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Adaptive Method of Adjusting Flowgraph for Route Reconstruction in Video Surveillance Systems

Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Pawlak's flowgraph has been applied as a suitable data structure for description and analysis of human behaviour in the area supervised with multicamera video surveillance system. Information contained in the flowgraph can be easily used to predict consecutive movements of a particular object. Moreover, utilization of the flowgraph can support reconstructing object route from the past video images. However, such a flowgraph with its accumulative nature needs a certain period of time for adaptation to changes in behaviour of objects which can be caused, e.g. by closing a door or placing other obstacle forcing people to pass it by. In this paper a method for reduction of time needed for flowgraph adaptation is presented. Additionally, distance measure between flowgraphs is also introduced in order to determine if carrying out the adaptation process is needed.
Wydawca
Rocznik
Strony
561--576
Opis fizyczny
Bibliogr. 35 poz., rys., wykr.
Twórcy
  • Multimedia Systems Department, Gdańsk University of Technology, Poland
autor
  • Multimedia Systems Department, Gdańsk University of Technology, Poland
Bibliografia
  • [1] Allen, R., Mcgeorge, P., Pearson, D., Milne, A. B.: Attention and expertise in multiple target tracking, Applied Cognitive Psychology, 2004.
  • [2] Butz, C. J., Yan, W., Yang, B.: An Efficient Algorithm for Inference in Rough Set Flow Graphs.
  • [3] Cai, Y., Chen, W., Huang, K., T.Tan: Continuously Tracking Objects Across Multiple Widely Separated Cameras, ACCV2007, II, 2007.
  • [4] Cavanagh, P., Alvarez, G.: Tracking multiple targets with multifocal attention, TRENDS in Cognitive Sciences, 2005.
  • [5] Colombo, A., Orwell, J., Velastin, S.: Colour Constancy Techniques for Re-Recognition of Pedestrians from Multiple Surveillance Cameras, Workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications, 2008.
  • [6] Czyżewski, A., Kostek, B.: Musical Metadata Retrieval with Flow Graphs, in: Rough Sets and Current Trends in Computing (S. Tsumoto, R. Słowiński, J. Komorowski, J. Grzymała-Busse, Eds.), vol. 3066 of Lecture Notes in Computer Science, Springer Berlin / Heidelberg, 2004, ISBN 978-3-540-22117-3, 691698, 10.1007/978-3-540-25929-9_87.
  • [7] Dalka, P., Szwoch, G., Szczuko, P., Czyżewski, A.: Video Content Analysis in the Urban Area Telemonitoring System, Multimedia Services in Inteligent Environments, Springer-Verlag Berlin Heidelberg, 2010.
  • [8] Dunin-Keplicz, B., Jankowski, A., Skowron, A., Szczuka, M., Pawlak, Z.: Flow Graphs, their Fusion and Data Analysis, in: Monitoring, Security, and Rescue Techniques in Multiagent Systems, vol. 28 of Advances in Soft Computing, Springer Berlin / Heidelberg, 2005, ISBN 978-3-540-23245-2, 3-12, 10.1007/3-540- 32370-8_l.
  • [9] Gilbert, A., Bowden, R.: Tracking objects across cameras by incrementally learning inter-camera colour calibration and patterns of activity, 9th European Conference on Computer Vision (ICCV 2006), 2006.
  • [10] Greco, S., Pawlak, Z., Słowinski, R.: Generalized Decision Algorithms, Rough Inference Rules, and Flow Graphs, in: Rough Sets and Current Trends in Computing (J. Alpigini, J. Peters, A. Skowron, N. Zhong, Eds.), vol. 2475 of Lecture Notes in Computer Science, Springer Berlin / Heidelberg, 2002, ISBN 978-3540-44274-5, 951-951, 10.1007/3-540-45813-l_12.
  • [11] Javed, O.: Appearance Modeling for Tracking in Multiple Non-overlapping Cameras, IEEE International Conference on Computer Vision and Pattern Recognition, 2005.
  • [12] Kostek, B.: Perception-Based Data Processing in Acoustics: Applications to Music Information Retrieval and Psychophysiology of Hearing, 1st edition, Springer Publishing Company, Incorporated, 2010, ISBN 3642065147, 9783642065149.
  • [13] Kostek, B., Czyzewski, A.: Processing of Musical Metadata Employing Pawlaks Flow Graphs, in: Transactions on Rough Sets I (J. Peters, A. Skowron, J. Grzymała-Busse, B. Kostek, R. Swiniarski, M. Szczuka, Eds.), vol. 3100 of Lecture Notes in Computer Science, Springer Berlin / Heidelberg, 2004, ISBN 978-3540-22374-0, 279-298.
  • [14] Kotus, J., Łopatka, K., Czyzewski, A.: Detection and localization of selected acoustic events in acoustic field for smart surveillance applications, Multimedia Tools and Applications, 2012, 1-17, ISSN 1380-7501.
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  • [16] Lane, N., Xu, Y., Lu, H., Campbell, A., Choudhury, T., Eisenman, S.: Exploiting Social Networks for Large- Scale Human Behavior Modeling, Pervasive Computing, IEEE, 10(4), 2011, 45-53, ISSN 1536-1268.
  • [17] Liu, H., Sun, J., Zhang, H.: Interpretation of Extended Pawlak Flow Graphs Using Granular Computing, in: Transactions on Rough Sets VIII (J. F. Peters, A. Skowron, Eds.), vol. 5084 of Lecture Notes in Computer Science, Springer Berlin Heidelberg, 2008, ISBN 978-3-540-85063-2,93-115.
  • [18] Matsumoto, M., Nishimura, T.: Mersenne twister: a 623-dimensionally equidistributed uniform pseudorandom number generator, ACM Trans. Model. Comput. Simul., 8(1), January 1998, 3-30, ISSN 1049-3301.
  • [19] Matusiewicz, Z., Pancerz, K.: Rough Set Flow Graphs and Max - * Fuzzy Relation Equations in State Prediction Problems, in: Rough Sets and Current Trends in Computing (C.-C. Chan, J. Grzymała-Busse, W. Ziarko, Eds.), vol. 5306 of Lecture Notes in Computer Science, Springer Berlin / Heidelberg, 2008, ISBN 978-3-540-88423-1,359-368, 10.1007/978-3-540-88425-5_37.
  • [20] Nguyen, H. S., Skowron, A., Szczuka, M. S.: Situation Identification by Unmanned Aerial Vehicle, Revised Papers from the Second International Conference on Rough Sets and Current Trends in Computing, RSCTC ’00, Springer-Verlag, London, UK, UK, 2001, ISBN 3-540-43074-1.
  • [21] Pawlak, Z.: The Rough Set View on Bayes Theorem, in: Advances in Soft Computing AFSS 2002 (N. Pal, M. Sugeno, Eds.), vol. 2275 of Lecture Notes in Computer Science, Springer Berlin Heidelberg, 2002, ISBN 978-3-540-43150-3,106-116.
  • [22] Pawlak, Z.: Flow Graphs and Data Mining, in: Transactions on Rough Sets III (J. Peters, A. Skowron, Eds.), vol. 3400 of Lecture Notes in Computer Science, Springer Berlin / Heidelberg, 2005, ISBN 978-3540-25998-5,1-36, 10.1007/11427834_1.
  • [23] Pawlak, Z.: Some remarks on conflict analysis, European Journal of Operational Research, 166(3), 2005, 649 - 654, ISSN 0377-2217, Advances in Complex Systems Modeling.
  • [24] Pawlak, Z.: Conflicts and negotations, Proceedings of the First international conference on Rough Sets and Knowledge Technology, RSKT’06, Springer-Verlag, Berlin, Heidelberg, 2006, ISBN 3-540-36297-5, 978-3-540-36297-5.
  • [25] Pawlak, Z.: Decision Trees and Flow Graphs, in: Rough Sets and Current Trends in Computing (S. Greco, Y. Hata, S. Hirano, M. Inuiguchi, S. Miyamoto, H. Nguyen, R. Slowinski, Eds.), vol. 4259 of Lecture Notes in Computer Science, Springer Berlin / Heidelberg, 2006, ISBN 978-3-540-47693-1, 1-11, 10.1007/11908029_1.
  • [26] Pentland, A., Liu, A.: Modeling and prediction of human behavior, Neural Comput., 11(1), January 1999, 229-242, ISSN 0899-7667.
  • [27] Sadilek, A.: Modeling Human Behavior at a Large Scale, Ph.D. Thesis, University of Rochester, 2012.
  • [28] Stinson, D.: Cryptography: Theory and Practice, Second Edition, 2nd edition, CRC/C&H, 2002, ISBN 1584882069.
  • [29] Sun, J., Liu, H., Zhang, H.: An Extension of Pawlaks Flow Graphs, in: Rough Sets and Knowledge Technology (G.-Y. Wang, J. Peters, A. Skowron, Y. Yao, Eds.), vol. 4062 of Lecture Notes in Computer Science, Springer Berlin/Heidelberg, 2006, ISBN 978-3-540-36297-5,191-199, 10.1007/117951308.
  • [30] Szwoch, G.: Performance Evaluation of the Parallel Codebook Algorithm for Background Subtraction in Video Stream, 4th International Conference Multimedia Communications, Services and Security (MCSS), 2011.
  • [31] Szwoch, G., Dalka, P.: Automatic Detection of Abandoned Luggage Employing a Dual Camera System, MCSS 2010: IEEE International Conference on Multimedia Communications, Services and Security, 2010.
  • [32] Szwoch, G., Dalka, P., Czyzewski, A.: Objects classification based on their physical sizes for detection of events in camera images, NTAV/SPA 2008 Signal Processing: Algorithms, Architectures, Arrangements, and Applications; New Trends in Audio and Video, 2008.
  • [33] Szwoch, G., Dalka, P., Czyzewski, A.: Resolving conflicts in object tracking for automatic detection of events in video, Elektronika, 2011.
  • [34] Szwoch, G., Ellwart, D., Czyzewski, A.: Parallel implementation of background subtraction algorithms for real-time video processing on a supercomputer platform, Journal of Real-Time Image Processing, 2012, 1-15, ISSN 1861-8200.
  • [35] Ziebart, B. D., Maas, A., Bagnell, J. A., Dey, A. K.: Human Behavior Modeling with Maximum Entropy Inverse Optimal Control, 2009.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-7fbea05a-3574-4e79-9968-c2f4f6677fcf
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