Efficient One-Shot Sports Field Image Registration with Arbitrary Keypoint Segmentation
In: IEEE International Conference on Image Processing ; https://hal.science/hal-03738153 ; IEEE International Conference on Image Processing, Oct 2022, Bordeaux, France. ⟨10.1109/ICIP46576.2022.9897170⟩, 2022
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International audience ; Automatic sports field registration aims at projecting a given image taken with unknown camera parameters to a known 3D coordinate system in order to obtain higher-level information like the position and speed of players. Existing methods generally detect specific visual landmarks on the field and then use an iterative refinement to get closer to the desired calibration. They are usually only compared in terms of precision on a standard benchmark without considering other metrics. However, execution speed is also important, mainly in the context of live broadcast TV and sports analysis. This work introduces a new automatic field registration method achieving excellent performance on the WorldCup Soccer benchmark, while neither depending on specific visible landmarks nor any refinement, resulting in a very high execution speed one-shot model. Finally, to complement the usual Soccer benchmark, we introduce a new Swimming Pool registration benchmark which is more challenging for the task at hand. Code and dataset available at https://github.com/ njacquelin/sports field registration.
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Efficient One-Shot Sports Field Image Registration with Arbitrary Keypoint Segmentation
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Autor/in / Beteiligte Person: | Jacquelin, Nicolas ; Vuillemot, Romain ; Duffner, Stefan ; Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS) ; Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL) ; Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL) ; Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon) ; Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS) ; Extraction de Caractéristiques et Identification (imagine) ; Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL) ; Situated Interaction, Collaboration, Adaptation and Learning (SICAL) |
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Zeitschrift: | IEEE International Conference on Image Processing ; https://hal.science/hal-03738153 ; IEEE International Conference on Image Processing, Oct 2022, Bordeaux, France. ⟨10.1109/ICIP46576.2022.9897170⟩, 2022 |
Veröffentlichung: | HAL CCSD, 2022 |
Medientyp: | Konferenz |
DOI: | 10.1109/ICIP46576.2022.9897170 |
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