Visual communication with dual video transmissions for remote sign language interpretation services

2003 ◽  
Author(s):  
N. Kato ◽  
I. Naito ◽  
H. Murakami ◽  
H. Minagawa ◽  
Y. Ishihara
Keyword(s):  
Sign Language ◽  
Visual Communication ◽  
Language Interpretation

Design and Development of a Humanoid Robot for Sign Language Interpretation

2021 ◽  
Vol 2 (3) ◽  
Author(s):  
Ragib Amin Nihal ◽  
Nawara Mahmood Broti ◽  
Shamim Ahmed Deowan ◽  
Sejuti Rahman
Keyword(s):  
Sign Language ◽  
Humanoid Robot ◽  
Design And Development ◽  
Language Interpretation

A Modern Approach for Sign Language Interpretation Using Convolutional Neural Network

2019 ◽  
pp. 431-444 ◽  
Author(s):  
Pias Paul ◽  
Moh. Anwar-Ul-Azim Bhuiya ◽  
Md. Ayat Ullah ◽  
Molla Nazmus Saqib ◽  
Nabeel Mohammed ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Sign Language ◽  
Modern Approach ◽  
Language Interpretation

A human skin-inspired self-powered flex sensor with thermally embossed microstructured triboelectric layers for sign language interpretation

Nano Energy ◽  
2020 ◽  
Vol 76 ◽  
pp. 105071 ◽  
Author(s):  
Pukar Maharjan ◽  
Trilochan Bhatta ◽  
Md Salauddin ◽  
M.S. Rasel ◽  
M.T. Rahman ◽  
...  
Keyword(s):  
Sign Language ◽  
Human Skin ◽  
Language Interpretation ◽  
Self Powered

scholarly journals Sign Language Video Processing for Text Detection in Hindi Language

2016 ◽  
Vol 4 (3) ◽  
pp. 21
Author(s):  
Rashmi B Hiremath ◽  
Ramesh M Kagalkar
Keyword(s):  
Image Processing ◽  
Sign Language ◽  
Video Processing ◽  
Body Language ◽  
Noise Elimination ◽  
Processing Methods ◽  
Inference System ◽  
Language Interpretation ◽  
Video Recognition ◽  
Result Analysis

Sign language is a way of expressing yourself with your body language, where every bit of ones expressions, goals, or sentiments are conveyed by physical practices, for example, outward appearances, body stance, motions, eye movements, touch and the utilization of space. Non-verbal communication exists in both creatures and people, yet this article concentrates on elucidations of human non-verbal or sign language interpretation into Hindi textual expression. The proposed method of implementation utilizes the image processing methods and synthetic intelligence strategies to get the goal of sign video recognition. To carry out the proposed task implementation it uses image processing methods such as frame analysing based tracking, edge detection, wavelet transform, erosion, dilation, blur elimination, noise elimination, on training videos. It also uses elliptical Fourier descriptors called SIFT for shape feature extraction and most important part analysis for feature set optimization and reduction. For result analysis, this paper uses different category videos such as sign of weeks, months, relations etc. Database of extracted outcomes are compared with the video fed to the system as a input of the signer by a trained unclear inference system.

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