[HTML][HTML] Machine learning methods for sign language recognition: A critical review and analysis
Sign language is an essential tool to bridge the communication gap between normal and
hearing-impaired people. However, the diversity of over 7000 present-day sign languages …
hearing-impaired people. However, the diversity of over 7000 present-day sign languages …
[HTML][HTML] A survey on Sign Language machine translation
A Núñez-Marcos, O Perez-de-Viñaspre… - Expert Systems with …, 2023 - Elsevier
Abstract Sign Languages (SLs) are employed by deaf and hard-of-hearing (DHH) people to
communicate on a daily basis. However, the communication with hearing people still faces …
communicate on a daily basis. However, the communication with hearing people still faces …
Word-level deep sign language recognition from video: A new large-scale dataset and methods comparison
Vision-based sign language recognition aims at helping the hearing-impaired people to
communicate with others. However, most existing sign language datasets are limited to a …
communicate with others. However, most existing sign language datasets are limited to a …
BSL-1K: Scaling up co-articulated sign language recognition using mouthing cues
Recent progress in fine-grained gesture and action classification, and machine translation,
point to the possibility of automated sign language recognition becoming a reality. A key …
point to the possibility of automated sign language recognition becoming a reality. A key …
The jester dataset: A large-scale video dataset of human gestures
Gesture recognition and its application in human-computer interfaces have been growing
increasingly popular in recent years. Although many gestures can be recognized from a …
increasingly popular in recent years. Although many gestures can be recognized from a …
How2sign: a large-scale multimodal dataset for continuous american sign language
One of the factors that have hindered progress in the areas of sign language recognition,
translation, and production is the absence of large annotated datasets. Towards this end, we …
translation, and production is the absence of large annotated datasets. Towards this end, we …
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 …
Hand gesture recognition for sign language using 3DCNN
Recently, automatic hand gesture recognition has gained increasing importance for two
principal reasons: the growth of the deaf and hearing-impaired population, and the …
principal reasons: the growth of the deaf and hearing-impaired population, and the …
Exploiting recurrent neural networks and leap motion controller for the recognition of sign language and semaphoric hand gestures
Hand gesture recognition is still a topic of great interest for the computer vision community.
In particular, sign language and semaphoric hand gestures are two foremost areas of …
In particular, sign language and semaphoric hand gestures are two foremost areas of …
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 …