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Video Surveillance Based Tracking System

  • R. Venkatesan
  • P. Dinesh Anton Raja
  • A. Balaji Ganesh
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 324)

Abstract

The paper presents video surveillance-based tracking system for the outdoor environment. The video processing has been done using both LabVIEW and MATLAB, and the comparisons are illustrated. In LabVIEW, self-learning and real-time moving object tracking are implemented for the surveillance of environment. In a two-dimensional color pattern matching, a self-learned template has to be located on real-time video, regardless of the template’s position, color, and shape. It is done by organizing a set of feature vectors that encompass all the variations in the self-learned template. Matching is then done by determining the best similarity between the feature vectors extracted from the video image and the self-learned template set. Template learning time and elapsed time are taken as parameters for the comparison. In MATLAB, tracking is achieved using Camshift algorithm. The feature vectors include position, orientation, and size of the object to be tracked.

Keywords

Camshift algorithm Self-autonomous video surveillance Tracking system Region of interest LabVIEW and MATLAB 

Notes

Acknowledgments

The authors wish to thank Department of Science and Technology for awarding a project under Cognitive Science Initiative Programme (DST File No.: SR/CSI/09/2011) through which the work has been implemented.

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Copyright information

© Springer India 2015

Authors and Affiliations

  • R. Venkatesan
    • 1
  • P. Dinesh Anton Raja
    • 1
  • A. Balaji Ganesh
    • 1
  1. 1.Department of TIFAC COREVelammal Engineering CollegeChennaiIndia

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