Who will receive the ball? Predicting pass recipient in soccer videos

Article Type

Research Article

Publication Title

Journal of Visual Communication and Image Representation


The game of soccer involves an act of one team trying to score a goal against the other. During the game, defending players constantly try to predict the pass of the attacking player to prevent a goal. So, pass prediction is an important facet to anticipate the game strategy of participating teams. Here we present a probabilistic framework for pass prediction. Aberrating the state-of-the-art notion of mutually independent decision models, the proposed framework predicts pass recipients by integrating two dependent models, designed from the coordinates of the players in abstract top-view visualization. To evaluate the real time efficacy of the proposed pass prediction framework, a soccer data set has been introduced. The proposed pass prediction algorithm is compared against recent methods and the ground truth available in the soccer data set. The proposed method outperforms the existing approaches by a noticeable margin.



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