Moving Objects Detection System on Spherical Panorama

  • Authors

    • Hong gue Kang
    • Soon Gohn Kim
    2018-06-08
    https://doi.org/10.14419/ijet.v7i2.33.17926
  • CCTV, Spherical Panorama, Moving Object Detection, DoF Algorithm, Image Processing.

  • Background/Objectives: As a security camera system, there is an image security system that uses CCTV (Closed Circuit TeleVision). For supervisory imaging device for CCTV, cameras are used.

    Methods/Statistical analysis: It was not possible to get valid level of result and not possible to detect minor changes since it is based on histogram. Therefore, this paper suggests spherical panorama image supervisory system with DoF(Difference of Frame) technique.

    Findings: The error-detection ratio and execution time are very important things. So, we experimented the error-detection and execution time on the same one panorama 21 images per one meter. The first performance index represent the execution time of each frame and second index represent the number of total frame and error detected frame on the each locations.

    Improvements/Applications: For supervisory imaging device for CCTV, cameras are used. There is method to install number of cameras to minimize blind spot. However, installation cost, using power, maintenance time and cost are dramatically increased due to increasing number of cameras.

     

  • References

    1. [1] Guler, S., Griffith, J. M., &Pushee, I. A.,Tracking and handoff between multiple perspective camera views. In Applied Imagery Pattern Recognition Workshop, 2003. Proceedings. 32nd, pp. 275-281.

      [2] Onoe Y., Yokoya N., Yamazawa K., &Takemur H.,Visual surveillance and monitoring system using an omnidirectional video camera.in Pattern Recognition, 1998. Proceedings,1998 August, pp. 588-592.

      [3] C. Stauffer and W.E.L. Grimson, Adaptive ackground mixture models for real-time tracking. Proc. IEEE CVPR. 1999 June, pp. 248-252.

      [4] Noriega P., Bernier O.,Real Time Illumination Invariant Background Subtraction Using Local Kernel Histograms. In BMVC. 2006 September, Vol. 6, pp. 979-988.

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  • How to Cite

    gue Kang, H., & Gohn Kim, S. (2018). Moving Objects Detection System on Spherical Panorama. International Journal of Engineering & Technology, 7(2.33), 1138-1140. https://doi.org/10.14419/ijet.v7i2.33.17926