Recently, human activity recognition using skeleton data is increasing due to its ease of
acquisition and finer shape details. Still, it suffers from a wide range of intra-class variation …

The primary goal of hand gesture recognition with wearables is to facilitate the realization of
gestural user interfaces in mobile and ubiquitous environments. A key challenge in …

Landmark-based human action recognition in videos is a challenging task in computer
vision. One key step is to design a generic approach that generates discriminative features …

We present a module that extends the temporal graph of a graph convolutional network
(GCN) for action recognition with a sequence of skeletons. Existing methods attempt to …

Labanotation is a widely-used notation system for dance recording. Numerous methods for
automatic Labanotation generation from motion capture data have been proposed to save …

This paper proposes a novel 3D action recognition technique that uses time-series
information extracted from depth image sequences for use in systems of human daily activity …

The 3D skeleton sequences of action can be recognized based on series of meaningful
movements including changes in the direction and geometry features of the body pose. In …

The details presented in this article revolve around a sophisticated monitoring framework
equipped with knowledge representation and computer vision capabilities, that aims to …

Previous research on 3D skeleton-based human action recognition has frequently relied on
a sequence-wise viewpoint normalization process, which adjusts the view directions of all …

Human skeleton action recognition has garnered significant attention from researchers due
to its promising performance in real-world applications. Recently, graph neural networks …