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Development of Smartphone Application for Markerless Three-Dimensional Motion Capture Based on Deep Learning Model
To quantitatively assess pathological gait, we developed a novel smartphone application for full-body human motion tracking in real time from markerless video-based images using a smartphone monocular camera and deep learning. As training data for deep learning, the original three-dimensional (3D) d...
Autores principales: | Aoyagi, Yukihiko, Yamada, Shigeki, Ueda, Shigeo, Iseki, Chifumi, Kondo, Toshiyuki, Mori, Keisuke, Kobayashi, Yoshiyuki, Fukami, Tadanori, Hoshimaru, Minoru, Ishikawa, Masatsune, Ohta, Yasuyuki |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9322512/ https://www.ncbi.nlm.nih.gov/pubmed/35890959 http://dx.doi.org/10.3390/s22145282 |
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