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A Review on Human Activity Recognition System

N. Geetha1 , E. S. Samundeeswari2

Section:Review Paper, Product Type: Journal Paper
Volume-6 , Issue-12 , Page no. 825-829, Dec-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i12.825829

Online published on Dec 31, 2018

Copyright © N. Geetha, E. S. Samundeeswari . 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: N. Geetha, E. S. Samundeeswari, “A Review on Human Activity Recognition System,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.825-829, 2018.

MLA Style Citation: N. Geetha, E. S. Samundeeswari "A Review on Human Activity Recognition System." International Journal of Computer Sciences and Engineering 6.12 (2018): 825-829.

APA Style Citation: N. Geetha, E. S. Samundeeswari, (2018). A Review on Human Activity Recognition System. International Journal of Computer Sciences and Engineering, 6(12), 825-829.

BibTex Style Citation:
@article{Geetha_2018,
author = {N. Geetha, E. S. Samundeeswari},
title = {A Review on Human Activity Recognition System},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {12 2018},
volume = {6},
Issue = {12},
month = {12},
year = {2018},
issn = {2347-2693},
pages = {825-829},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3423},
doi = {https://doi.org/10.26438/ijcse/v6i12.825829}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i12.825829}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3423
TI - A Review on Human Activity Recognition System
T2 - International Journal of Computer Sciences and Engineering
AU - N. Geetha, E. S. Samundeeswari
PY - 2018
DA - 2018/12/31
PB - IJCSE, Indore, INDIA
SP - 825-829
IS - 12
VL - 6
SN - 2347-2693
ER -

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Abstract

Action recognition being one of the hot topics of many research efforts and being useful in so many commercial and scientific fields. Action recognition concerns the extraction ofactivity based knowledge, image data relationship or other patterns implicitly or explicitly stored in the images. Action in images is one of the powerful sources of high-level semantics. Recognition can be used for recognizing activities occurring in a particular scene. There is a need of effective and efficient methods to be encounter for recognizing the activities of human. The goal of this work is to study various recognition methods of common human actions represented in images. In this research, we present detailed insights on existing works and the methodologies used by researchers for recognizing the human activities. Comparison among different human activities by similarity systems is particularly challenging owing to the great variety of techniques implemented to represent likeness and the dependence that the results present of the used image dataset. This will be helpful to the researchers for their future research direction in this area.

Key-Words / Index Term

Human Activities, Segmentation, Feature Extraction, Classification, Human Action Recognition

References

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