1. Ktisis Cyprus University of Technology

DeepSignNet: Video processing for Sign Language Recognition using Deep Bayesian Recurrent Neural Networks

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Primary Data

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Project title
DeepSignNet: Video processing for Sign Language Recognition using Deep Bayesian Recurrent Neural Networks
Project Coordinator
Start date
01-01-2019
Expected Completion
10-08-2021
 
Project website

Description

Abstract
Sign Languages (SLs), being the mother tongues of the deaf, are an important part of the European and the world cultural diversity. In Europe, there are 30 official SLs and more than 750000 SL users, while only 12000 interpreters. This shortage undermines the right to equal education and health services, and even endangers the lives of deaf people.

DeepSignNet makes significant contributions to automated visual SL recognition (SLR). We address: (a) Inference of the appropriate machine learning model size to limit the amount of parameters to learn, and (b) integration of prior linguistic constraints and non-manual cues. 

To this end, we will collaborate with a world-leading group, the Computational Bioimaging and Modeling (CBIM) Center of Rutgers University – New Jersey. It is one of the leaders in computer vision and has extensive know–how in SL recognition.
 

Publications
(All)


Results 1-1 of 1 (Search time: 0.001 seconds).

Issue DateTitleAuthor(s)
12020Variational Bayesian Sequence-to-Sequence Networks for Memory-Efficient Sign Language TranslationPartaourides, Harris ; Voskou, Andreas ; Kosmopoulos, Dimitrios I. ; Chatzis, Sotirios P. ; N. Metaxas, Dimitris