Inflated 3D ConvNet for detection of sign language

D. Chandana; M. Tushara; A. Ramya Sri; Sridevi Sakhamuri; Laith Abualigah

doi:10.1117/12.3027104

1 April 2024 Inflated 3D ConvNet for detection of sign language

D. Chandana, M. Tushara, A. Ramya Sri, Sridevi Sakhamuri, Laith Abualigah

Proceedings Volume 13077, Fourth International Conference on Signal Processing and Machine Learning (CONF-SPML 2024); 1307702 (2024) https://doi.org/10.1117/12.3027104
Event: 4th International Conference on Signal Processing and Machine Learning (CONF-SPML 2024), 2024, Chicago, IL, United States

Abstract

Every human has their own kind of disabilities, we all try to live and overcome them in our life. We educate ourselves to overcome them, we invent technology to achieve our goals. Sign Language is a communication path for deaf-mute people through hand gestures and actions. Sign Language helps people who can’t speak sign language to interact with the people who can speak sign language, this deep learning paper aims to help build a communication bridge for this reason. We used Amazon Rekognition service which uses Deep CNN algorithm for the detection of static images of the signs. As most of the signs are for words they are in the form of videos. We used the I3D algorithm for the classification of videos of the signs of words. The PyTorch framework provides support for CuDNN (NVIDIA CUDA Deep Neural Network) which provides fast GPU implementations for the deep neural networks. The Experimental results has shown that the models used has displayed good results in detecting the words.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

D. Chandana, M. Tushara, A. Ramya Sri, Sridevi Sakhamuri, and Laith Abualigah "Inflated 3D ConvNet for detection of sign language", Proc. SPIE 13077, Fourth International Conference on Signal Processing and Machine Learning (CONF-SPML 2024), 1307702 (1 April 2024); https://doi.org/10.1117/12.3027104

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
5 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Video

Video acceleration

Education and training

3D modeling

Data modeling

Telecommunications

Visual process modeling

Show All Keywords

Keywords/Phrases

Search In:

Publication Years