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Tracking Movements of Humans in a Real-Time Surveillance Scene

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 437)

Abstract

Increased security concern has brought up an acute need for being thoughtful in the area of surveillance. The normal trend of surveillance followed is a grid of CCTV cameras with control centralized at a room, which is manually looked upon by a caretaker. Many a times there is no regular watch carried by caretaker, instead logs of video footage are maintained, which are used in the case of any mishaps occurring. This is the practice followed even at major sensitive places. This is a retroactive kind of situation handling. A solution to this could be a system that continuously has a watch using a camera and indentifies a human object and then tracks its movement to identify any uncommon behavior. The sudden responsive action (reaction) made by the caretaker is the expected design objective of the system. In this paper we have proposed a system that analyzes the real-time video stream from camera, identifying a human object anfd then tracking its movement if it tries to go out of the field of view (FoV) of the camera. That is, the camera changes its FoV with the movement of the object.

Keywords

  • Object detection
  • Haar-like features
  • Cascade classifier
  • Surveillance
  • Camera
  • Microcontroller
  • Angular shift
  • Servo motor

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References

  1. Haering, N., Venetianer, P.L., Lipton, A.: The evolution of video surveillance: an overview. Mach. Vis. Appl. 19(5-6), 279–290 (2008)

    CrossRef  Google Scholar 

  2. Open Computer Vision Library Reference Manual. Intel Corporation, USA (2001)

    Google Scholar 

  3. Dollar, P., Wojek, C., Schiele, B., Perona, P.: Pedestrian detection: a benchmark. In: Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (2009)

    Google Scholar 

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

    CrossRef  Google Scholar 

  5. Viola, P., Jones, M., Snow, D.: Detecting pedestrians using patterns of motion and appearance. In: Proceedings of IEEE International Conference on Computer Vision, pp. 734–741 (2003)

    Google Scholar 

  6. Wu, B., Nevatia, R.: Detection and tracking of multiple, partially occluded humans by bayesian combination of edgelet based part detectors. Int. J. Comput. Vision 75(2), 247–266 (2007)

    CrossRef  Google Scholar 

  7. Wu, J., Liu, N., Rehg, J.M.: A real-time object detection framework. IEEE Trans. Image Process. (2013)

    Google Scholar 

  8. Qiang, Z. et al.: Fast human detection using a cascade of histograms of oriented gradients. In: 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2. IEEE (2006)

    Google Scholar 

  9. Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2001. CVPR 2001. vol. 1. IEEE (2001)

    Google Scholar 

  10. Wilson, P.I., Fernandez, J.: Facial feature detection using Haar classifiers. J. Comput. Sci. Coll. 21(4), 127–133 (2006)

    Google Scholar 

  11. Menezes, P., Barreto, J.C., Dias, J.: Face tracking based on haar-like features and eigenfaces. In: IFAC/EURON Symposium on Intelligent Autonomous Vehicles (2004)

    Google Scholar 

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Correspondence to Dushyant Kumar Singh .

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Singh, D.K., Kushwaha, D.S. (2016). Tracking Movements of Humans in a Real-Time Surveillance Scene. In: Pant, M., Deep, K., Bansal, J., Nagar, A., Das, K. (eds) Proceedings of Fifth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 437. Springer, Singapore. https://doi.org/10.1007/978-981-10-0451-3_45

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  • DOI: https://doi.org/10.1007/978-981-10-0451-3_45

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-0450-6

  • Online ISBN: 978-981-10-0451-3

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