Cargando…
Fast Temporal Graph Convolutional Model for Skeleton-Based Action Recognition
Human action recognition has a wide range of applications, including Ambient Intelligence systems and user assistance. Starting from the recognized actions performed by the user, a better human–computer interaction can be achieved, and improved assistance can be provided by social robots in real-tim...
Autores principales: | Nan, Mihai, Florea, Adina Magda |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9570854/ https://www.ncbi.nlm.nih.gov/pubmed/36236213 http://dx.doi.org/10.3390/s22197117 |
Ejemplares similares
-
Comparison between Recurrent Networks and Temporal Convolutional Networks Approaches for Skeleton-Based Action Recognition
por: Nan, Mihai, et al.
Publicado: (2021) -
Enhanced Spatial and Extended Temporal Graph Convolutional Network for Skeleton-Based Action Recognition
por: Li, Fanjia, et al.
Publicado: (2020) -
Shallow Graph Convolutional Network for Skeleton-Based Action Recognition
por: Yang, Wenjie, et al.
Publicado: (2021) -
Spatio-Temporal Features in Action Recognition Using 3D Skeletal Joints
por: Trăscău, Mihai, et al.
Publicado: (2019) -
Adaptive Attention Memory Graph Convolutional Networks for Skeleton-Based Action Recognition
por: Liu, Di, et al.
Publicado: (2021)