Tracking Human Motion in Structured Environments Using a Distributed-Camera System
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
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
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
A Noniterative Greedy Algorithm for Multiframe Point Correspondence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-Time Wide Area Multi-Camera Stereo Tracking
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Tracking soccer players aiming their kinematical motion analysis
Computer Vision and Image Understanding
Trajectory based event tactics analysis in broadcast sports video
Proceedings of the 15th international conference on Multimedia
Trajectory Association across Multiple Airborne Cameras
IEEE Transactions on Pattern Analysis and Machine Intelligence
Visually tracking football games based on TV broadcasts
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Moving object segmentation by background subtraction and temporal analysis
Image and Vision Computing
Multi-view object tracking using sequential belief propagation
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
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In this paper, we propose a distributed sensing algorithm that integrates players' trajectories observed from multiple cameras during a football game. Football scenes present several situations where players occlude each other, thus generating ambiguities that may lead to tracking failures. The integration of tracks from different views may help disambiguate players tracks. The proposed approach first uses homography to synthesize the ground plane virtual top-view and then transforms players locations from the camera image plane to the ground plane. Finally, the tracking on the ground plane is performed applying the graph theory. We demonstrate the results of our algorithm on football scenario.