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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3809))

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Abstract

This paper presents a complete visual surveillance system for automatic scene interpretation of airport aprons. The system comprises two main modules — Scene Tracking and Scene Understanding. The Scene Tracking module is responsible for detecting, tracking and classifying the semantic objects within the scene using computer vision. The Scene Understanding module performs high level interpretation of the observed objects by detecting video events using cognitive vision techniques based on spatio-temporal reasoning. The performance of the system is evaluated for a series of pre-defined video events specified using a video event ontology.

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References

  1. Aguilera, J., Wildernauer, H., Kampel, M., Borg, M., Thirde, D., Ferryman, J.: Evaluation of motion segmentation quality for aircraft activity surveillance. In: Proc. Joint IEEE Int. Workshop on VS-PETS, Beijing (October 2005)

    Google Scholar 

  2. Allen, J.F.: Maintaining knowledge about temporal intervals. Communications of the ACM 26(11), 823–843 (1983)

    Article  Google Scholar 

  3. Bar-Shalom, Y., Li, X.R.: Multitarget-Multisensor Tracking: Principles and Techniques. YBS Publishing (1995)

    Google Scholar 

  4. Black, J., Ellis, T.J.: Multi Camera Image Measurement and Correspondence. Measurement - Journal of the International Measurement Confederation 35(1), 61–71 (2002)

    Google Scholar 

  5. Thonnat, M., Brémond, F., Maillot, N., Vu, V.: Ontologies for video events. Research report number 51895 (November 2003)

    Google Scholar 

  6. Horprasert, T., Harwood, D., Davis, L.S.: A statistical approach for real-time robust background subtraction and shadow detection. In: IEEE ICCV 1999 FRAME-RATE Workshop (1999)

    Google Scholar 

  7. Jabri, S., Duric, Z., Wechsler, H., Rosenfeld, A.: Detection and location of people in video images using adaptive fusion of color and edge information. In: Proc. IAPR Internation Conference on Pattern Recognition, pp. 4627–4631 (2000)

    Google Scholar 

  8. Shi, J., Tomasi, C.: Good features to track. In: Proc. of IEEE Conference on Computer Vision and Pattern Recognition, pp. 593–600 (1994)

    Google Scholar 

  9. Stauffer, C., Grimson, W.E.L.: Adaptive background mixture models for real-time tracking. In: Proc. International Conference on Pattern Recognition, pp. 246–252 (1999)

    Google Scholar 

  10. Sullivan, G.D.: Visual interpretation of known objects in constrained scenes. Phil. Trans. R. Soc. Lon. B(337), 361–370 (1992)

    Article  Google Scholar 

  11. Thirde, D., Borg, M., Valentin, V., Fusier, F., Aguilera, J., Ferryman, J., Brémond, F., Thonnat, M., Kampel, M.: Visual surveillance for aircraft activity monitoring. In: Proc. Joint IEEE Int. Workshop on VS-PETS, Beijing (October 2005)

    Google Scholar 

  12. Vu, V., Brémond, F., Thonnat, M.: Automatic video interpretation: A novel algorithm for temporal event recognition. In: IJCAI 2003, Acapulco, Mexico (August 2003)

    Google Scholar 

  13. Wren, C.R., Azarbayejani, A., Darrell, T., Pentland, A.: Pfinder: Real-time tracking of the human body. IEEE Transactions on PAMI 19(7), 780–785 (1997)

    Google Scholar 

  14. Xiang, T., Gong, S.: On the structure of dynamic bayesian networks for complex scene modelling. In: Proc. Joint IEEE Int. Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance (VS-PETS), October 2003, pp. 17–22 (2003)

    Google Scholar 

  15. Xu, G., Zhang, Z.: Epipolar Geometry in Stereo, Motion and Object Recognition: A Unified Approach. Kluwer Academic Publ., Dordrecht (1996)

    MATH  Google Scholar 

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© 2005 Springer-Verlag Berlin Heidelberg

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Ferryman, J. et al. (2005). Automated Scene Understanding for Airport Aprons. In: Zhang, S., Jarvis, R. (eds) AI 2005: Advances in Artificial Intelligence. AI 2005. Lecture Notes in Computer Science(), vol 3809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11589990_62

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