Citas bibligráficas
Laboriano, A., (2024). Clasificación automática de eventos en videos de fútbol utilizando redes convolucionales profundas [Pontificia Universidad Católica del Perú]. http://hdl.handle.net/20.500.12404/28089
Laboriano, A., Clasificación automática de eventos en videos de fútbol utilizando redes convolucionales profundas []. PE: Pontificia Universidad Católica del Perú; 2024. http://hdl.handle.net/20.500.12404/28089
@mastersthesis{renati/532680,
title = "Clasificación automática de eventos en videos de fútbol utilizando redes convolucionales profundas",
author = "Laboriano Galindo, Alipio",
publisher = "Pontificia Universidad Católica del Perú",
year = "2024"
}
The way the new generations consume and experiment sports, especially soccer, has generated significant opportunities in the dissemination of sports content on non-traditional platforms and in smaller formats. However, retrieving information with semantic content of sporting events presented in video format is not an easy task and poses several challenges. In videos of soccer matches, among other challenges we have: the positions of the recording cameras, the overlapping of events or plays and the huge amount of frames available. In order to generate quality summaries that are interesting for the fan, this research developed a system based on Deep Convolutional Networks to automatically classify events or plays that occur during a soccer match. For this purpose, a database was built from soccer videos downloaded from SoccerNet, which contains 1,959 video clips of 5 events: goal kicks, corner kicks, fouls, indirect free kicks and shots on target. For the experimentation, video preprocessing techniques were used, a proprietary convolutional architecture and transfer learning was applied with models such as ResNet50, EfficientNetb0, Vision Transformers and Video Vision Transformers. The best result was obtained with a modified EfficentNetb0 in its first convolutional layer, with which 91% accuracy was obtained, and an accuracy of 100% for goal kicks, 92% for corner kicks, 90% for fouls committed, 88% for indirect free kicks and 89% for shots on target.
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