Open Access   Article Go Back

A Preliminary Investigation on a Novel Approach for Efficient and Effective Video Classification Model

M. Ramesh1 , K. Mahesh2

Section:Survey Paper, Product Type: Journal Paper
Volume-07 , Issue-05 , Page no. 266-269, Mar-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7si5.266269

Online published on Mar 10, 2019

Copyright © M. Ramesh, K. Mahesh . 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.

View this paper at   Google Scholar | DPI Digital Library

XML View
PDF Download

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: M. Ramesh, K. Mahesh, “A Preliminary Investigation on a Novel Approach for Efficient and Effective Video Classification Model,” International Journal of Computer Sciences and Engineering, Vol.07, Issue.05, pp.266-269, 2019.

MLA Style Citation: M. Ramesh, K. Mahesh "A Preliminary Investigation on a Novel Approach for Efficient and Effective Video Classification Model." International Journal of Computer Sciences and Engineering 07.05 (2019): 266-269.

APA Style Citation: M. Ramesh, K. Mahesh, (2019). A Preliminary Investigation on a Novel Approach for Efficient and Effective Video Classification Model. International Journal of Computer Sciences and Engineering, 07(05), 266-269.

BibTex Style Citation:
@article{Ramesh_2019,
author = {M. Ramesh, K. Mahesh},
title = {A Preliminary Investigation on a Novel Approach for Efficient and Effective Video Classification Model},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {3 2019},
volume = {07},
Issue = {05},
month = {3},
year = {2019},
issn = {2347-2693},
pages = {266-269},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=845},
doi = {https://doi.org/10.26438/ijcse/v7i5.266269}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i5.266269}
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=845
TI - A Preliminary Investigation on a Novel Approach for Efficient and Effective Video Classification Model
T2 - International Journal of Computer Sciences and Engineering
AU - M. Ramesh, K. Mahesh
PY - 2019
DA - 2019/03/10
PB - IJCSE, Indore, INDIA
SP - 266-269
IS - 05
VL - 07
SN - 2347-2693
ER -

           

Abstract

In the recent ten to fifteen years web developers and web users expend more amount of time on images and videos. Since video is an admirable tool for delivering content, it has one of the major roles in human daily life. There are many kinds of videos available in real life and therefore we need an important tool to perform classification on video-based applications. Video classification and video content analysis is one of the ongoing research areas in the field of computer vision. The main goal of video classification is to help the viewers to find video of their own interest. We need a tool to classify the video with sky scramble accuracy. Therefore, we propose a model for video classification with several medium layers. This model takes video as an input passed through various layers and produce the video class label. The class label may be sports, movies, advertisement, cartoon, news etc.

Key-Words / Index Term

Video Classification, Keyframe, Video Frame, Background Subtraction

References

[1] M. Ramesh1*, K. Mahesh2, “Multidimentional View of Automatic Video Classification : An Elucidation”, International Journal of Computer Sciences and Engineering, Vol-6, Special Issue-4, May 2018.
[2] Jiajun Sun, Jing Wang, Ting-chun Yeh, “Video understanding: From video classification to captioning”.
[3] Nirav Bhatt, - “A survey on video classification techniques‖, International Journal of Emerging Technologies and Innovative Research”, March 2015, Volume 2, Issue 3.
[4] Darin Brezeale and Diane J. Cook, - “Automatic Video Classification: A Survey of Literature”, IEEE Transactions on systems, man, and cybernetics—part c: applications and reviews, vol. 38, no. 3, may 2008.
[5] A.D.Bimbo, “Visual information retrieval, San Francisco”, CA: Morgan kaufman, 1999.
[6] Insaf Setitra, “Object Classification in Videos—An Overview”, Journal of Automation and Control Engineering, Vol. 1, No. 2, June 2013
[7] M. Ramesh1*, K. Mahesh2, ,” Significance of various Video Classification Techniques and Methods: A Retrospective”,International Journal of Pure and Applied Mathematics, Volume 118 No. 8 2018, 523-526.
[8] S.Maheshwari, P. Arockia Jansi Rani, “Human Action Recognition System Based on Silhouette”, International Journal of Computer and Information Engineering, VOl. 9, No:110, 2015.
[9] Darin Brezeale and Diane J. Cook, ―”Automatic Video Classification: A Survey of Literature‖, IEEE Transactions on systems, man, and cybernetics—part c: applications and reviews”, vol. 38, no. 3, may 2008.
[10] Reza Fuad Rachmadi†∗ , Keiichi Uchimura†, and Gou Koutaki, - “Video classification using compacted dataset based on selected keyframe”, Proceedings of the International Conference,2016 IEEE Region.
[11] Shankar, K., K. Mahesh, and K. Kuppusamy. – “Analyzing Image Quality via Color Spaces” image. In 1.1 (2014).
[12] Mittal C. Darji1, Dipti Mathpal2, - “ A Review of Video Classification Techniques”, International Research Journal of Engineering and Technology (IRJET), Volume: 04 Issue: 06 | June -2017.