Preliminary Validation of a Low-Cost Motion Analysis System Based on RGB Cameras to Support the Evaluation of Postural Risk Assessment
This paper introduces a low-cost and low computational marker-less motion capture system based on the acquisition of frame images through standard RGB cameras. It exploits the open-source deep learning model CMU, from the tf-pose-estimation project. Its numerical accuracy and its usefulness for ergo...
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Autores principales: | Thomas Agostinelli, Andrea Generosi, Silvia Ceccacci, Riccardo Karim Khamaisi, Margherita Peruzzini, Maura Mengoni |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
MDPI AG
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/f7b83fcdd577450c8939eb193ae355e4 |
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