Self-Calibration of Rotating and Zooming Cameras
International Journal of Computer Vision
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Tracking Players and Estimation of the 3D Position of a Ball in Soccer Games
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Physics-Based 3D Position Analysis of a Soccer Ball from Monocular Image Sequences
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MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Parallel Tracking of All Soccer Players by Integrating Detected Positions in Multiple View Images
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An Effective and Fast Soccer Ball Detection and Tracking Method
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
3D reconstruction and enrichment of broadcast soccer video
Proceedings of the 12th annual ACM international conference on Multimedia
A novel ball detection framework for real soccer video
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1
A scheme for ball detection and tracking in broadcast soccer video
PCM'05 Proceedings of the 6th Pacific-Rim conference on Advances in Multimedia Information Processing - Volume Part I
Proposal of a modular system for tracking indoor and outdoor sports
SMO'09 Proceedings of the 9th WSEAS international conference on Simulation, modelling and optimization
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This paper proposes a new method based on self-calibration to estimate the ball’s 3D position in broadcast soccer video. According to the physical limitation, the ball’s 3D position is estimated through the camera position and the ball’s virtual shadow, which is the point of intersection between the playfield and the line through the camera’s optical center and the ball. First, the virtual shadow is computed by the homography between playfield and image plane. For the image having enough corresponding points, the map is determined directly; for those images not having enough these points, their homographies are estimated through global motion estimation. Then, based on self-calibrating for rotating and zooming camera, and the homography, the camera’s position in the playfield is estimated. Experiments show that the proposed method can extract ball’s 3D position information without referring to other object with assuming height and obtain promising results.