VI-Net—View-Invariant Quality of Human Movement Assessment

We propose a view-invariant method towards the assessment of the quality of human movements which does not rely on skeleton data. Our end-to-end convolutional neural network consists of two stages, where at first a view-invariant trajectory descriptor for each body joint is generated from RGB images...

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Detalles Bibliográficos
Autores principales: Sardari, Faegheh, Paiement, Adeline, Hannuna, Sion, Mirmehdi, Majid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7570706/
https://www.ncbi.nlm.nih.gov/pubmed/32942561
http://dx.doi.org/10.3390/s20185258

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7570706/
https://www.ncbi.nlm.nih.gov/pubmed/32942561
http://dx.doi.org/10.3390/s20185258

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