Abnormal crowd behavior detection using social force model

@article{Mehran2009AbnormalCB,
  title={Abnormal crowd behavior detection using social force model},
  author={Ramin Mehran and Alexis Oyama and Mubarak Shah},
  journal={2009 IEEE Conference on Computer Vision and Pattern Recognition},
  year={2009},
  pages={935-942}
}
In this paper we introduce a novel method to detect and localize abnormal behaviors in crowd videos using Social Force model. For this purpose, a grid of particles is placed over the image and it is advected with the space-time average of optical flow. By treating the moving particles as individuals, their interaction forces are estimated using social force model. The interaction force is then mapped into the image plane to obtain Force Flow for every pixel in every frame. Randomly selected… CONTINUE READING

Similar Papers

References

Publications referenced by this paper.
SHOWING 1-10 OF 33 REFERENCES

A Lagrangian Particle Dynamics Approach for Crowd Flow Segmentation and Stability Analysis

  • 2007 IEEE Conference on Computer Vision and Pattern Recognition
  • 2007
VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL

Latent Dirichlet Allocation

VIEW 15 EXCERPTS
HIGHLY INFLUENTIAL

Social force model for pedestrian dynamics.

  • Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics
  • 1995
VIEW 7 EXCERPTS
HIGHLY INFLUENTIAL

Autonomous pedestrians

  • Graphical Models
  • 2007
VIEW 2 EXCERPTS

Corpetti . Crowd motion capture

T.
  • Comput . Animat . Virtual Worlds
  • 2007