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Context Data to Improve Association in Visual Tracking Systems

  • A. M. Sánchez
  • M. A. Patricio
  • J. García
  • J. M. Molina
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4528)

Abstract

A key aspect in visual surveillance systems is robust movement segmentation, which is still a difficult and unresolved problem. In this paper, we propose an architecture based on a two-layer image-processing modules: General Tracking Layer (GTL) and Context Layer (CL). GTL describe a generic multipurpose tracking process for video-surveillance systems. CL is designed as a symbolic reasoning system that manages the symbolic interface data between GTL modules in order to asses a specific situation and take the appropriate decision about visual data association. Our architecture has been used to improve the association process of a tracking system and tested in two different scenarios to show the advantages in improved performance and output continuity.

Keywords

Tracking System Near Neighbor Data Association Context Data Mobile Object 
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.

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References

  1. 1.
    Patricio, M.A., Carbó, J., Pérez, O., García, J., Molina, J.M.: Multi-agent framework in visual sensor networks. EURASIP Journal on Advances in Signal Processing (2007), doi:10.1155/2007/98639Google Scholar
  2. 2.
    Kumar, P., Ranganath, S., Sengupta, K., Weimin, H.: Co-operative multi-target tracking and classification. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3021, pp. 376–389. Springer, Heidelberg (2004)Google Scholar
  3. 3.
    Pérez, Ó., Piccardi, M., García, J., Patricio, M.Á., Molina, J.M.: Comparison Between Genetic Algorithms and the Baum-Welch Algorithm in Learning HMMs for Human Activity Classification. In: Giacobini, M. (ed.) EvoWorkshops 2007. LNCS, vol. 4448, pp. 399–406. Springer, Heidelberg (2007)Google Scholar
  4. 4.
    Pérez, O., Patricio, M.A., García, J., Molina, J.M.: Improving the segmentation stage of a pedestrian tracking video-based system by means of evolution strategies. In: 8th European Workshop on Evolutionary Computation in Image Analysis and Signal Processing, EvoIASP 2006, Budapest, Hungary (April 2006)Google Scholar
  5. 5.
    Cox, I.J., Hingorani, S.L.: An efficient implementation of reid’s multiple hypothesis tracking algorithm and its evaluation for the purpose of visual tracking. IEEE Trans. Pattern Anal. Mach. Intell. 18(2), 138–150 (1996)CrossRefGoogle Scholar
  6. 6.
    Haritaoglu, I., Harwood, D., David, L.S.: W4: Real-time surveillance of people and their activities. IEEE Trans. Pattern Anal. Mach. Intell. 22(8), 809–830 (2000)CrossRefGoogle Scholar
  7. 7.
    Kim, E.Y., Park, S.H.: Automatic video segmentation using genetic algorithms. Pattern Recogn. Lett. 27(11), 1252–1265 (2006)CrossRefGoogle Scholar
  8. 8.
    Garcia, J., Molina, J.M., Besada, J.A., Portillo, J.I.: A multitarget tracking video system based on fuzzy and neuro-fuzzy techniques. EURASIP Journal on Applied Signal Processing 14, 2341–2358 (2005)CrossRefGoogle Scholar
  9. 9.
    Lienard, B., Desurmont, X., Barrie, B., Delaigle, J.: Real-time high-level video understanding using data warehouse. In: Real-Time Image Processing 2006, Valencia, España (February 2006)Google Scholar
  10. 10.
    Cucchiara, R.: Multimedia surveillance systems. In: VSSN ’05: Proceedings of the third ACM international workshop on Video surveillance & sensor networks, pp. 3–10. ACM Press, New York (2005)CrossRefGoogle Scholar

Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • A. M. Sánchez
    • 1
  • M. A. Patricio
    • 1
  • J. García
    • 1
  • J. M. Molina
    • 1
  1. 1.Universidad Carlos III de Madrid, Computer Science Department, Applied Artificial Intelligence Group, Avda. Universidad Carlos III 22, 28270 Colmenarejo (Madrid) 

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