KaliCalib: A Framework for Basketball Court Registration - CEA - Commissariat à l’énergie atomique et aux énergies alternatives Access content directly
Conference Papers Year : 2022

KaliCalib: A Framework for Basketball Court Registration

Abstract

Tracking the players and the ball in team sports is key to analyse the performance or to enhance the game watching experience with augmented reality. When the only sources for this data are broadcast videos, sports-field registration systems are required to estimate the homography and re-project the ball or the players from the image space to the field space. This paper describes a new basketball court registration framework in the context of the MMSports 2022 camera calibration challenge. The method is based on the estimation by an encoder-decoder network of the positions of keypoints sampled with perspective-aware constraints. The regression of the basket positions and heavy data augmentation techniques make the model robust to different arenas. Ablation studies show the positive effects of our contributions on the challenge test set. Our method divides the mean squared error by 4.7 compared to the challenge baseline.
Fichier principal
Vignette du fichier
KaliCalib.pdf (10.25 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

cea-03823869 , version 1 (21-10-2022)

Identifiers

Cite

Adrien Maglo, Astrid Orcesi, Quoc-Cuong Pham. KaliCalib: A Framework for Basketball Court Registration. 5th International ACM Workshop on Multimedia Content Analysis in Sports (MMSports '22), ACM, Oct 2022, Lisbonne, Portugal. pp.Pages 111-116, ⟨10.1145/3552437.3555701⟩. ⟨cea-03823869⟩
17 View
109 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More