MRF Model for Detecting Abnormal Activates in Crowded Environments

Authors(2) :-K. Poomala, J. Jayageetha

This paper focus on detecting unusual activities in video. The analysis of motions and behaviours in crowded scenes constitutes a challenging task for traditional computer vision methods. To overcome this disadvantage there are different methods are used to detect the abnormalities in the video. This proposed method shows that a space-time MRF (Markov Random Field) model for detecting abnormal activities like bicycle passing through a crowd. This method not only localizes abnormal activities in crowded scenes, it can also capture the irregular interactions between local activities in a global sense. Histograms of Oriented Gradients (HOG) are used for capture the image from the particular video. The extraction of appearance characteristics in Region Of Interest (ROI) tracked over time using HOG descriptor. The robustness of this method in practical application can be understood by applying it on long surveillance videos.

Authors and Affiliations

K. Poomala
SNS College of Technology, Coimbatore, Tamilnadu, India
J. Jayageetha
SNS College of Technology, Coimbatore, Tamilnadu, India

MRF, HOG, ROI

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Publication Details

Published in : Volume 2 | Issue 2 | March-April 2016
Date of Publication : 2017-12-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 112-115
Manuscript Number : IJSRSET162228
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

K. Poomala, J. Jayageetha, " MRF Model for Detecting Abnormal Activates in Crowded Environments, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 2, pp.112-115, March-April.2016
URL : http://ijsrset.com/IJSRSET162228

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