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DOI: 10.14569/IJACSA.2019.0100363
PDF

Real Time Analysis of Crowd Behaviour for Automatic and Accurate Surveillance

Author 1: E Padmalatha
Author 2: Karedla Anantha Sashi Sekhar
Author 3: Dasarada Ram Reddy Mudiam

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 3, 2019.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Surveillance in this modern era is a necessity. Creating an alert in case of emergencies and disturbances is of very much importance. As the number of simultaneous camera feeds increase, burden on human supervisor also increases. The proposed system is a way to aid human supervisor in the surveillance job. Creating alerts in real time will help responding quickly to crucial situations. With this in mind, we propose the following things: (1) Generation of ViF (Violent Flow Descriptors) as high-level features in real time. (2) Using generated ViF’s of a Video Dataset for training a neural net and testing its accuracy.(3) Developing a system that can detect the signs of disturbance among the crowd in real time and can learn from the decisions it makes.

Keywords: Real time surveillance; violent flow descriptors; neural network

E Padmalatha, Karedla Anantha Sashi Sekhar and Dasarada Ram Reddy Mudiam, “Real Time Analysis of Crowd Behaviour for Automatic and Accurate Surveillance” International Journal of Advanced Computer Science and Applications(IJACSA), 10(3), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100363

@article{Padmalatha2019,
title = {Real Time Analysis of Crowd Behaviour for Automatic and Accurate Surveillance},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100363},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100363},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {3},
author = {E Padmalatha and Karedla Anantha Sashi Sekhar and Dasarada Ram Reddy Mudiam}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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