Desiree Doronzo
Computer Vision Methods for 2D Ball Trajectory Extraction to Support Tennis Analytics.
Rel. Fabrizio Lamberti. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2025
Abstract
Trajectory estimation plays a crucial part in tennis analytics, as the ball’s flight path encapsulates a wealth of valuable information that can be exploited to enhance player’s performance. The goal of this thesis is to extract the complete trajectory of the tennis ball using suitable detection and tracking techniques, aiming to subsequently use this data, e.g., for evaluating shot effectiveness in future applications. To reach this goal several challenges need to be addressed, related to the ball’s physical characteristics – such as its small size and high speed – as well as external issues like occlusions from foreign objects, misdetection, or inactive balls in the background.
Although previous studies have demonstrated robust and accurate trajectory extraction, they often rely on restrictive assumptions, such as the presence of a single ball
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