Skip to main content

A Study on Mosaic Based CCTV System Using Localization

  • Conference paper
  • 1766 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 5576))

Abstract

This paper proposes a combined recognition method related to frames based on a combined CCTV system using local partial images. The goal of the proposed algorithm is to reduce the combining speed and increase the overall recognition rate compared to existing methods. Since the SIFT algorithm, an existing method, has the disadvantages of being patented and slow, speed was raised to actually match the processing speed of CCTV in this paper by using an improved local image regeneration method. This paper consists of a description of the overall system based on the recognition rate and speed and use of localized images that was built along with an introduction to the algorithm. Performance was comparatively evaluated through actual tests. By applying this method to CCTV operating in real time, a low cost inline system which reduces monitoring fatigue since each individual screen need not be observed was built. In addition to being economically effective, it can also be used by regular users.

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   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
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. Szeliski, R.: Video mosaics for virtual environments. IEEE computer Graphics and Applications, 22–30 (March 1996)

    Google Scholar 

  2. Lemuz-López, R., Arias-Estrada, M.: Iterative Closest SIFT Formulation for Robust Feature Matching. In: Bebis, G., Boyle, R., Parvin, B., Koracin, D., Remagnino, P., Nefian, A., Meenakshisundaram, G., Pascucci, V., Zara, J., Molineros, J., Theisel, H., Malzbender, T. (eds.) ISVC 2006. LNCS, vol. 4292, pp. 502–513. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  3. Murase, H., Shree K, N.: Visual Learning and Recogntion 3-Dobject from appearance. International Journal of Computer Vision 14 (1995)

    Google Scholar 

  4. Zhang, J.Z., Chen, L.H.: Nonmonotone Levenberg–Marquardt Algorithms and Their Convergence Analysis. Journal of Optimization Theory and Applications 92(2) (1997)

    Google Scholar 

  5. Burschka, D., Cobzas, D., Dodds, Z., Hager, G., Jagersand, M., Yerex, K.: Recent Methods for Image-based Modeling and Rendering. IEEE Virtual Reality tutorial 1 (March 2003)

    Google Scholar 

  6. Kim, J.-M., Yang, H.-S., Lee, W.-K.: Network-Based Face Recognition System Using Multiple Images. In: Shi, Z.-Z., Sadananda, R. (eds.) PRIMA 2006. LNCS (LNAI), vol. 4088, pp. 626–631. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  7. Bennett, A., Magee, D.: Learning Sets of Sub-Models for Spatio-Temporal Prediction. In: Research and Development in Intelligent Systems, vol. XXIV, pp. 123–136 (November 2007)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Kim, JM., Kang, MA. (2009). A Study on Mosaic Based CCTV System Using Localization. In: Park, J.H., Chen, HH., Atiquzzaman, M., Lee, C., Kim, Th., Yeo, SS. (eds) Advances in Information Security and Assurance. ISA 2009. Lecture Notes in Computer Science, vol 5576. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02617-1_83

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-02617-1_83

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02616-4

  • Online ISBN: 978-3-642-02617-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics