TY  - JOUR
T1  - Advances, Challenges and Opportunities in Continuous Sign
Language Recognition
AU - Ibrahim, Nada B. AU - Zayed, Hala H. AU - Selim, Mazen M. 
JO  - Journal of Engineering and Applied Sciences
VL  - 15
IS  - 5
SP  - 1205
EP  - 1227
PY  - 2020
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2020.1205.1227
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2020.1205.1227
KW  - Continuous sign language recognition
KW  -gesture recognition
KW  -movement epenthesis
KW  -dynamic
gesture
KW  -presented
KW  -dependency
AB  - Sign Language (SL) is the hands spoken language assisting the deaf to understand each other.
Understanding SL by vocal people not only paves the way to contribute deaf and dumb in the workforce but
also provides a fertile environment for analyzing the human motion and gesturing. Consequently, translating
SL sentence into written or spoken language, known as Continuous Sign Language Recognition (CSLR) will
help in integrating the deaf and dumb in the society. Most of the surveys in the field of Sign Language
Recognition (SLR) spotlight on isolated SLR that mainly deals with words, numbers and letters each in
separate. Moreover, these systems are designed to operate in artificial settings for the background, signer
dependency and limited vocabulary. Even though for real-life CSLR is the objective, till now there is not a
complete survey on CSLR that provides researchers with a comprehensive study on the advances, challenges
and opportunities in this field. The presented piece of work analyzes the articles published earlier and illustrates
the core stumbling blocks related to CSLR including: the dynamic hand detection and tracking, facial
expression recognition, movement epenthesis detection and recognition methods as well as a comparative study
on the available benchmark databases. An inventory of the applications which stand to benefit from CSLR are
also brightened up. The conclusions and recommendations of this research can be a milestone for developing
evolved and efficient CSLR systems.
ER  -