Sensing Systems for Sign Language Recognition Call for Papers

Research topic: 
Sensing Systems for Sign Language Recognition
https://www.mdpi.com/journal/sensors/special_issues/SSSLR

Deadline for manuscript submissions: 15 January 2022.

The automatic understanding of Sign Languages is a must to ease
integration for millions of deaf people around the world. The last two
decades have witnessed increasing research efforts to solve this
problem. Many of these proposals were based on somehow intrusive
sensors to capture the 3D rapid movements of arms, hands and fingers
(data gloves, colored gloves, mocap, ultrasound, etc.), but, for the
past ten years, RGB and depth sensors have been becoming the
mainstream solution to simultaneously capturing the communicative
channels related to hand movements, face expressivity and whole upper
body movements. The latest advancements in human activity recognition
from visual cues, rooted in highly efficient deep learning models,
have also pushed research in Sign Language Recognition as a closely
related application. We are in an excitement moment when it comes to
pushing socially required applications to reduce communicative
barriers.

This Special Issue seeks to bring together innovative research and
development solutions in the area of Sign Language Recognition, using
any kind of sensing devices. Comparative studies on different sensing
devices are also very welcome. Authors are invited to submit original
articles across the full development stack (hardware, system and
software), including architectures, techniques and tools for sensing
and modeling the complex movement details of signing and the proper
decoding of sign sequences. This may include, but is not limited to,
sensing modalities, innovative solutions for data collection,
strategies for data augmentation, sensor fusion, spatio-temporal
representation, computational reduction, model optimization for mobile
devices, real-world applications, etc.

This topic is very well-fitted to the scope of the journal because
using proper acquisition sensors allows trustful and discriminative
information which is critical for sign language representation and,
then, recognition. This journal also accepts the algorithmic
processing of sensed signals, something that is rapidly evolving for
SLR.


Guest Editors

Dr. Josť Luis Alba Castro
Dr. Sergio Escalera
Prof. Jun Wan