Semantic annotation of soccer videos: automatic highlights identification
Computer Vision and Image Understanding - Special isssue on video retrieval and summarization
A novel ball detection framework for real soccer video
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1
Automatic soccer video analysis and summarization
IEEE Transactions on Image Processing
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Soccer video processing for the detection of advertisement billboards
Pattern Recognition Letters
Anthropocentric video segmentation for lecture webcasts
Journal on Image and Video Processing - Anthropocentric Video Analysis: Tools and Applications
Playfield and ball detection in soccer video
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
Situation analysis and atypical event detection with multiple cameras and multi-object tracking
RobVis'08 Proceedings of the 2nd international conference on Robot vision
Generalized playfield segmentation of sport videos using color features
Pattern Recognition Letters
An unsupervised method for active region extraction in sports videos
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
Visual features extraction through spatiotemporal slice analysis
MMM'07 Proceedings of the 13th International conference on Multimedia Modeling - Volume Part II
Action recognition in broadcast tennis video using optical flow and support vector machine
ECCV'06 Proceedings of the 2006 international conference on Computer Vision in Human-Computer Interaction
Traffic observation and situation assessment
Proceedings of the 15th international conference on Theoretical Foundations of Computer Vision: outdoor and large-scale real-world scene analysis
Football video annotation based on player motion recognition using enhanced entropy
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advences in computational intelligence - Volume Part II
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With the growing popularity of digitized sports video, automatic analysis of them need be processed to facilitate semantic summarization and retrieval. Playfield plays the fundamental role in automatically analyzing many sports programs. Many semantic clues could be inferred from the results of playfield segmentation. In this paper, a novel playfield segmentation method based on Gaussian mixture models (GMMs) is proposed. Firstly, training pixels are automatically sampled from frames. Then, by supposing that field pixels are the dominant components in most of the video frames, we build the GMMs of the field pixels and use these models to detect playfield pixels. Finally region-growing operation is employed to segment the playfield regions from the background. Experimental results show that the proposed method is robust to various sports videos even for very poor grass field conditions. Based on the results of playfield segmentation, match situation analysis is investigated, which is also desired for sports professionals and longtime fanners. The results are encouraging.