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       This paper presents research work on the detection, tracking, and localization of the soccer ball in a broadcast soccer video and maps the ball locations to the global coordinate system of the soccer field. Because of the lack of reference points in these frames, the calculation of the global coordinates of the ball remains a very challenging task. This paper proposes to use an object-based algorithm and Kalman filter to detect and track the ball in such videos. Once the ball is located, frames are registered to static soccer field, and the absolute ball location is found in the field. The existing feature matching algorithms do not work well for frame registration, especially when involving lighting variations and large camera pan-tile-zoom change. To overcome this challenge, a new feature descriptor and matching algorithm that is robust to these deformations is developed and presented in this paper. Experimental results show the proposed algorithm is very effective and accurate.

 Graduate Students:

  Alok Desai and Craig Wilson

  1. A. Desai, D.J. Lee, and C.N. Wilson, “Determine Absolute Soccer Ball Location in Broadcast Video Using SYBA Descriptor,"Lecture Notes in Computer Science, International Symposium on Visual Computing, p. 588-597, Las Vegas, NV, USA, December 8-10 2014.
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