A Streakline Representation of Flow in Crowded Scenes

@inproceedings{Mehran2010ASR,
  title={A Streakline Representation of Flow in Crowded Scenes},
  author={Ramin Mehran and Brian E. Moore and Mubarak Shah},
  booktitle={ECCV},
  year={2010}
}
Based on the Lagrangian framework for fluid dynamics, a streakline representation of flow is presented to solve computer vision problems involving crowd and traffic flow. Streaklines are traced in a fluid flow by injecting color material, such as smoke or dye, which is transported with the flow and used for visualization. In the context of computer vision, streaklines may be used in a similar way to transport information about a scene, and they are obtained by repeatedly initializing a fixed… CONTINUE READING
BETA

Figures, Tables, and Topics from this paper.

Citations

Publications citing this paper.
SHOWING 1-10 OF 123 CITATIONS, ESTIMATED 33% COVERAGE

Crowd motion segmentation via streak flow and collectiveness

  • 2017 Chinese Automation Congress (CAC)
  • 2017
VIEW 8 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Support Vector Motion Clustering

  • IEEE Transactions on Circuits and Systems for Video Technology
  • 2017
VIEW 7 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

A comparative study of representations for folk dances recognition in video

  • 2016 24th European Signal Processing Conference (EUSIPCO)
  • 2016
VIEW 4 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Group activity recognition on outdoor scenes

  • 2016 13th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)
  • 2016
VIEW 4 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Grouping multi-vector streaklines for human activity identification

  • 2016 IEEE 12th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP)
  • 2016
VIEW 7 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

High-density crowd behaviors segmentation based on dynamical systems

  • Multimedia Systems
  • 2016
VIEW 6 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

Human and group activity recognition from video sequences

VIEW 7 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Human group activity recognition based on modelling moving regions interdependencies

  • 2016 23rd International Conference on Pattern Recognition (ICPR)
  • 2016
VIEW 5 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Long-range trajectories from global and local motion representations

  • J. Visual Communication and Image Representation
  • 2016
VIEW 10 EXCERPTS
CITES METHODS, BACKGROUND & RESULTS
HIGHLY INFLUENCED

FILTER CITATIONS BY YEAR

2010
2019

CITATION STATISTICS

  • 28 Highly Influenced Citations

  • Averaged 17 Citations per year over the last 3 years

References

Publications referenced by this paper.
SHOWING 1-10 OF 21 REFERENCES

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

  • 2007 IEEE Conference on Computer Vision and Pattern Recognition
  • 2007
VIEW 7 EXCERPTS
HIGHLY INFLUENTIAL

Scene understanding by statistical modeling of motion patterns

  • 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
  • 2010
VIEW 1 EXCERPT

Crowd event recognition using HOG tracker

  • 2009 Twelfth IEEE International Workshop on Performance Evaluation of Tracking and Surveillance
  • 2009
VIEW 1 EXCERPT

Event Detection in Crowded Videos

  • 2007 IEEE 11th International Conference on Computer Vision
  • 2007
VIEW 1 EXCERPT

Towards Robust Pedestrian Detection in Crowded Image Sequences

  • 2007 IEEE Conference on Computer Vision and Pattern Recognition
  • 2007
VIEW 1 EXCERPT

Similar Papers

Loading similar papers…