CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Where Are the Ball and Players? Soccer Game Analysis with Color Based Tracking and Image Mosaick
ICIAP '97 Proceedings of the 9th International Conference on Image Analysis and Processing-Volume II
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Vision and Image Understanding
Automatic Parsing of TV Soccer Programs
ICMCS '95 Proceedings of the International Conference on Multimedia Computing and Systems
Sports video processing for description, summarization and search
Sports video processing for description, summarization and search
Parallel Tracking of All Soccer Players by Integrating Detected Positions in Multiple View Images
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Hierarchical Indexing Structure for Efficient Similarity Search in Video Retrieval
IEEE Transactions on Knowledge and Data Engineering
ACM Computing Surveys (CSUR)
Soccer video analysis by ball, player and referee tracking
SAICSIT '06 Proceedings of the 2006 annual research conference of the South African institute of computer scientists and information technologists on IT research in developing countries
Trajectory Analysis for Soccer Players
ICDMW '06 Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops
Automatic soccer players tracking in goal scenes by camera motion elimination
Image and Vision Computing
Tracking soccer players aiming their kinematical motion analysis
Computer Vision and Image Understanding
Automatic soccer video analysis and summarization
IEEE Transactions on Image Processing
Event detection in field sports video using audio-visual features and a support vector Machine
IEEE Transactions on Circuits and Systems for Video Technology
Enhancing multi-lingual information extraction via cross-media inference and fusion
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
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A video stream is usually massive in terms of data content with abundant information. In the past, extracting explicit semantic information from a video stream; i.e. object detection, object tracking and information extraction; has been extensively investigated. However, little work has been devoted on the problem of discovering global or implicit information from huge video streams. In this paper, a framework has been presented for extracting information for a specified player from soccer video broadcast by data mining techniques. Concepts and information which exist in a soccer video broadcast are useful for team coaches. But, due to various reasons; i.e. wide field of view of a video stream, huge data, existence of great number of important objects in the play field of a soccer match and the occurrence of number of important events, manual extraction of information from soccer video broadcast is difficult and time consuming task. In this paper, a set of techniques is presented that automatically extract some useful information of a player, i.e. velocity and traversed distance, from a soccer video broadcast. Processing of video sequence under change of lighting conditions, fast camera movement and player`s occlusion is a challenging task. Our proposed framework comprise of 3 stages, player segmentation, player tracking and information extraction. All three stages must be robust under various challenges. The performance of our proposed system has been evaluated using a variety of soccer video broadcast having different characteristics in term of lighting conditions. The experiments showed that the efficiency of our system is satisfactory.