W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Soccer Image Sequence Computed by a Virtual Camera
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
Probabilistic Integration of Tracking and Recognition of Soccer Players
MMM '09 Proceedings of the 15th International Multimedia Modeling Conference on Advances in Multimedia Modeling
A novel multimedia data mining framework for information extraction of a soccer video stream
Intelligent Data Analysis
IEEE Transactions on Circuits and Systems for Video Technology
A review of vision-based systems for soccer video analysis
Pattern Recognition
Soccer formation classification based on fisher weight map and Gaussian mixture models
LKR'08 Proceedings of the 3rd international conference on Large-scale knowledge resources: construction and application
A method for identification of moving objects by integrative use of a camera and accelerometers
Proceedings of the 27th Annual ACM Symposium on Applied Computing
3D reconstruction of soccer sequences using non-calibrated video cameras
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
A multiple camera methodology for automatic localization and tracking of futsal players
Pattern Recognition Letters
Hi-index | 0.00 |
In this work, we consider the problem of tracking players, during a soccer game, through the use of multiple cameras. The main goal here consists in finding the position of the players on the pitch at each instance of time. The tracking is performed through a graph representation in which the nodes correspond to the blobs obtained by image segmentation and the edges, weighted using the blobs information and trajectory in the image sequence, represent the distance between nodes. We present a new way of trating occlusions by splitting segmented blobs based on morphological operators and a backward and forward graph representation which allows an increasing in the number of frames automatically tracked. Unlike other works in which the analysis of short video sequences is presented, this paper illustrates the tracking results for all the players during a whole game.