Abstract
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.
This work is partly supported by NEC Research China and “Science 100 Plan” of Chinese Academy of Sciences.
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Liu, Y., Liang, D., Huang, Q., Gao, W. (2006). Self-calibration Based 3D Information Extraction and Application in Broadcast Soccer Video. In: Narayanan, P.J., Nayar, S.K., Shum, HY. (eds) Computer Vision – ACCV 2006. ACCV 2006. Lecture Notes in Computer Science, vol 3852. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11612704_85
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DOI: https://doi.org/10.1007/11612704_85
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