In this work, we propose a robust classification system that estimates the advertising
panels visibility in real time. For each frame of the sequence, a set of descriptors is
extracted to characterize a specific part of the scene: the grass field. Gathering all
these descriptors, a decision tree determines whether the LED panels are visible in
that frame. In order to improve the robustness of the algorithm, the redundancy of
the temporal domain is exploited.
The validity of the proposed algorithm has been tested on a large amount of frames
representing 250 minutes of broadcasted football sequences in a wide variety of
scenarios. Promising results have been obtained with a 95% of accuracy in the
classification of these images.
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