Make skeleton-based action recognition model smaller, faster and better
Although skeleton-based action recognition has achieved great success in recent years,
most of the existing methods may suffer from a large model size and slow execution speed …
most of the existing methods may suffer from a large model size and slow execution speed …
Dynamic hand gesture recognition using multi-branch attention based graph and general deep learning model
The dynamic hand skeleton data have become increasingly attractive to widely studied for
the recognition of hand gestures that contain 3D coordinates of hand joints. Many …
the recognition of hand gestures that contain 3D coordinates of hand joints. Many …
Literature review of vision‐based dynamic gesture recognition using deep learning techniques
Gesture recognition is the foremost need in building intelligent human‐computer interaction
systems to solve many day‐to‐day problems and simplify human life in this digital world. The …
systems to solve many day‐to‐day problems and simplify human life in this digital world. The …
Efficient skeleton-based action recognition via multi-stream depthwise separable convolutional neural network
Skeleton-based human action recognition has attracted considerable attention and
achieved great success in several engineering fields, which is also one of the most active …
achieved great success in several engineering fields, which is also one of the most active …
A novel hybrid bidirectional unidirectional LSTM network for dynamic hand gesture recognition with leap motion
Due to the recent development of machine learning and sensor innovations, hand gesture
recognition systems become promising for the digital entertainment field. In this paper, we …
recognition systems become promising for the digital entertainment field. In this paper, we …
[HTML][HTML] American sign language words recognition of skeletal videos using processed video driven multi-stacked deep LSTM
SB Abdullahi, K Chamnongthai - Sensors, 2022 - mdpi.com
Complex hand gesture interactions among dynamic sign words may lead to
misclassification, which affects the recognition accuracy of the ubiquitous sign language …
misclassification, which affects the recognition accuracy of the ubiquitous sign language …
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) …
SBI-DHGR: Skeleton-based intelligent dynamic hand gestures recognition
S Narayan, AP Mazumdar, SK Vipparthi - Expert Systems with Applications, 2023 - Elsevier
Hand gesture recognition (HGR) plays a significant role in interpreting the meaning of sign
language, human–computer interaction, and robot control. This paper proposes a real-time …
language, human–computer interaction, and robot control. This paper proposes a real-time …
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 …
Oo-dmvmt: A deep multi-view multi-task classification framework for real-time 3d hand gesture classification and segmentation
Continuous mid-air hand gesture recognition based on captured hand pose streams is
fundamental for human-computer interaction, particularly in AR/VR. However, many of the …
fundamental for human-computer interaction, particularly in AR/VR. However, many of the …