Abstract
An extension of the re-identification method of modeling objects behavior in muti-camera surveillance systems, related to adding a particle filter to the decision-making algorithm is covered by the paper. A variety of tracking methods related to a single FOV (Field of Vision) are known, proven to be quite different for inter-camera tracking, especially in case of non-overlapping FOVs. The re-identification methods refer to the determination of the probability of a particular object’s identity recognized by a pair of cameras. An evaluation of the proposed modification of the re-identification method is presented in the paper, which is concluded with an analysis of some comparison results brought by the methods implemented with and without a particle filter employment.
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Acknowledgements
This work has been partially funded by the Polish National Science Centre within the grant belonging to the program “Preludium” No. 2014/15/N/ST6/04905 entitled:“Methods for design of the camera network topology aimed to re-identification and tracking objects on the basis of behavior modeling with the flow graph”.
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Lisowski, K., Czyżewski, A. (2019). Modelling of Objects Behaviour for Their Re-identification in Multi-camera Surveillance System Employing Particle Filters and Flow Graphs. In: Choraś, M., Choraś, R. (eds) Image Processing and Communications Challenges 10. IP&C 2018. Advances in Intelligent Systems and Computing, vol 892. Springer, Cham. https://doi.org/10.1007/978-3-030-03658-4_10
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