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ID Globalization Across Multiple Convergence Spaces Using Smart Cameras

  • Geon Woo Kim
  • Jong Wook Han
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 214)

Abstract

This paper suggests a scheme for ID globalization, wherein the single successful authentication at initial stage requires no further authentication check while traversing multiple convergence spaces. This is done by delivering ID-related information among smart cameras during an object’s movement.

Keywords

ID globalization SAT Object tracking Security convergence 

Notes

Acknowledgments

This work was supported by the IT R&D program of KEIT&KCC&MKE, Korea. (KI002240, Development of Video Surveillance Security Technologies for Preserving Personal Security)

References

  1. 1.
    Kisacanin, B., Bhattacharyya, S.S., Chai, S.: Embedded Computer Vision, Springer-London, LNCS ISBM 978-1-84800-303-3, pp. 163–175 (2009)Google Scholar
  2. 2.
    Zhang, Y., Kiselewich, S.J., Bauson, W.A.: A monocular vision-based occupant classification approach for smart airbag deployment, pp. 632–637. Proceedings of IEEE Intelligent Vehicle Symposium, Las Vegas, Nevada (2005)Google Scholar
  3. 3.
    Hrahnstoever, N., Tu, P., Yu, T., Patwardhan, K., Hamilton, D., Yu, B., Greco, C., Doretto, G.: Intelligent video for protecting crowded sports venues, pp. 116–121. Proceedings of IEEE International Conference on Advanced Video and Signal based Surveillance, Genoa, Italy (2009)Google Scholar
  4. 4.
    Gilbert, A., Bowden, R.: Tracking objects across cameras by incrementally learning inter-camera color calibration and patterns of activity, Proceedings of 9th European Conference on Computer Vision, Graz, Austria, pp. 125–136 (2006)Google Scholar
  5. 5.
    Niu, C., Grimson, E.: Recovering non-overlapping network topology using far-field vehicle tracking data, Proceedings of 18th International Conference on Pattern Recognition, Hong Kong, vol. 4, pp. 944–949 (2006)Google Scholar
  6. 6.
    Cheng, E., Piccardi, M.: Matching of objects moving across disjoint cameras, pp. 1769–1772. Proceedings of IEEE International Conference on Image Processing, Atlanta (2006)Google Scholar
  7. 7.
    Javed, O., Shafigue, K., Shah, M.: Appearance modeling for tracking in multiple non-overlapping cameras, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, San Diego, pp. 26–33 (2005)Google Scholar
  8. 8.
    Zajdel, W., Krose, B.J.A.: A sequential Bayesian algorithm for surveillance with non-overlapping cameras. International Journal of Pattern Recognition and Artificial Intelligence 19(8), 977–996 (2005)CrossRefGoogle Scholar
  9. 9.
    Kim, H.G., Romberg, J., Wolf, W.: Multi-camera tracking on a graph using Markov Chain Monte Carlo. ACM/IEEE International Conference on Distributed Smart Cameras, Como, Italy (2009)Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Cyber Security-Convergence Research LaboratoryElectronics and Telecommunications Research InstituteDaejeonKorea

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