Multi-Camera Analysis of Soccer Sequences

The automatic detection of meaningful phases in a soccergame depends on the accurate localization of playersand the ball at each moment. However, the automatic analysisof soccer sequences is a challenging task due to thepresence of fast moving multiple objects. For this purpose,we present a multi-camera analysis system that yields theposition of the ball and players on a common ground plane.The detection in each camera is based on a code-book algorithmand different features are used to classify the detectedblobs. The detection results of each camera are transformedusing homography to a virtual top-view of the playing field.Within this virtual top-view we merge trajectory informationof the different cameras allowing to refine the foundpositions. In this paper, we evaluate the system on a publicSOCCER dataset and end with a discussion of possibleimprovements of the dataset.

[1]  Ming Xu,et al.  Multi-camera video surveillance for real-time analysis and reconstruction of soccer games , 2010, Machine Vision and Applications.

[2]  Larry S. Davis,et al.  Real-time foreground-background segmentation using codebook model , 2005, Real Time Imaging.

[3]  Wen Gao,et al.  A Scheme for Ball Detection and Tracking in Broadcast Soccer Video , 2005, PCM.

[4]  Mohan M. Trivedi,et al.  Homography-based Analysis of People and Vehicle Activities in Crowded Scenes , 2007, 2007 IEEE Workshop on Applications of Computer Vision (WACV '07).

[5]  Tiziana D'Orazio,et al.  A ball detection algorithm for real soccer image sequences , 2002, Object recognition supported by user interaction for service robots.

[6]  Liu Hua-Yong,et al.  Semantic Event Mining in Soccer Video Based on Multiple Feature Fusion , 2009, 2009 International Conference on Information Technology and Computer Science.

[7]  Wen Gao,et al.  Trajectory based event tactics analysis in broadcast sports video , 2007, ACM Multimedia.

[8]  Jin Hyeong Park,et al.  Performance evaluation of object detection algorithms , 2002, Object recognition supported by user interaction for service robots.

[9]  Shamik Sural,et al.  Ball detection from broadcast soccer videos using static and dynamic features , 2008, J. Vis. Commun. Image Represent..

[10]  Mubarak Shah,et al.  Tracking Multiple Occluding People by Localizing on Multiple Scene Planes , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Xinguo Yu,et al.  Current and Emerging Topics in Sports Video Processing , 2005, 2005 IEEE International Conference on Multimedia and Expo.

[12]  Tiziana D'Orazio,et al.  Multi-view Player Action Recognition in Soccer Games , 2009, MIRAGE.

[13]  Steven Verstockt,et al.  Multi-view Object Localization in H.264/AVC Compressed Domain , 2009, 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance.

[14]  Tiziana D'Orazio,et al.  A Semi-automatic System for Ground Truth Generation of Soccer Video Sequences , 2009, 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance.