Multimedia retrieval through spatio-temporal activity maps
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
Proceedings of the conference on Visualization '01
Survey of sports video analysis: research issues and applications
VIP '05 Proceedings of the Pan-Sydney area workshop on Visual information processing
An Automated Refereeing and Analysis Tool for the Four-Legged League
RoboCup 2006: Robot Soccer World Cup X
Journal of Visual Communication and Image Representation
Recovering ball motion from a single motion-blurred image
Computer Vision and Image Understanding
Automatic Golf Ball Trajectory Reconstruction and Visualization
MIRAGE '09 Proceedings of the 4th International Conference on Computer Vision/Computer Graphics CollaborationTechniques
Tennissense: a platform for extracting semantic information from multi-camera tennis data
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
A ball tracking system for offline tennis videos
VIS'08 Proceedings of the 1st WSEAS international conference on Visualization, imaging and simulation
Real-Time acrobatic gesture analysis
GW'05 Proceedings of the 6th international conference on Gesture in Human-Computer Interaction and Simulation
A scheme for ball detection and tracking in broadcast soccer video
PCM'05 Proceedings of the 6th Pacific-Rim conference on Advances in Multimedia Information Processing - Volume Part I
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This paper presents a real-time computer vision system that tracks the motion of a tennis ball in 3D using multiple cameras. Ball tracking enables virtual replays, new game statistics, and other visualizations, which result in very new ways of experiencing and analyzing tennis matches. The system has been used in international television broadcasts and webcasts of more than 15 matches. Six cameras around a stadium, divided into four pairs, are currently used to track the ball on serves, which sometimes exceed speeds of 225 kmph. A multi-threaded approach is taken to tracking where each thread tracks the ball in a pair of cameras based on motion, intensity and shape, performs stereo matching to obtain the 3D trajectory, detects when a ball goes out of view of its camera pair, and initializes and triggers a subsequent thread. This efficient approach is scalable to many more cameras tracking multiple objects. The ready acceptance of the system indicates the growing potential for multi-camera based real-time tracking in broadcast applications.