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Detect and Track the Motion of Any Moving Object Using OpenCV

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Cyber Security in Intelligent Computing and Communications

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1007))

Abstract

This paper represents the moving object that can detect and track in a computer system with the help of OpenCV and image processing. In this paper, we found that a video picture is moving and that moving object is detected using OpenCV and the detected picture has been represented in frames with the help of contour by computer vision (CV) in a computer system. Detecting and recognizing an object is the initial stage of image systems in computer vision. Therefore, is a real-time identification of tracking a large moving object system using open computer vision (CV). In future work we focus on the security surveillance system to improve the influence of moving object detection using OpenCV.

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References

  1. M. Kirby, L. Sirovich, Application of the Karhunen-Loeve procedure for the characterization of human faces. IEEE Trans. Pattern Anal. Mach. Intell. 12(1), 103–108 (1990)

    Google Scholar 

  2. L.J. Latecki, V. Rajagopal, A. Gross, Image retrieval and reversible illumination normalization. Internet Imaging VI, vol. 5670 (International Society for Optics and Photonics, 2005)

    Google Scholar 

  3. K. Goyal, A. Kartikey, K. Rishi, Face detection and tracking: using OpenCV, in 2017 International conference of Electronics, Communication and Aerospace Technology (ICECA), vol. 1 (IEEE, 2017)

    Google Scholar 

  4. G. Bradski, A. Kaehler, Learning OpenCV computer vision with the OpenCV library. (O’Reilly Media, Inc., 2008).

    Google Scholar 

  5. N. Saini, S. Kaur, H. Singh, A review: face detection methods and algorithms. Int. J. Eng. Res. Technol. (IJERT) 2(Issue 6) (2013). ISSN: 2278-0181. www.ijert.org

  6. D.J. Robertson, R.S.S. Kramer, A. Mike Burton, Face averages enhance user recognition for smartphone security. Plos One 10.3, e0119460 (2015)

    Google Scholar 

  7. S. Tripathi, V. Sharma, S. Sharma, Face detection using combined skin color detector and template matching method. Int. J. Comput. Appl. 26(7) (2011)

    Google Scholar 

  8. H. Makwana, T. Singh, Comparison of different algorithm for face recognition. Glob. J. Comput. Sci. Technol. (2014)

    Google Scholar 

  9. N. Rani et al., Analyzing the performance of image segmentation using its efficient architecture. (2007)

    Google Scholar 

  10. P. Spagnolo, M. Leo, A. Distante, Moving object segmentation by background subtraction and temporal analysis. Image Vis. Comput. 24(5), 411–423 (2006)

    Google Scholar 

  11. P.W. Power, J.A. Schoonees, Understanding background mixture models for foreground segmentation, in Proceedings Image and Vision Computing New Zealand. (2002)

    Google Scholar 

  12. P. Viola, M.J. Jones, Robust real-time face detection. Int. J. Comput. Vis. 57(2), 137–154 (2004)

    Google Scholar 

  13. A.K. Chauhan, P. Krishan, Moving object tracking using gaussian mixture model and optical flow. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 3(4), 243–246 (2013)

    Google Scholar 

  14. D.-S. Chen, Z.-K. Liu, Generalized Haar-like features for fast face detection, in 2007 International Conference on Machine Learning and Cybernetics, vol. 4 (IEEE, 2007)

    Google Scholar 

  15. K. Meenatchi, P. Subhashini, Multiple object tracking and segmentation in video sequences. Int. J. 2(5), 71–79 (2014)

    Google Scholar 

  16. V. Naidu, J. Raol, Object tracking using image registration and Kalman filter, in International Conference on Avionics Systems. (2008)

    Google Scholar 

  17. A. Tiwari, J. Verma, Scene understanding using back propagation by neural network. (2011)

    Google Scholar 

  18. M.S. Kalas, Real time face detection and tracking using OpenCV. Int. J. Soft Comput. Artif. Intell. 2(1), 41–44 (2014)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Information Technology, GL Bajaj Institute of Technology and Management, Greater Noida, India

    Harikesh Pandey, Pushpa Choudhary & Arjun Singh

Authors
  1. Harikesh Pandey
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  2. Pushpa Choudhary
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  3. Arjun Singh
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Editor information

Editors and Affiliations

  1. GL Bajaj Institute of Technology and Management, Greater Noida, Uttar Pradesh, India

    Rajeev Agrawal

  2. Kennesaw State University, Kennesaw, GA, USA

    Jing He

  3. Malaviya National Institute of Technology (MNIT), Jaipur, India

    Emmanuel Shubhakar Pilli

  4. Department of Master of Computer Applications, GL Bajaj Institute of Technology and Management, Greater Noida, Uttar Pradesh, India

    Sanjeev Kumar

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Pandey, H., Choudhary, P., Singh, A. (2022). Detect and Track the Motion of Any Moving Object Using OpenCV. In: Agrawal, R., He, J., Shubhakar Pilli, E., Kumar, S. (eds) Cyber Security in Intelligent Computing and Communications. Studies in Computational Intelligence, vol 1007. Springer, Singapore. https://doi.org/10.1007/978-981-16-8012-0_27

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  • DOI: https://doi.org/10.1007/978-981-16-8012-0_27

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-8011-3

  • Online ISBN: 978-981-16-8012-0

  • eBook Packages: EngineeringEngineering (R0)

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