Recent progress in sensing and computing techniques for human activity recognition and motion analysis

Z Meng, M Zhang, C Guo, Q Fan, H Zhang, N Gao… - Electronics, 2020 - mdpi.com
The recent scientific and technical advances in Internet of Things (IoT) based pervasive
sensing and computing have created opportunities for the continuous monitoring of human …

Temporal decoupling graph convolutional network for skeleton-based gesture recognition

J Liu, X Wang, C Wang, Y Gao… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Skeleton-based gesture recognition methods have achieved high success using Graph
Convolutional Network (GCN), which commonly uses an adjacency matrix to model the …

A Methodological and Structural Review of Hand Gesture Recognition Across Diverse Data Modalities

J Shin, ASM Miah, MH Kabir, MA Rahim… - IEEE Access, 2024 - ieeexplore.ieee.org
Researchers have been developing Hand Gesture Recognition (HGR) systems to enhance
natural, efficient, and authentic human-computer interaction, especially benefiting those who …

Applying deep neural networks for the automatic recognition of sign language words: A communication aid to deaf agriculturists

A Venugopalan, R Reghunadhan - Expert Systems with Applications, 2021 - Elsevier
One of the major challenges that deaf people face in modern societal life is communication.
For those engaged in agricultural jobs, efficiency at work and productivity are deeply related …

A transformer-based network for dynamic hand gesture recognition

A D'Eusanio, A Simoni, S Pini, G Borghi… - … Conference on 3D …, 2020 - ieeexplore.ieee.org
Transformer-based neural networks represent a successful self-attention mechanism that
achieves state-of-the-art results in language understanding and sequence modeling …

Dynamic hand gesture recognition using improved spatio-temporal graph convolutional network

JH Song, K Kong, SJ Kang - … on Circuits and Systems for Video …, 2022 - ieeexplore.ieee.org
Hand gesture recognition is essential to human-computer interaction as the most natural
way of communicating. Furthermore, with the development of 3D hand pose estimation …

Sta-gcn: two-stream graph convolutional network with spatial–temporal attention for hand gesture recognition

W Zhang, Z Lin, J Cheng, C Ma, X Deng, H Wang - The Visual Computer, 2020 - Springer
Skeleton-based hand gesture recognition is an active research topic in computer graphics
and computer vision and has a wide range of applications in VR/AR and robotics. Although …

Normalized edge convolutional networks for skeleton-based hand gesture recognition

F Guo, Z He, S Zhang, X Zhao, J Fang, J Tan - Pattern Recognition, 2021 - Elsevier
Dynamic hand skeletons consisting of discrete spatial-temporal finger joint clouds effectively
convey the intentions of communicators. Previous graph convolutional networks (GCNs) …

Multiview video-based 3-d hand pose estimation

L Khaleghi, A Sepas-Moghaddam… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Hand pose estimation (HPE) can be used for a variety of human–computer interaction
applications, such as gesture-based control for physical or virtual/augmented reality devices …

Compact joints encoding for skeleton-based dynamic hand gesture recognition

Y Li, D Ma, Y Yu, G Wei, Y Zhou - Computers & Graphics, 2021 - Elsevier
With the development of 3D hand pose estimation technologies, skeleton-based dynamic
hand gesture recognition has attracted widespread attention. In this paper, we propose a …