An automatic classification technique for indexing of soccer highlights using neural networks

Authors:
Hyun Sook Kim;Young Kyu Yang
Affiliations:
Department of Computer and Information Processing, Shinsung University, San-49 Deogma-ri, Jeongmi-myeon, Dangjin-kun, Chungnam-do, Korea 343-860;Image Processing Dept., Electronics and Telecommunications Research Institute, 161 Kajong-dong, Yusong -ku, Taejon Korea 305-350
Venue:
Machine Graphics & Vision International Journal
Year:
2001

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Abstract

A method for automatic classification of offensive play patterns in soccer games has been developed using the neural networks technique. Back-propagation (BP) neural network techniques have been applied to obtain data that define the positions of both a player and the ball on the ground. The offensive play patterns that have been formulated from the group formations enable automatic indexing of the highlights of soccer games. Excepts from actual soccer games, including some from the 1998 French World Cup, yielded 297 video clips which were categorized into the following five types of patterns: Left-Running are 60, Right-Running 74, Center-Running 72, Corner-Kick 39 and Free-Kick 52. Examination of the results shows the following rates of satisfactory pattern recognition: Left-Running comes to 91.7%, Right-Running 100%, Center-Running 87.5%, Corner-Kick 97.4% and Free-Kick 75%.