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 …
RETRACTED ARTICLE: Machine learning based sign language recognition: a review and its research frontier
R Elakkiya - Journal of Ambient Intelligence and Humanized …, 2021 - Springer
In the recent past, research in the field of automatic sign language recognition using
machine learning methods have demonstrated remarkable success and made momentous …
machine learning methods have demonstrated remarkable success and made momentous …
Ms-asl: A large-scale data set and benchmark for understanding american sign language
Sign language recognition is a challenging and often underestimated problem comprising
multi-modal articulators (handshape, orientation, movement, upper body and face) that …
multi-modal articulators (handshape, orientation, movement, upper body and face) that …
Continuous sign language recognition: Towards large vocabulary statistical recognition systems handling multiple signers
This work presents a statistical recognition approach performing large vocabulary
continuous sign language recognition across different signers. Automatic sign language …
continuous sign language recognition across different signers. Automatic sign language …
Fully convolutional networks for continuous sign language recognition
Continuous sign language recognition (SLR) is a challenging task that requires learning on
both spatial and temporal dimensions of signing frame sequences. Most recent work …
both spatial and temporal dimensions of signing frame sequences. Most recent work …
Korean sign language recognition using transformer-based deep neural network
Sign language recognition (SLR) is one of the crucial applications of the hand gesture
recognition and computer vision research domain. There are many researchers who have …
recognition and computer vision research domain. There are many researchers who have …
[PDF][PDF] Sign language recognition using sub-units
This paper discusses sign language recognition using linguistic sub-units. It presents three
types of sub-units for consideration; those learnt from appearance data as well as those …
types of sub-units for consideration; those learnt from appearance data as well as those …
Understanding vision-based continuous sign language recognition
N Aloysius, M Geetha - Multimedia Tools and Applications, 2020 - Springer
Real-time sign language translation systems, that convert continuous sign sequences to
text/speech, will facilitate communication between the deaf-mute community and the normal …
text/speech, will facilitate communication between the deaf-mute community and the normal …
The fate landscape of sign language ai datasets: An interdisciplinary perspective
Sign language datasets are essential to developing many sign language technologies. In
particular, datasets are required for training artificial intelligence (AI) and machine learning …
particular, datasets are required for training artificial intelligence (AI) and machine learning …
Isolated sign language recognition with grassmann covariance matrices
In this article, to utilize long-term dynamics over an isolated sign sequence, we propose a
covariance matrix--based representation to naturally fuse information from multimodal …
covariance matrix--based representation to naturally fuse information from multimodal …