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Anomaly Detection in Surveillance Video using Color Modeling

by M. Gangadharappa, Pooja Goel, Rajiv Kapoor
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 45 - Number 14
Year of Publication: 2012
Authors: M. Gangadharappa, Pooja Goel, Rajiv Kapoor
10.5120/6845-9231

M. Gangadharappa, Pooja Goel, Rajiv Kapoor . Anomaly Detection in Surveillance Video using Color Modeling. International Journal of Computer Applications. 45, 14 ( May 2012), 1-6. DOI=10.5120/6845-9231

@article{ 10.5120/6845-9231,
author = { M. Gangadharappa, Pooja Goel, Rajiv Kapoor },
title = { Anomaly Detection in Surveillance Video using Color Modeling },
journal = { International Journal of Computer Applications },
issue_date = { May 2012 },
volume = { 45 },
number = { 14 },
month = { May },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume45/number14/6845-9231/ },
doi = { 10.5120/6845-9231 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:37:34.704499+05:30
%A M. Gangadharappa
%A Pooja Goel
%A Rajiv Kapoor
%T Anomaly Detection in Surveillance Video using Color Modeling
%J International Journal of Computer Applications
%@ 0975-8887
%V 45
%N 14
%P 1-6
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The primary goal of this paper propose an algorithm for automatic detection of abnormal events in video surveillance scenarios. We specifically focus our attention on the event of object dropping in public places such as railway stations and airports etc. We look into how to distinguish events in surveillance video, and further what is a remarkable event. Analyzing surveillance data, without the knowledge of when and where or even if an interesting event has occurred which often takes place, is very time consuming labour. In this kind of analysis we are interested in extraordinary events, something that deviates from the normal.

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Index Terms

Computer Science
Information Sciences

Keywords

Abnormal Events Surveillance Videos Object Tracking Feature- Extraction And Feature- Analysis

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