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Enhancing Tracking Capabilities of KDE Background Subtraction-Based Algorithm Using Edge Histograms

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Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 403))

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Abstract

The paper presents a method which allows to improve tracking abilities of conventional background subtraction-based algorithm. The presented algorithm which is a result of the studies is a hybrid method consisting of the Kernel Density Estimation (KDE) background subtraction tracking method and the Edge Histograms Displacement Calculation (EHDC) algorithm. Tracking ratios before and after merging with EHDC have been measured and presented. The paper also describes an algorithm eliminating cyclic changes in image’s intensities values, which have significant influence on the input data for the hybrid algorithm. The influence of moving-camera video specificity on the output data has been pointed out.

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References

  1. Rokita, P.: Fast tracking using edge histograms. SPIE. Real-Time Imaging II, vol. 3028, p. 91, 3 Apr 1997

    Google Scholar 

  2. Kowaleczko P., Rokita P.: Wykorzystanie algorytmow opartych na metodzie Edge Histograms do okreslenia parametrow ruchu kamer glowicy optoelektronicznej WH-1 (in Polish), KNTWE 2014 conference materials (2014)

    Google Scholar 

  3. Lewis, J.P.: Fast normalized cross-correlation. Vis. Interface 10(1), 120–123 (1995)

    Google Scholar 

  4. Yilmaz, A., Javed, O., Shah, M.: Object tracking—a survey. Acm Comput. Surv. (CSUR) 38(4), 13 (2006)

    Article  Google Scholar 

  5. Benezeth Y., Jodoin P., Emile B., Laurent H., Rosenberger C.: Review and Evaluation of Commonly-Implemented Background Subtraction Algorithms. In: Pattern Recognition, ICPR 2008, 19th International Conference on Pattern Recognition (2008)

    Google Scholar 

  6. Piccardi, M.: Background subtraction techniques: a review. 2004 IEEE Int. Conf. Syst. Man Cybern. 4, 3099–3104 (2004)

    Article  Google Scholar 

  7. Elgammal A., Harwood D., Davis L.: Non-parametric model for background subtraction, ECCV (2000)

    Google Scholar 

  8. Babich, G.A., Camps, O.I.: Weighted Parzen windows for pattern classification. IEEE Trans. Pattern Anal. Mach. Intell. 18(5), 567–570 (1996)

    Article  Google Scholar 

  9. Kovac J., Peer P., Solina F.: Eliminating the Influence of Non-Standard Illumination from Images, Technical Report, (2003)

    Google Scholar 

  10. OpenCV documentation, http://docs.opencv.org

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Author information

Authors and Affiliations

  1. C4ISR Systems Integration Division, Air Force Institute of Technology, Ksiecia Boleslawa 6, 01-494, Warsaw, Poland

    Piotr Kowaleczko

  2. Faculty of Cybernetics, Military University of Technology, Gen. S. Kaliskiego 2, 00-908, Warsaw, Poland

    Przemyslaw Rokita

Authors
  1. Piotr Kowaleczko
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  2. Przemyslaw Rokita
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Corresponding author

Correspondence to Piotr Kowaleczko .

Editor information

Editors and Affiliations

  1. Department of Systems, Wrocław University of Technology, Wroclaw, Poland

    Robert Burduk

  2. Department of Systems and Computer, Wrocław University of Technology, Wroclaw, Poland

    Konrad Jackowski

  3. Department of Systems and Computer, Wrocław University of Technology, Wroclaw, Poland

    Marek Kurzyński

  4. Dept. of Systems and Computer Networks, Wrocław University of Technology, Wroclaw, Poland

    Michał Woźniak

  5. Department of Systems, Wrocław University of Technology, Wroclaw, Poland

    Andrzej Żołnierek

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Kowaleczko, P., Rokita, P. (2016). Enhancing Tracking Capabilities of KDE Background Subtraction-Based Algorithm Using Edge Histograms. In: Burduk, R., Jackowski, K., Kurzyński, M., Woźniak, M., Żołnierek, A. (eds) Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015. Advances in Intelligent Systems and Computing, vol 403. Springer, Cham. https://doi.org/10.1007/978-3-319-26227-7_70

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  • DOI: https://doi.org/10.1007/978-3-319-26227-7_70

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26225-3

  • Online ISBN: 978-3-319-26227-7

  • eBook Packages: EngineeringEngineering (R0)

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