Distributed real-time soccer tracking
Proceedings of the ACM 2nd international workshop on Video surveillance & sensor networks
Live 3D Video in Soccer Stadium
International Journal of Computer Vision
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
3D Tracking by Catadioptric Vision Based on Particle Filters
RoboCup 2007: Robot Soccer World Cup XI
Video analysis of hockey play in selected game situations
Image and Vision Computing
Tracking and recognizing actions of multiple hockey players using the boosted particle filter
Image and Vision Computing
A novel hierarchical Bayesian HMM for multi-dimensional discrete data
AIA '08 Proceedings of the 26th IASTED International Conference on Artificial Intelligence and Applications
Real-time soccer player tracking method by utilizing shadow regions
Proceedings of the international conference on Multimedia
Strategy diagram for identifying play strategies in multi-view soccer video data
DS'06 Proceedings of the 9th international conference on Discovery Science
A visualization framework for team sports captured using multiple static cameras
Computer Vision and Image Understanding
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This paper presents a technique for integrating multiple visual features for tracking moving objects. Our proposed method consists of observation (pattern-matching) units and prediction units, which form a ladder structure.The major feature of our proposed method is that each of the observation units with different pattern matching algorithms is executed step-by-step to innovate the state vector considering the reliability of the observation. The fusion of multiple observations makes the tracks robust to occlusion and to deformation.In this paper, experiments with soccer sequences are shown to validate the technique's robustness. Its applications to broadcasting services are also briefly discussed.