| KEYWORD |
Area Engineering
Artificial Intelligence techniques for analyzing tennis players' performance
Thesis in external company
keywords ARTIFICIAL INTELLIGENCE, COMPUTER VISION, DEEP LEARNING, NEURAL NETWORKS, SPORT
Reference persons FABRIZIO LAMBERTI
Research Groups DAUIN - GR-09 - GRAphics and INtelligent Systems - GRAINS
Thesis type THESIS IN COLLAB. W/ A COMPANY, THESIS WITH A COMPANY
Description Several new thesis proposals are available, which will be developed in collaboration with HyperTennis (https://hypertennis.it/) a startup / spin-off of Politecnico di Torino. HyperTennis is designing solutions for the application of Artificial Intelligence and other technologies to analyze and improve the performance of tennis players. Thesis works will require the application of Computer Vision and Deep Learning techniques to:
1) perform high-speed, Human Pose Estimation and extract the articulated 3D model of the tennis players from the video feed coming from multiple, synchronized cameras
2) identify relevant tennis players' actions in the execution of technical gestures, i.e. shots (serve, forehand, backhand, etc.)
3) extract accurate information about the ball (trajectories and impact with the racket) and the field
4) automatically classify shot type
5) identify/separate specific phases in the execution of a shot
6) predicting next shot based on historical data
See also http://grains.polito.it/work.php
Deadline 15/11/2025
PROPONI LA TUA CANDIDATURA