Methods, databases and recent advancement of vision-based hand gesture recognition for hci systems: A review
Hand gesture recognition is viewed as a significant field of exploration in computer vision
with assorted applications in the human–computer communication (HCI) community. The …
with assorted applications in the human–computer communication (HCI) community. The …
A multi-stream convolutional neural network for sEMG-based gesture recognition in muscle-computer interface
In muscle-computer interface (MCI), deep learning is a promising technology to build-up
classifiers for recognizing gestures from surface electromyography (sEMG) signals …
classifiers for recognizing gestures from surface electromyography (sEMG) signals …
Divide and conquer-based 1D CNN human activity recognition using test data sharpening
H Cho, SM Yoon - Sensors, 2018 - mdpi.com
Human Activity Recognition (HAR) aims to identify the actions performed by humans using
signals collected from various sensors embedded in mobile devices. In recent years, deep …
signals collected from various sensors embedded in mobile devices. In recent years, deep …
MVFFNet: Multi-view feature fusion network for imbalanced ship classification
The accurate classification of moving ships is of fundamental importance to maritime
authorities for ensuring the safety and security of shipping operations. With the wide use of …
authorities for ensuring the safety and security of shipping operations. With the wide use of …
Structured dynamic time warping for continuous hand trajectory gesture recognition
Continuous hand gesture recognition is an important area of HCI and challenged by various
writing habits and unconstrained hand movement. In this paper, we propose a Structured …
writing habits and unconstrained hand movement. In this paper, we propose a Structured …
State of the art and perspectives on traditional and emerging biometrics: A survey
I Traore, M Alshahrani, MS Obaidat - Security and Privacy, 2018 - Wiley Online Library
The last three decades have seen a shift and impressive progress in the biometric
technologies landscape. Several major real‐world applications of biometrics have been …
technologies landscape. Several major real‐world applications of biometrics have been …
Hand gesture recognition using leap motion via deterministic learning
W Zeng, C Wang, Q Wang - Multimedia tools and applications, 2018 - Springer
With the development of multimedia technology, traditional interactive tools, such as mouse
and keyboard, cannot satisfy users' requirements. Touchless interaction has received …
and keyboard, cannot satisfy users' requirements. Touchless interaction has received …
Kinect-based hand gesture recognition using trajectory information, hand motion dynamics and neural networks
Hand gestures are spatio-temporal patterns which can be characterized by collections of
spatio-temporal features. Recognition of hand gestures is to find the re-occurrences of such …
spatio-temporal features. Recognition of hand gestures is to find the re-occurrences of such …
Two-stream fusion model for dynamic hand gesture recognition using 3d-cnn and 2d-cnn optical flow guided motion template
The use of hand gestures can be a useful tool for many applications in the human-computer
interaction community. In a broad range of areas hand gesture techniques can be applied …
interaction community. In a broad range of areas hand gesture techniques can be applied …
SEMG-based gesture recognition with embedded virtual hand poses and adversarial learning
To improve the accuracy of surface electromyography (sEMG)-based gesture recognition,
we present a novel hybrid approach that combines real sEMG signals with corresponding …
we present a novel hybrid approach that combines real sEMG signals with corresponding …