Abstract
The idea of Pawlak’s flowgraph turned out to be a useful and convenient container for a knowledge of objects’ behaviour and movements within the area observed with a multi-camera surveillance system. Utilization of the flowgraph for modelling behaviour admittedly requires certain extensions and enhancements, but it allows for combining many rules into a one data structure and for obtaining parameters describing how objects tend to move through the supervised area. The main aim of this article is presentation of the complexity analysis of proposed modification of flowgraphs. This analysis contains considerations of issues such as memory efficiency and computational complexity of operations on the flowgraph. The measures related to space and time efficiency were also included.
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References
Cormen T (2009) Introduction to algorithms. MIT Press, Cambridge. Mass
Czyzewski A, Lisowski K (2013) Adaptive method of adjusting flowgraph for route reconstruction in video surveillance systems. Fundam Inf 127(1–4):561–576. doi:10.3233/FI-2013-927
Czyzewski A, Lisowski K (2013) Employing flowgraphs for forward route reconstruction in video surveillance system. Journal of Intelligent Information Systems:1–15. doi:10.1007/s10844-013-0253-8
Ellwart D, Czyewski A (2013) Visual objects description for their re-identification in multi-camera systems. In: Zgrzywa A, Choro K, Siemiski A (eds) Multimedia and Internet Systems: Theory and Practice, Advances in Intelligent Systems and Computing, vol 183, pp 45–54. Springer, Berlin. doi:10.1007/978-3-642-32335-5_5
Greco S, Pawlak Z, Slowinski R (2002) Generalized decision algorithms, rough inference rules, and flow graphs. In: Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing, TSCTC ’02, pp 93–104. Springer, London. http://dl.acm.org/citation.cfm?id=646473.693145
Hongeng S, Bremond F, Nevatia R (2000) Bayesian framework for video surveillance application. In: Proceedings of the 15th International Conference on Pattern Recognition 2000, vol 1, pp 164–170. doi:10.1109/ICPR.2000.905296, (to appear in print)
Javed O, Shafique K, Shah M (2005) Appearance modeling for tracking in multiple non-overlapping cameras. In: 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, vol 2, pp 26–33. doi:10.1109/CVPR.2005.71, (to appear in print)
Kim H, Romberg J, Wolf W (2009) Multi-camera tracking on a graph using markov chain monte carlo. In: 2009 Third ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC 2009, pp 1–8. doi:10.1109/ICDSC.2009.5289352, (to appear in print)
Kubale M (1998) Introduction to computational complexity and algorithmic graph coloring. Gdanskie Towarzystwo Naukowe, Gdansk
Leung V, Orwell J, Velastin S (2008) Performance evaluation of re-acquisition methods for public transport surveillance. In: 2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008, pp 705–712. doi:10.1109/ICARCV.2008.4795604, (to appear in print)
Lev-Tov A, Moses Y (2010) Path recovery of a disappearing target in a large network of cameras. In: Proceedings of the Fourth ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC ’10, pp 57–64. ACM, New York. doi:10.1145/1865987.1865997, (to appear in print)
Pawlak Z (2003) Flow graphs and decision algorithms. In: Wang G, Liu Q, Yao Y, Skowron A (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, Lecture Notes in Computer Science, vol 2639, pp 1–10. Springer, Berlin
Pawlak Z (2003) Rough sets, bayes’ theorem and flow graphs. In: Intelligent Systems for Information Processing, pp 243–252. Elsevier. doi:10.1016/b978-044451379-3/50020-0, (to appear in print)
Siek J (2002) The boost graph library : user guide and reference manual. Addison-Wesley, Boston
Wang Y, Velipasalar S, Gursoy M (2011) Wide-area multi-object tracking with non-overlapping camera views. In: 2011 IEEE International Conference on Multimedia and Expo (ICME), pp 1–6. doi:10.1109/ICME.2011.6012163, (to appear in print)
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This work has been partially funded by the Artemis JU and by the Polish National Centre for Research and Development (NCBR) as part of the COPCAMS project (http://copcams.eu) under GA number 332913.
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Lisowski, K., Czyzewski, A. Complexity analysis of the Pawlak’s flowgraph extension for re-identification in multi-camera surveillance system. Multimed Tools Appl 75, 10495–10511 (2016). https://doi.org/10.1007/s11042-015-2652-z
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DOI: https://doi.org/10.1007/s11042-015-2652-z