Skip to main content

Elimination of Moving Shadow Based on Vibe and Chromaticity from Surveillance Videos

  • Conference paper
  • 2363 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8610))

Abstract

Shadow removal is one of the most important parts of moving object recognition in the field of intelligent video surveillance since the shadow definitely affects the recognition performance. This is caused from that shadows share the same movement patterns and similar magnitude of intensity to those of the foreground objects. Therefore, in this paper, to effectively remove moving shadows from video, a new approach based on chromaticity and a well-known universal background subtraction named as Vibe was proposed. Experimental results prove that moving shadows can be removed effectively by the proposed approach than the other ones.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Cucchiara, R., Grana, C., Piccardi, M., Prati, A.: Detecting moving objects, ghosts, and shadows in video streams. IEEE Trans. on Pattern Analysis and Machine Intelligence 25(10) (October 2003)

    Google Scholar 

  2. Barnich, O., Van Droogenbroeck, M.: Vibe: A Universal Background Subtraction Algorithm for Video Sequences. IEEE Trans. on Image Processing 20(6) (June 2011)

    Google Scholar 

  3. Sanin, A., Sanderson, C., Lovell, B.C.: Shadow Detection: A Survey and Comparative Evaluation of Recent Methods. Pattern Recognition 45(4), 1684–1695 (2012)

    Article  Google Scholar 

  4. Nadimi, S., Bhanu, B.: Physical models for moving shadow and object detection. IEEE Trans. on Pattern Analysis and Machine Intelligence 26(8) (August 2004)

    Google Scholar 

  5. Chang, C.-J., Hu, W.-F., Hsieh, J.-W., Chen, Y.-S.: Shadow elimination for effective moving object detection with Gaussian models. In: Proc. of the 16th Int’l Conf. on Pattern Recognition, pp. 540–543 (2002)

    Google Scholar 

  6. Sanin, A., Sanderson, C., Lovell, B.C.: Improved Shadow Removal for Robust Person Tracking in Surveillance Scenarios. In: Proc. of the 20th Int’l Conf. on Pattern Recognition, pp. 141–144 (August 2010)

    Google Scholar 

  7. Stauffer, C., Grimson, E.: Adaptive background mixture models for real-time tracking. In: Proc. of IEEE Int. Conf. on Computer Vision and Pattern Recognition, pp. 246–252 (June 1999)

    Google Scholar 

  8. Zhu, Z., Lu, X.: An Accurate Shadow Removal Method for Vehicle Tracking. In: Proc. of Int’l Conf. on Artificial Intelligence and Computational Intelligence (AICI), pp. 59–62 (October 2010)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Zhao, H., Kang, M.W., Kim, K.Y., Kim, YS. (2014). Elimination of Moving Shadow Based on Vibe and Chromaticity from Surveillance Videos. In: Ślȩzak, D., Schaefer, G., Vuong, S.T., Kim, YS. (eds) Active Media Technology. AMT 2014. Lecture Notes in Computer Science, vol 8610. Springer, Cham. https://doi.org/10.1007/978-3-319-09912-5_46

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-09912-5_46

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09911-8

  • Online ISBN: 978-3-319-09912-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics