Detection and classification of football players with automatic generation of models

Jorge Raul Gomez; Elias Herrero Jaraba; Miguel Angel Montañes; Francisco Martinez Contreras; Carlos Orrite-Uruñuela

doi:10.1117/1.3294885

1 January 2010 Detection and classification of football players with automatic generation of models

Jorge Raul Gomez, Elias Herrero Jaraba, Miguel Angel Montañes, Francisco Martinez Contreras, Carlos Orrite-Uruñuela

Author Affiliations +

Optical Engineering, Vol. 49, Issue 1, 017005 (January 2010). https://doi.org/10.1117/1.3294885

Abstract

We focus on the automatic detection and classification of players in a football match. Our approach is not based on any a priori knowledge of the outfits, but on the assumption that the two main uniforms detected correspond to the two football teams. The algorithm is designed to be able to operate in real time, once it has been trained, and is able to detect partially occluded players and update the color of the kits to cope with some gradual illumination changes through time. Our method, evaluated from real sequences, gave better detection and classification results than those obtained by a system using a manual selection of samples to compute a Gaussian mixture model.

©(2010) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Jorge Raul Gomez, Elias Herrero Jaraba, Miguel Angel Montañes, Francisco Martinez Contreras, and Carlos Orrite-Uruñuela "Detection and classification of football players with automatic generation of models," Optical Engineering 49(1), 017005 (1 January 2010). https://doi.org/10.1117/1.3294885

Published: 1 January 2010

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