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An Effective Method of Video Segmentation and Summarization for Surveillance

by Pratyush Pranjal, Rohit Lakhdive, Aditya Vasave, Atulkumar Varma, Amit Barve
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 95 - Number 2
Year of Publication: 2014
Authors: Pratyush Pranjal, Rohit Lakhdive, Aditya Vasave, Atulkumar Varma, Amit Barve
10.5120/16563-6227

Pratyush Pranjal, Rohit Lakhdive, Aditya Vasave, Atulkumar Varma, Amit Barve . An Effective Method of Video Segmentation and Summarization for Surveillance. International Journal of Computer Applications. 95, 2 ( June 2014), 1-3. DOI=10.5120/16563-6227

@article{ 10.5120/16563-6227,
author = { Pratyush Pranjal, Rohit Lakhdive, Aditya Vasave, Atulkumar Varma, Amit Barve },
title = { An Effective Method of Video Segmentation and Summarization for Surveillance },
journal = { International Journal of Computer Applications },
issue_date = { June 2014 },
volume = { 95 },
number = { 2 },
month = { June },
year = { 2014 },
issn = { 0975-8887 },
pages = { 1-3 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume95/number2/16563-6227/ },
doi = { 10.5120/16563-6227 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:18:21.374567+05:30
%A Pratyush Pranjal
%A Rohit Lakhdive
%A Aditya Vasave
%A Atulkumar Varma
%A Amit Barve
%T An Effective Method of Video Segmentation and Summarization for Surveillance
%J International Journal of Computer Applications
%@ 0975-8887
%V 95
%N 2
%P 1-3
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In today's world, video surveillance has become an integral part of investigation system. Video Segmentation and Summarization plays a crucial role in the field of Video analysis. The paper presents an approach that helps in extracting the movable segments from a large stable video. The system takes the video as input and extracts the movements from the video and identifies the time-intervals. Initially frames (images) are extracted from the video and compared consecutively. If some movements are detected then the movement signatures (start time – end time) are stored. Based on signaturesthe segmented and summarized video is generated. The result shows substantial improvement in video summarization process.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Key frame Video Segmentation and Summarization P-Hash

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