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

• Autorzy: Kim H. S. , Yang Y. K.
• Języki publikacji: EN

Abstrakty

EN

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 bith a player and the ball on the ground. The offensive play patterns thet have been formulated from the group formations enable automatic indexing of the highlights of soccer games. Except from actual soccer games, including some from the1998 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%.

Słowa kluczowe

EN

Soccer game; offensive play patterns; neural network; BP algorithm; group formation

• Wydawca: Institute of Information Technology of the Warsaw University of Life Sciences – SGGW
• Czasopismo: Machine Graphics and Vision
• Rocznik: 2001
• Tom: Vol. 10, No. 4
• Strony: 467--487
• Opis fizyczny: Bibliogr. 21 poz.

Twórcy

autor

Kim H. S.

autor

Yang Y. K.

• Department of Computer and Information Processing, Shinsung University, San-49 Deogma-ri, Jeongami-myeon, Dangjin-kun, Chungnam-do, Korea 343-860,