Automatic Parsing of TV Soccer Programs
ICMCS '95 Proceedings of the International Conference on Multimedia Computing and Systems
An Introduction to the Kalman Filter
An Introduction to the Kalman Filter
An Effective and Fast Soccer Ball Detection and Tracking Method
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
A ball tracking framework for broadcast soccer video
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1
Tracking and labelling of interacting multiple targets
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
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
Data sharing analysis of emerging parallel media mining workloads
HiPC'08 Proceedings of the 15th international conference on High performance computing
ACM Transactions on Intelligent Systems and Technology (TIST)
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A three-level method is proposed to achieve robust and real-time ball tracking in soccer videos. It includes object-, intra-trajectory-, and intertrajectory-level processing. Due to much noise and frequent occlusion, it's difficult to get the solely ball in one frame. Thus, in object level, multiple objects instead of a single one are detected and taken as ball candidates with shape and color features. Then at intra-trajectory level, each ball candidate is tracked by a Kalman filter in successive frames, which results in lots of initial trajectories in a video segment. These trajectories are thereafter scored and filtered according to their length and relationship in a time-line model. With these trajectories, we construct a distance graph, in which a node represents a trajectory, and an edge means distance between two trajectories. We use the Dijkstra algorithm to get the optimal path in the graph at the inter-trajectory level. To smooth the trajectory, we finally apply cubic spline interpolation to bridge the gap between adjacent trajectories. The algorithm is tested on broadcast soccer games in FIFA2006 and got the F-score 80.26%. The whole speed far exceeds real-time, 35.6 fps on mpeg2 data.