Football Penalty Kick Prediction Model Based on Kicker's Pose Estimation

Josue Angel Mauricio Salazar, Hugo Alatrista-Salas

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

This paper describes an innovative methodology for predicting penalty kicks in football based on the pose estimation of the kicker. Our proposal starts with the construction of a corpus of penalty kick videos. Then, we combine semantic video segmentation and 3D pose estimation using the TAM and MMPose methods. For the prediction of the goal area where the kick would land, three deep-learning models were compared, as well as the study of the part of the player's body that affects the prediction task.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 2024 9th International Conference on Machine Learning Technologies, ICMLT 2024
EditorialAssociation for Computing Machinery
Páginas196-203
Número de páginas8
ISBN (versión digital)9798400716379
DOI
EstadoPublicada - 24 may. 2024
Evento9th International Conference on Machine Learning Technologies, ICMLT 2024 - Oslo, Noruega
Duración: 24 may. 202426 may. 2024

Serie de la publicación

NombreACM International Conference Proceeding Series

Conferencia

Conferencia9th International Conference on Machine Learning Technologies, ICMLT 2024
País/TerritorioNoruega
CiudadOslo
Período24/05/2426/05/24

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