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Computer Vision based Hand Gesture Recognition: A Survey

Shaminder Singh1 , Anuj Kumar Gupta2 , Tejwant Singh3

Section:Survey Paper, Product Type: Journal Paper
Volume-7 , Issue-5 , Page no. 507-515, May-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i5.507515

Online published on May 31, 2019

Copyright © Shaminder Singh, Anuj Kumar Gupta, Tejwant Singh . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Shaminder Singh, Anuj Kumar Gupta, Tejwant Singh, “Computer Vision based Hand Gesture Recognition: A Survey,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.5, pp.507-515, 2019.

MLA Style Citation: Shaminder Singh, Anuj Kumar Gupta, Tejwant Singh "Computer Vision based Hand Gesture Recognition: A Survey." International Journal of Computer Sciences and Engineering 7.5 (2019): 507-515.

APA Style Citation: Shaminder Singh, Anuj Kumar Gupta, Tejwant Singh, (2019). Computer Vision based Hand Gesture Recognition: A Survey. International Journal of Computer Sciences and Engineering, 7(5), 507-515.

BibTex Style Citation:
@article{Singh_2019,
author = {Shaminder Singh, Anuj Kumar Gupta, Tejwant Singh},
title = {Computer Vision based Hand Gesture Recognition: A Survey},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2019},
volume = {7},
Issue = {5},
month = {5},
year = {2019},
issn = {2347-2693},
pages = {507-515},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4272},
doi = {https://doi.org/10.26438/ijcse/v7i5.507515}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i5.507515}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4272
TI - Computer Vision based Hand Gesture Recognition: A Survey
T2 - International Journal of Computer Sciences and Engineering
AU - Shaminder Singh, Anuj Kumar Gupta, Tejwant Singh
PY - 2019
DA - 2019/05/31
PB - IJCSE, Indore, INDIA
SP - 507-515
IS - 5
VL - 7
SN - 2347-2693
ER -

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Abstract

Gestures are the most common way of interaction for physically challenged people. Owing to this, many researchers are interested in the direction of automated hand gestures recognition. Major applications include extremely wide range: from sign language to robot control or from virtual reality to intelligent home systems. In addition, these enable deaf and dumb to interface with machine in a more natural way. As a result, immense endeavours have been done in this domain and this article, therefore, reviews the major researches in a comprehensive manner.

Key-Words / Index Term

Gesture Recognition; Artificial Neural Networks; Computer Vision; Classification

References

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