Skeleton-based human recognition is a key technology for visual feedback, which can help
the Internet of Things (IoT) interact with humans in a non-contact manner outdoors. Graph …

In visual surveillance systems, it is necessary to recognize the behavior of people handling
objects such as a phone, a cup, or a plastic bag. In this paper, to address this problem, we …

With the prevalence of accessible depth sensors, dynamic human body skeletons have
attracted much attention as a robust modality for action recognition. Previous methods model …

Human skeleton, as a compact representation of human action, has received increasing
attention in recent years. Many skeleton-based action recognition methods adopt GCNs to …

Graph Convolutional Networks (GCNs) have been widely used in skeleton-based human
action recognition and have achieved promising results. However, current GCN-based …

Graph convolutional networks (GCN), which can model the human body skeletons as spatial
and temporal graphs, have shown remarkable potential in skeleton-based action …

Action recognition is a key algorithmic part of emerging on-the-edge smart video
surveillance and security systems. Skeleton-based action recognition is an attractive …

Human action recognition is a computer vision challenge that involves identifying and
classifying human movements and activities. The behavior of humans comprises …

Recently, skeleton-based gesture and action recognition have emerged thanks to the
progress in human pose estimation. Gesture representation using skeletal data is robust …

The emergence of low-cost depth sensors opens up new potentials for skeleton-based
human action recognition. The recent methods for this task have made significant progress …