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RETRACTED ARTICLE: Machine learning based sign language recognition: a review and its research frontier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 …
A survey on human motion analysis from depth data
Human pose estimation has been actively studied for decades. While traditional approaches
rely on 2d data like images or videos, the development of Time-of-Flight cameras and other …
rely on 2d data like images or videos, the development of Time-of-Flight cameras and other …
Real-time sign language letter and word recognition from depth data
D Uebersax, J Gall, M Van den Bergh… - … on computer vision …, 2011 - ieeexplore.ieee.org
In this work, we present a system for recognizing letters and finger-spelled words of the
American sign language (ASL) in real-time. To this end, the system segments the hand and …
American sign language (ASL) in real-time. To this end, the system segments the hand and …
Dynamic–static unsupervised sequentiality, statistical subunits and lexicon for sign language recognition
We introduce a new computational phonetic modeling framework for sign language (SL)
recognition. This is based on dynamic–static statistical subunits and provides sequentiality …
recognition. This is based on dynamic–static statistical subunits and provides sequentiality …
Lexicon-free fingerspelling recognition from video: Data, models, and signer adaptation
We study the problem of recognizing video sequences of fingerspelled letters in American
Sign Language (ASL). Fingerspelling comprises a significant but relatively understudied part …
Sign Language (ASL). Fingerspelling comprises a significant but relatively understudied part …
Subunit sign modeling framework for continuous sign language recognition
R Elakkiya, K Selvamani - Computers & Electrical Engineering, 2019 - Elsevier
A new framework named three subunit sign modeling is introduced for automatic sign
language recognition. This works on continuous video sequences consisting of isolated …
language recognition. This works on continuous video sequences consisting of isolated …
Human activity recognition using segmented body part and body joint features with hidden Markov models
MZ Uddin - Multimedia Tools and Applications, 2017 - Springer
In recent years, human activity recognition from video has been getting considerable
research attentions by computer vision researchers due to its prominent applications in …
research attentions by computer vision researchers due to its prominent applications in …
Modelling Sign Language with Encoder-Only Transformers and Human Pose Estimation Keypoint Data
We present a study on modelling American Sign Language (ASL) with encoder-only
transformers and human pose estimation keypoint data. Using an enhanced version of the …
transformers and human pose estimation keypoint data. Using an enhanced version of the …
Fingerspelling recognition with semi-Markov conditional random fields
T Kim, G Shakhnarovich… - Proceedings of the IEEE …, 2013 - openaccess.thecvf.com
Recognition of gesture sequences is in general a very difficult problem, but in certain
domains the difficulty may be mitigated by exploiting the domain's" grammar". One such …
domains the difficulty may be mitigated by exploiting the domain's" grammar". One such …