Visual crowd surveillance through a hydrodynamics lens

People in high-density crowds appear to move with the flow of the crowd, like particles in a liquid.

[1]  Helbing,et al.  Social force model for pedestrian dynamics. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[2]  A. Schadschneider,et al.  Simulation of pedestrian dynamics using a two dimensional cellular automaton , 2001 .

[3]  D. Helbing Traffic and related self-driven many-particle systems , 2000, cond-mat/0012229.

[4]  Andreas Schadschneider,et al.  Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics , 2002 .

[5]  Roger L. Hughes,et al.  A continuum theory for the flow of pedestrians , 2002 .

[6]  R. Hughes The flow of human crowds , 2003 .

[7]  Jorge S. Marques,et al.  Tracking Groups of Pedestrians in Video Sequences , 2003, 2003 Conference on Computer Vision and Pattern Recognition Workshop.

[8]  Ramakant Nevatia,et al.  Tracking multiple humans in crowded environment , 2004, CVPR 2004.

[9]  P. Reisman,et al.  Crowd detection in video sequences , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[10]  Ramakant Nevatia,et al.  Tracking multiple humans in crowded environment , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[11]  Nuno Vasconcelos,et al.  Mixtures of dynamic textures , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[12]  J. Marsden,et al.  Definition and properties of Lagrangian coherent structures from finite-time Lyapunov exponents in two-dimensional aperiodic flows , 2005 .

[13]  Seth J. Teller,et al.  Particle Video: Long-Range Motion Estimation Using Point Trajectories , 2006, Computer Vision and Pattern Recognition.

[14]  Robert B. Fisher,et al.  Modelling Crowd Scenes for Event Detection , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[15]  A. Bennett Lagrangian Fluid Dynamics: Sound waves, shear instabilities, Rossby waves and Ptolemaic vortices , 2006 .

[16]  M. Shah,et al.  Object tracking: A survey , 2006, CSUR.

[17]  Roberto Cipolla,et al.  Unsupervised Bayesian Detection of Independent Motion in Crowds , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[18]  Seth J. Teller,et al.  Particle Video: Long-Range Motion Estimation Using Point Trajectories , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[19]  Mubarak Shah,et al.  A Lagrangian Particle Dynamics Approach for Crowd Flow Segmentation and Stability Analysis , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[20]  Ting Yu,et al.  Unified Crowd Segmentation , 2008, ECCV.

[21]  Sergio A. Velastin,et al.  Crowd analysis: a survey , 2008, Machine Vision and Applications.

[22]  Mubarak Shah,et al.  Floor Fields for Tracking in High Density Crowd Scenes , 2008, ECCV.

[23]  Nuno Vasconcelos,et al.  Bayesian Poisson regression for crowd counting , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[24]  L. Kratz,et al.  Anomaly detection in extremely crowded scenes using spatio-temporal motion pattern models , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[25]  Luc Van Gool,et al.  You'll never walk alone: Modeling social behavior for multi-target tracking , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[26]  Ramin Mehran,et al.  Abnormal crowd behavior detection using social force model , 2009, CVPR.

[27]  Mubarak Shah,et al.  A Streakline Representation of Flow in Crowded Scenes , 2010, ECCV.