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A Two-Stage Image Frame Extraction Model -ISLKE for Live Gesture Analysis on Indian Sign Language

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Title A Two-Stage Image Frame Extraction Model -ISLKE for Live Gesture Analysis on Indian Sign Language
 
Creator J, Hyma
P, Rajamani
 
Subject Classification
Clustering
Featured learning
Image processing
Region of interest
Video summarization
 
Description 426-431
The new industry revolution focused on Smart and interconnected technologies along with the Robotics and Artificial
Intelligence, Machine Learning, Data analytics etc. on the real time data to produce the value-added products. The ways the
goods are being produced are aligned with the people’s life style which is witnessed in terms of wearable smart devices,
digital assistants, self-driving cars etc. Over the last few years, an evident capturing of the true potential of Industry 4.0 in
health service domain is also observed. In the same context, Sign Language Recognition- a breakthrough in the live video
processing domain, helps the deaf and mute communities grab the attention of many researchers. From the research insights,
it is clearly evident that precise extraction and interpretation of the gesture data along with an addressal of the prevailing
limitations is a crucial task. This has driven the work to come out with a unique keyframe extraction model focusing on the
preciseness of the interpretation. The proposed model ISLKE deals with a clustering-based two stage keyframe extraction
process. It has experimented on daily usage vocabulary of Indian Sign Language (ISL) and attained an average accuracy of
96% in comparison to the ground-truth facts. It is also observed that with the two-stage approach, filtering of uninformative
frames has reduced complexity and computational efforts. These key leads, help in the further development of commercial
communication applications in order to reach the speech and hearing disorder communities.
 
Date 2023-04-03T10:00:43Z
2023-04-03T10:00:43Z
2023-04
 
Type Article
 
Identifier 0022-4456 (Print); 0975-1084 (Online)
http://nopr.niscpr.res.in/handle/123456789/61656
https://doi.org/10.56042/jsir.v82i04.72389
 
Language en
 
Publisher NIScPR-CSIR,India
 
Source JSIR Vol.82(04) [April 2023]