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Real-Time Statistics for Padel Tennis Using Artificial Intelligence
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| 16.65 MB | Adobe PDF |
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Advisor(s)
Abstract(s)
O Padel, desporto conhecido pelo seu crescimento explosivo e jogabilidade emocionante,
está à beira de uma revolução tecnológica. Com o objetivo de transformar o jogo de Padel
através do uso criativo de técnicas de deteção de objetos e Deep Learning, esta dissertação de
mestrado investiga a junção da Inteligência Arti cial (IA) e do Padel. O principal objetivo é
usar a IA para produzir estatísticas em tempo real que darão aos jogadores, treinadores e fãs
um melhor conhecimento das complexidades do Padel e dos meios para levar o jogo a novos
patamares.
Esta dissertação explora a monitorização e localização em tempo real dos jogadores e
da bola dentro do campo, através de algoritmos de visão computacional. As Redes Neu ronais de Convolução (RNC), um tipo de modelo de Deep Learning, são essenciais para o
reconhecimento preciso de eventos e ações importantes durante o jogo.
A criação de um sistema baseado em IA que produz dados instantâneos para partidas de
Padel é a inovação central desta dissertação. Estas estatísticas oferecem uma visão analítica
e detalhada de cada jogo, tendo em consideração os movimentos dos jogadores, as trajetórias
da bola e a dinâmica do jogo. Esta dissertação não promove apenas o Padel, mas também
cria novas oportunidades para a utilização de IA em outros desportos.
The sport of Padel, known for its explosive growth and exciting gameplay, is on the verge of a technological revolution. With the goal of transforming the game of Padel through the creative use of object detection and deep learning techniques, this master's thesis investi gates the junction of Arti cial Intelligence (AI) and Padel. The main goal is to use AI to produce real-time statistics that will give players, coaches and fans a better knowledge of the complexities of Padel and the means to take the game to new heights. This dissertation explores the real-time tracking and localization of players and the ball within the court by utilizing cutting-edge computer vision algorithms. Convolution Neural Networks (CNN), one type of deep learning model, are essential for the precise recognition of important gaming events and actions. The creation of an AI-driven system that produces in-the-moment data for Padel matches is the central innovation of this dissertation. These statistics o er a detailed and analytical view of each game by taking into account player movements, ball trajectories, and game dynamics. This dissertation not only advances the sport of Padel but also creates new op portunities for the use of AI in other sports analytics.
The sport of Padel, known for its explosive growth and exciting gameplay, is on the verge of a technological revolution. With the goal of transforming the game of Padel through the creative use of object detection and deep learning techniques, this master's thesis investi gates the junction of Arti cial Intelligence (AI) and Padel. The main goal is to use AI to produce real-time statistics that will give players, coaches and fans a better knowledge of the complexities of Padel and the means to take the game to new heights. This dissertation explores the real-time tracking and localization of players and the ball within the court by utilizing cutting-edge computer vision algorithms. Convolution Neural Networks (CNN), one type of deep learning model, are essential for the precise recognition of important gaming events and actions. The creation of an AI-driven system that produces in-the-moment data for Padel matches is the central innovation of this dissertation. These statistics o er a detailed and analytical view of each game by taking into account player movements, ball trajectories, and game dynamics. This dissertation not only advances the sport of Padel but also creates new op portunities for the use of AI in other sports analytics.
Description
Keywords
Inteligência artificial Redes neuronais de convolução Padel Artificial intelligence Convolution neural networks Mathematics Statistics and Applications . Faculdade de Ciências Exatas e da Engenharia