A review of hand gesture and sign language recognition techniques
Hand gesture recognition serves as a key for overcoming many difficulties and providing
convenience for human life. The ability of machines to understand human activities and their …
convenience for human life. The ability of machines to understand human activities and their …
Deep learning for sign language recognition: Current techniques, benchmarks, and open issues
M Al-Qurishi, T Khalid, R Souissi - IEEE Access, 2021 - ieeexplore.ieee.org
People with hearing impairments are found worldwide; therefore, the development of
effective local level sign language recognition (SLR) tools is essential. We conducted a …
effective local level sign language recognition (SLR) tools is essential. We conducted a …
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 …
Survey on 3D hand gesture recognition
Three-dimensional hand gesture recognition has attracted increasing research interests in
computer vision, pattern recognition, and human-computer interaction. The emerging depth …
computer vision, pattern recognition, and human-computer interaction. The emerging depth …
Recent methods and databases in vision-based hand gesture recognition: A review
PK Pisharady, M Saerbeck - Computer Vision and Image Understanding, 2015 - Elsevier
Successful efforts in hand gesture recognition research within the last two decades paved
the path for natural human–computer interaction systems. Unresolved challenges such as …
the path for natural human–computer interaction systems. Unresolved challenges such as …
[HTML][HTML] A new spiking convolutional recurrent neural network (SCRNN) with applications to event-based hand gesture recognition
The combination of neuromorphic visual sensors and spiking neural network offers a high
efficient bio-inspired solution to real-world applications. However, processing event-based …
efficient bio-inspired solution to real-world applications. However, processing event-based …
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 recognition with the kinect
Z Zafrulla, H Brashear, T Starner, H Hamilton… - Proceedings of the 13th …, 2011 - dl.acm.org
We investigate the potential of the Kinect depth-mapping camera for sign language
recognition and verification for educational games for deaf children. We compare a …
recognition and verification for educational games for deaf children. We compare a …
Gesture-based human-robot interaction for human assistance in manufacturing
The paradigm for robot usage has changed in the last few years, from a scenario in which
robots work isolated to a scenario where robots collaborate with human beings, exploiting …
robots work isolated to a scenario where robots collaborate with human beings, exploiting …
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 …