Skeleton-Based ST-GCN for Human Action Recognition With Extended Skeleton Graph and Partitioning Strategy

Skeleton-Based ST-GCN for Human Action Recognition With Extended Skeleton Graph and Partitioning Strategy

Skeleton-based Graph Convolutional Networks (GCN) for human action and interaction recognition have received considerable attention of researchers due to its compact and view-invariant nature of skeleton data. However, the static skeleton graph topology in conventional GCNs does not reflect the impl...

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Bibliographic Details
Main Authors: Quanyu Wang, Kaixiang Zhang, Manjotho Ali Asghar
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Action recognition
deep learning
graph convolutional network
human skeleton
partition strategy
Online Access:https://ieeexplore.ieee.org/document/9749063/

Internet

https://ieeexplore.ieee.org/document/9749063/

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