Abstract
This paper proposes a scheme to detect and locate the players and the ball on the grass playfield in soccer videos. We put forward a shape analysis-based approach to identify the players and the ball from the roughly extracted foreground, which is obtained by a trained, color histogram-based playfield detector and connected component analysis. We employ Euclidean distance transform to extract skeletons for every foreground blob, and then perform shape analysis to remove false alarms (non-player and non-ball blobs) and cut-off the artifacts (mostly due to playfield lines) based on skeleton pruning and reverse Euclidean distance transform. Results are given to demonstrate the proposed algorithm works well in soccer video clips.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Choi, S., Seo, Y., et al.: Where are the ball and players? Soccer game analysis with color-based tracking and image mosaic. In: Int. Conf. on Image Analysis and Processing (September 1997)
Coeurjolly, D., Montanvert, A.: Optimal Separable Algorithms to Compute the Reverse Euclidean Distance Transformation and Discrete Medial Axis in Arbitrary Dimension. IEEE T-PAMI 29(3), 437–448 (2007)
Gong, Y., Sin, L.T., Chuan, C.H., Zhang, H., Sakauchi, M.: Automatic parsing of TV soccer programs. In: Proc. Multimedia Computing & Systems, pp. 167–174 (1995)
Haritaoglu, I., Harwood, D., Davis, L.S.: Hydra: multiple people detection and tracking using silhouettes. In: 2nd IEEE Workshop on Visual Surveillance (1999)
He, L., Han, C.Y., Wee, W.G.: Object recognition and recovery by skeleton graph matching. In: IEEE ICME’06 (2006)
Jones, M., Rehg, J.M.: Statistical Color Models with Application to Skin Detection. In: IEEE CVPR’99, June 1999, pp. 274–280 (1999)
Liang, D., et al.: A scheme for ball detection and tracking in broadcast soccer video. In: PCM 2005, Korea (2005)
Liu, Y., Jiang, S., Ye, Q., Gao, W., Huang, Q.: Playfield Detection Using Adaptive GMM and Its Application. In: IEEE ICASSP ’05, March 2005, pp. 421–424 (2005)
Needham, C.J., Boyle, R.D.: Tracking multiple sports players through occlusion, congestion and scale. BMVC’01 1, 93–102 (2001)
Nementhova, O., Zahumensky, M., Rupp, M.: Preprocessing of ball game video sequences for robust transmission over mobile network. In: CDMA International Conference (CIC), Seoul (2004)
D’Orazio, T., et al.: A Ball Detection Algorithm for Broadcast Soccer Image Sequences. In: IAPR ICPR’02 (2002)
Ozcanli, O.C., Tamrakar, A., Kimia, B.B.: Augmenting Shape with Appearance in Vehicle Category Recognition. In: IEEE CVPR’06, June 2006, pp. 935–942 (2006)
Renno, J., Orwell, J., Thirde, D., Jones, G.A.: Shadow Classification and Evaluation for Soccer Player Detection. In: BMVC’04, September 2004, Kingston (2004)
Tam, R.C., Heidrich, W.: Feature-Preserving Medial Axis Noise Removal. In: ECCV’02, pp. 672–686 (2002)
Tong, X., et al.: An Effective and Fast Soccer Ball Detection and Tracking Method. In: ICPR’04, pp. 795–798 (2004)
Utsumi, O., Miura, K., Ide, I., Sakai, S., Tanaka, H.: An object detection method for describing soccer games from video. In: IEEE ICME ’02 (2002)
Wang, J.R., Parameswaran, N.: Survey of Sports Video Analysis: research issues and applications. In: Pan Sydney Area Workshop on Visual Information Processing (VIP03) (2003)
Yu, X., Xu, C., Tian, Q., Leong, H.W.: A ball tracking framework for broadcast soccer video. In: ICME’03 (2003)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Huang, Y., Llach, J., Bhagavathy, S. (2007). Players and Ball Detection in Soccer Videos Based on Color Segmentation and Shape Analysis. In: Sebe, N., Liu, Y., Zhuang, Y., Huang, T.S. (eds) Multimedia Content Analysis and Mining. MCAM 2007. Lecture Notes in Computer Science, vol 4577. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73417-8_50
Download citation
DOI: https://doi.org/10.1007/978-3-540-73417-8_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73416-1
Online ISBN: 978-3-540-73417-8
eBook Packages: Computer ScienceComputer Science (R0)