Implementation of a Real-Time Image Object Tracking System for PTZ Cameras

  • Sang-Gu Lee
  • R. Batkhishig
Part of the Communications in Computer and Information Science book series (CCIS, volume 206)


In this paper, we implement a real-time surveillance monitoring and image object tracking system using PTZ (Pan-Tilt-Zoom) camera. For image object tracking, we use the mean shift tracking algorithm based on the color image distribution of detected object. Mean shift algorithm is efficient for real-time tracking because of its fast and stable performance. In this system, MatLab language is used for clustering moving object and accessing the PTZ protocol and RS-485 communication for controlling the position of PTZ cam-era in order to arrange the moving objects in the middle part of the monitor screen. This system can be applied to an effective and fast image surveillance system for continuous object tracking in a wider area.

Index Terms

Image object tracking PTZ camera Mean shift algorithm 


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  1. 1.
    Sonka, M., Hlavac, V., Boyle, R.: Image Processing, Analysis, and Machine Vision, 3rd edn. Thomson (2008)Google Scholar
  2. 2.
    Comaniciu, D., Meer, P.: Mean shift: A Robust Approach Toward Feature Space Analysis. IEEE Tr. on PAMI 24(5), 603–619 (2002)CrossRefGoogle Scholar
  3. 3.
    Comaniciu, D., Meer, P.: Kernel-based object tracking. IEEE Trans. PAMI 25(5), 564–577 (2003)CrossRefGoogle Scholar
  4. 4.
    Samsung Techwin, PTZ Dome Camera SPD-1000 Manual (2010)Google Scholar
  5. 5.
    Lee, S.G., Hwang, S.K.: Implementation of an Object Tracking System using Mean shift Algorithm for PTZ camera. In: IPIU 2011, Jeju, Korea (February 2011)Google Scholar
  6. 6.
    Nixon, M., Aguado, A.: Feature Extraction and Image Processing, 2nd edn. Academic Press, London (2008)Google Scholar
  7. 7.
    Jain, A.K., Duin, R.P.W., Mao, J.: Statistical Pattern Recognition: A Review. IEEE Trans. Pattern Analysis and Machine Intelligence 22(1), 4–37 (2000)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Sang-Gu Lee
    • 1
  • R. Batkhishig
    • 1
  1. 1.Department of Computer EngineeringHannam UniversityDaejonKorea

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