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Abnormal Prediction of Dense Crowd Videos by a Purpose–Driven Lattice Boltzmann Model

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Adam, A., Rivlin, E., Shimshoni, I. and Reinitz, D. (2008). Robust real-time unusual event detection using multiple fixed-location monitors, IEEE Transactions on Pattern Analysis and Machine Intelligence30(3): 555–560.10.1109/TPAMI.2007.7082518195449Search in Google Scholar

Ahlquist, J.S. and Breunig, C. (2012). Model-based clustering and typologies in the social sciences, Political Analysis20(1): 92–112.10.1093/pan/mpr039Search in Google Scholar

Al-nasur, S.J. (2006). New Models for Crowd Dynamics and Control, PhD thesis, Virginia Polytechnic Institute and State University, Blacksburg, VA.Search in Google Scholar

Alahi, A., Ramanathan, V. and Fei-Fei, L. (2014). Socially-aware large-scale crowd forecasting, 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, OH, USA, pp. 2211–2218.Search in Google Scholar

Ali, S. and Shah, M. (2007). A Lagrangian particle dynamics approach for crowd flow segmentation and stability analysis, 2007 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Minneapolis, MN, USA, pp. 1–6.Search in Google Scholar

Baker, S., Scharstein, D., Lewis, J.P., Roth, S., Black, M.J. and Szeliski, R. (2011). A database and evaluation methodology for optical flow, International Journal of Computer Vision92(1): 1–31.10.1007/s11263-010-0390-2Search in Google Scholar

Bhatnagar, P.L., Gross, E.P. and Krook, M. (1954). A model for collision processes in gases. I: Small amplitude processes in charged and neutral one-component systems, Physical Review94(3): 511–525.Search in Google Scholar

Cao, T., Wu, X., Guo, J., Yu, S. and Xu, Y. (2009). Abnormal crowd motion analysis, 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO), Guilin, China, pp. 1709–1714.Search in Google Scholar

Chan, A.B. and Vasconcelos, N. (2008). Modeling, clustering, and segmenting video with mixtures of dynamic textures, IEEE Transactions on Pattern Analysis and Machine Intelligence30(5): 909–926.10.1109/TPAMI.2007.7073818369258Search in Google Scholar

Chetverikov, D. and Péteri, R. (2005). A brief survey of dynamic texture description and recognition, in M. Kurzyński et al. (Eds.), Computer Recognition Systems, Advances in Soft Computing, Vol. 30, Springer, Berlin/Heidelberg, pp. 17–26.10.1007/3-540-32390-2_2Search in Google Scholar

Cong, Y., Yuan, J. and Liu, J. (2011). Sparse reconstruction cost for abnormal event detection, 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Colorado Springs, CO, USA, pp. 3449–3456.Search in Google Scholar

Cong, Y., Yuan, J. and Liu, J. (2013). Abnormal event detection in crowded scenes using sparse representation, Pattern Recognition46(7): 1851–1864.10.1016/j.patcog.2012.11.021Search in Google Scholar

Dębski, R. (2014). High-performance simulation-based algorithms for an alpine ski racer’s trajectory optimization in heterogeneous computer systems, International Journal of Applied Mathematics and Computer Science24(3): 551–566, DOI: 10.2478/amcs-2014-0040.10.2478/amcs-2014-0040Search in Google Scholar

Dębski, R. (2016). An adaptive multi-spline refinement algorithm in simulation based sailboat trajectory optimization using onboard multi-core computer systems, International Journal of Applied Mathematics and Computer Science26(2): 351–365, DOI: 10.1515/amcs-2016-0025.10.1515/amcs-2016-0025Search in Google Scholar

Dollár, P., Appel, R., Belongie, S. and Perona, P. (2014). Fast feature pyramids for object detection, IEEE Transactions on Pattern Analysis and Machine Intelligence36(8): 1532–1545.10.1109/TPAMI.2014.230047926353336Search in Google Scholar

Jiang, Y.-Q., Zhang, P., Wong, S.C. and Liu, R.-X. (2010). A higher-order macroscopic model for pedestrian flows, Physica A: Statistical Mechanics and Its Applications389(21): 4623–4635.10.1016/j.physa.2010.05.003Search in Google Scholar

Johansson, A., Helbing, D., Al-Abideen, H.Z. and Al-Bosta, S. (2008). From crowd dynamics to crowd safety: A video-based analysis, Advances in Complex Systems11(04): 497–527.10.1142/S0219525908001854Search in Google Scholar

Kowalski, M., Kaczmarek, P., Kabaciński, R., Matuszczak, M., Tranbowicz, K. and Sobkowiak, R. (2014). A simultaneous localization and tracking method for a worm tracking system, International Journal of Applied Mathematics and Computer Science24(3): 599–609, DOI: 10.2478/amcs-2014-0043.10.2478/amcs-2014-0043Search in Google Scholar

Lee, B.H., Koo, Y.-H., Oh, J.Y., Cheon, J.S., Tahk, Y.-W. and Sohn, D.-S. (2011). Fuel performance code cosmos for analysis of LWR UO2 and MOX fuel, Nuclear Engineering and Technology43(6): 499–508.10.5516/NET.2011.43.6.499Search in Google Scholar

Li, W., Mahadevan, V. and Vasconcelos, N. (2014). Anomaly detection and localization in crowded scenes, IEEE Transactions on Pattern Analysis and Machine Intelligence36(1): 18–32.10.1109/TPAMI.2013.11124231863Search in Google Scholar

Mandl, F. (2008). Statistical Physics, 2nd Edition, Manchester Physics, Hoboken, NJ.Search in Google Scholar

Mathiassen, J.R. and Skavhaug, A. (2002). Texture similarity measure using Kullback–Leibler divergence between gamma distributions, ECCV 2002: 7th European Conference on Computer Vision, Copenhagen, Denmark, Part III, pp. 133–147.Search in Google Scholar

McNamara, G.R. and Zanetti, G. (1988). Use of the Boltzmann equation to simulate lattice-gas automata, Physical Review Letters61(20): 2332.10.1103/PhysRevLett.61.233210039085Search in Google Scholar

Mehran, R., Oyama, A. and Shah, M. (2009). Abnormal crowd behavior detection using social force model, 2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Miami, FL, USA, pp. 935–942.Search in Google Scholar

Mészáros, A., Papp, J. and Telek, M. (2014). Fitting traffic traces with discrete canonical phase type distributions and Markov arrival processes, International Journal of Applied Mathematics and Computer Science24(3): 453–470, DOI: 10.2478/amcs-2014-0034.10.2478/amcs-2014-0034Search in Google Scholar

Raghavendra, R., Bue, A.D., Cristani, M. and Murino, V. (2011a). Optimizing interaction force for global anomaly detection in crowded scenes, 2011 IEEE International Conference on Computer Vision Workshops, Barcelona, Spain, pp. 136–143.10.1109/ICCVW.2011.6130235Search in Google Scholar

Raghavendra, R., Bue, A., Cristani, M. and Murino, V. (2011b). Abnormal crowd behavior detection by social force optimization, in A.A. Salah and B. Lepri (Eds.), Human Behavior Understanding: Second International Workshop, HBU 2011, Springer, Berlin/Heidelberg, pp. 134–145.10.1007/978-3-642-25446-8_15Search in Google Scholar

Rodriguez, M., Laptev, I., Sivic, J. and Audibert, J.Y. (2011). Density-aware person detection and tracking in crowds, 2011 International Conference on Computer Vision, Barcelona, Spain, pp. 2423–2430.Search in Google Scholar

Rowlinson, J.S. (2005). The Maxwell–Boltzmann distribution, Molecular Physics103(21–23): 2821–2828.10.1080/002068970500044749Search in Google Scholar

Silveira Jacques Jr., J.C., Raupp Musse, S. and Rosito Jung, C. (2010). Crowd analysis using computer vision techniques, IEEE Signal Processing Magazine27(5): 66–77.10.1109/MSP.2010.937394Search in Google Scholar

Solmaz, B., Moore, B.E. and Shah, M. (2012). Identifying behaviors in crowd scenes using stability analysis for dynamical systems, IEEE Transactions on Pattern Analysis and Machine Intelligence34(10): 2064–2070.10.1109/TPAMI.2012.12322641705Search in Google Scholar

Still, G.K. (2000). Crowd Dynamics, PhD thesis, University of Warwick, Coventry.Search in Google Scholar

Wang, B., Ye, M., Li, X., Zhao, F. and Ding, J. (2012). Abnormal crowd behavior detection using high-frequency and spatio-temporal features, Machine Vision and Applications23(3): 501–511.10.1007/s00138-011-0341-0Search in Google Scholar

Wang, Z., Bovik, A.C., Sheikh, H.R. and Simoncelli, E.P. (2004). Image quality assessment: From error visibility to structural similarity, IEEE Transactions on Image Processing13(4): 600–612.10.1109/TIP.2003.819861Search in Google Scholar

Wolf-Gladrow, D. (2000). Lattice-Gas Cellular Automata and Lattice Boltzmann Models—An Introduction, Lecture Notes in Mathematics, Vol. 1725, Springer, Berlin.Search in Google Scholar

Wu, S., Moore, B.E. and Shah, M. (2010). Chaotic invariants of lagrangian particle trajectories for anomaly detection in crowded scenes, 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), San Francisco, CA, USA, pp. 2054–2060.Search in Google Scholar

Xiong, G., Cheng, J., Wu, X., Chen, Y.-L., Ou, Y. and Xu, Y. (2012). An energy model approach to people counting for abnormal crowd behavior detection, Neurocomputing83: 121–135.10.1016/j.neucom.2011.12.007Search in Google Scholar

Xiong, G., Wu, X., Chen, Y.L. and Ou, Y. (2011). Abnormal crowd behavior detection based on the energy model, 2011 IEEE International Conference on Information and Automation (ICIA), Shenzhen, China, pp. 495–500.Search in Google Scholar

eISSN:
2083-8492
Langue:
Anglais
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Sujets de la revue:
Mathematics, Applied Mathematics