene classification using multimedia features , 2002, Proceedings. IEEE International Conference on Multimedia and Expo.

[2]  Cataldo Guaragnella,et al.  A new algorithm for ball recognition using circle Hough transform and neural classifier , 2004, Pattern Recognit..

[3]  Wei-Ta Chu,et al.  Extraction of Baseball Trajectory and Physics-Based Validation for Single-View Baseball Video Sequences , 2006, 2006 IEEE International Conference on Multimedia and Expo.

[4]  Chandrika Kamath,et al.  Robust techniques for background subtraction in urban traffic video , 2004, IS&T/SPIE Electronic Imaging.

[5]  Yongduek Seo,et al.  Where Are the Ball and Players? Soccer Game Analysis with Color Based Tracking and Image Mosaick , 1997, ICIAP.

[6]  J. L. Roux.  An Introduction to the Kalman Filter , 2003 .

[7]  Changsheng Xu,et al.  Robust goal-mouth detection for virtual content insertion , 2003, MULTIMEDIA '03.

[8]  Boon-Lock Yeo,et al.  Analysis And Presentation Of Soccer Highlights From Digital Video , 1995 .

[9]  S. Meher,et al.  Real-time position estimation and tracking of a basketball , 2012, 2012 IEEE International Conference on Signal Processing, Computing and Control.

[10]  Hua-Tsung Chen,et al.  A Trajectory-Based Ball Tracking Framework with Visual Enrichment for Broadcast Baseball Videos , 2008, J. Inf. Sci. Eng..

[11]  Mohinder S. Grewal,et al.  Kalman Filtering: Theory and Practice Using MATLAB , 2001 .

[12]  Alberto Del Bimbo,et al.  Semantic annotation of soccer videos: automatic highlights identification , 2003, Comput. Vis. Image Underst..

[13]  Yongdong Zhang,et al.  Automatic Detection and Analysis of Player Action in Moving Background Sports Video Sequences , 2010, IEEE Transactions on Circuits and Systems for Video Technology.

[14]  Sukadev Meher,et al.  2D Trajectory-based Position Estimation and Tracking of the Ball in a Basketball Video , 2011 .

[15]  Qi Tian,et al.  Trajectory-Based Ball Detection and Tracking in Broadcast Soccer Video , 2006, IEEE Transactions on Multimedia.

[16]  G C Dean,et al.  An Introduction to Kalman Filters , 1986 .