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A review of the hand gesture recognition system: Current progress and future directions
This paper reviewed the sign language research in the vision-based hand gesture
recognition system from 2014 to 2020. Its objective is to identify the progress and what …
recognition system from 2014 to 2020. Its objective is to identify the progress and what …
Hand gesture recognition with focus on leap motion: An overview, real world challenges and future directions
In the recent years, a steady growth of Hand Gesture Recognition (HGR) based applications
has been observed. Thus, significant progress has been made in the field of hand detection …
has been observed. Thus, significant progress has been made in the field of hand detection …
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 …
American sign language recognition and training method with recurrent neural network
Though American sign language (ASL) has gained recognition from the American society,
few ASL applications have been developed with educational purposes. Those designed …
few ASL applications have been developed with educational purposes. Those designed …
Dynamic hand gesture recognition based on signals from specialized data glove and deep learning algorithms
Y Dong, J Liu, W Yan - IEEE Transactions on Instrumentation …, 2021 - ieeexplore.ieee.org
Gesture recognition as a natural, convenient and recognizable way has been received more
and more attention on human-machine interaction (HMI) recently. However, visual-based …
and more attention on human-machine interaction (HMI) recently. However, visual-based …
Advances in machine translation for sign language: approaches, limitations, and challenges
Sign languages are used by the deaf community around the globe to communicate with one
another. These are gesture-based languages where a deaf person performs gestures using …
another. These are gesture-based languages where a deaf person performs gestures using …
Quantitative survey of the state of the art in sign language recognition
O Koller - arxiv preprint arxiv:2008.09918, 2020 - arxiv.org
This work presents a meta study covering around 300 published sign language recognition
papers with over 400 experimental results. It includes most papers between the start of the …
papers with over 400 experimental results. It includes most papers between the start of the …
American Sign Language alphabet recognition using Convolutional Neural Networks with multiview augmentation and inference fusion
Abstract American Sign Language (ASL) alphabet recognition by computer vision is a
challenging task due to the complexity in ASL signs, high interclass similarities, large …
challenging task due to the complexity in ASL signs, high interclass similarities, large …
User-independent American sign language alphabet recognition based on depth image and PCANet features
Sign language is the most natural and effective way for communications among deaf and
normal people. American Sign Language (ASL) alphabet recognition (ie fingerspelling) …
normal people. American Sign Language (ASL) alphabet recognition (ie fingerspelling) …
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 …