Recent progress in sensing and computing techniques for human activity recognition and motion analysis
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 …
sensing and computing have created opportunities for the continuous monitoring of human …
Temporal decoupling graph convolutional network for skeleton-based gesture recognition
Skeleton-based gesture recognition methods have achieved high success using Graph
Convolutional Network (GCN), which commonly uses an adjacency matrix to model the …
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
Researchers have been developing Hand Gesture Recognition (HGR) systems to enhance
natural, efficient, and authentic human-computer interaction, especially benefiting those who …
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 …
For those engaged in agricultural jobs, efficiency at work and productivity are deeply related …
A transformer-based network for dynamic hand gesture recognition
Transformer-based neural networks represent a successful self-attention mechanism that
achieves state-of-the-art results in language understanding and sequence modeling …
achieves state-of-the-art results in language understanding and sequence modeling …
Dynamic hand gesture recognition using improved spatio-temporal graph convolutional network
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 …
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
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 …
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
Dynamic hand skeletons consisting of discrete spatial-temporal finger joint clouds effectively
convey the intentions of communicators. Previous graph convolutional networks (GCNs) …
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 …
applications, such as gesture-based control for physical or virtual/augmented reality devices …
Compact joints encoding for skeleton-based dynamic hand gesture recognition
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 …
hand gesture recognition has attracted widespread attention. In this paper, we propose a …