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Reflection Removal for People Detection in Video Surveillance Applications

  • Dajana Conte
  • Pasquale Foggia
  • Gennaro Percannella
  • Francesco Tufano
  • Mario Vento
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6978)

Abstract

In this paper we present a method removing reflection of people on shiny floors in the context of people detection for video analysis applications. The method exploits chromatic properties of the reflections and does not require a geometric model of the objects. An experimental evaluation of the proposed method, performed on a significant database containing several publicly available videos, demonstrates its effectiveness. The proposed technique also favorably compares with respect to other state of the art algorithms for reflection removal.

Keywords

Foreground Object Foreground Region Shadow Detection Foreground Detection Foreground Mask 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Dataset for PETS 2006, http://www.cvg.rdg.ac.uk/PETS2006/
  2. 2.
  3. 3.
    Conte, D., Foggia, P., Petretta, M., Tufano, F., Vento, M.: Evaluation and improvements of a real-time background subtraction method. In: Kamel, M.S., Campilho, A.C. (eds.) ICIAR 2005. LNCS, vol. 3656, pp. 1234–1241. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  4. 4.
    Horprasert, T., Harwood, D., Davis, L.: A statistical approach for real-time robust background subtraction and shadow detection (1999)Google Scholar
  5. 5.
    Karaman, M., Goldmann, L., Sikora, T.: Improving object segmentation by reflection detection and removal. In: Proc. of SPIE-IS&T Electronic Imaging (2009)Google Scholar
  6. 6.
    Shen, J.: Motion detection in color image sequence and shadow elimination. Visual Communications and Image Processing 5308, 731–740 (2004)Google Scholar
  7. 7.
    Teschioni, A., Regazzoni, C.S.: A robust method for reflection analysis in color image sequences. In: IX European Signal Processing Conference, Eusipco 1998 (1998)Google Scholar
  8. 8.
    Zhao, T., Nevatia, R.: Tracking multiple humans in complex situations. IEEE Trans. on Pattern Analysis and Machine Intelligence 26, 1208–1221 (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Dajana Conte
    • 1
  • Pasquale Foggia
    • 1
  • Gennaro Percannella
    • 1
  • Francesco Tufano
    • 1
  • Mario Vento
    • 1
  1. 1.Dipartimento di Ingegneria Elettronica e Ingegneria InformaticaUniversità di SalernoFiscianoItaly

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