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Reseach Article

Unsupervised Approach for Retrieving Shots from Video

by M. Kalaiselvi Geetha, S. Palanivel
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 60 - Number 6
Year of Publication: 2012
Authors: M. Kalaiselvi Geetha, S. Palanivel
10.5120/9693-4144

M. Kalaiselvi Geetha, S. Palanivel . Unsupervised Approach for Retrieving Shots from Video. International Journal of Computer Applications. 60, 6 ( December 2012), 1-8. DOI=10.5120/9693-4144

@article{ 10.5120/9693-4144,
author = { M. Kalaiselvi Geetha, S. Palanivel },
title = { Unsupervised Approach for Retrieving Shots from Video },
journal = { International Journal of Computer Applications },
issue_date = { December 2012 },
volume = { 60 },
number = { 6 },
month = { December },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume60/number6/9693-4144/ },
doi = { 10.5120/9693-4144 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:07:41.707644+05:30
%A M. Kalaiselvi Geetha
%A S. Palanivel
%T Unsupervised Approach for Retrieving Shots from Video
%J International Journal of Computer Applications
%@ 0975-8887
%V 60
%N 6
%P 1-8
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Acquiring the video information based on user requirement is an important research, that attracts the attention of most of the researchers today. This paper proposes an unsupervised shot transition detection algorithm using Autoassociative Neural Network (AANN) for retrieving video shots. The work further identifies the type of shot transition, whether abrupt or gradual. Keyframes are extracted from the detected shots and an index is created using k-means clustering algorithm for effective retrieval of required shots based on user query. The approach shows good performance in retrieving the shots, tested on five popular genres.

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Index Terms

Computer Science
Information Sciences

Keywords

Shot transition detection Autoassociative neural network kmeans clustering algorithm Shot retrieval