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A Physically-Based Particle Model of Emergent Crowd Behaviors

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A visitor should have a feeling of this ... The red discs form a queue and the green ones jam together. ARTIS-GRAVIR / IMAG INRIA ... – PowerPoint PPT presentation

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Title: A Physically-Based Particle Model of Emergent Crowd Behaviors


1
A Physically-Based Particle Model of Emergent
Crowd Behaviors
  • Laure Heïgeas, Annie Luciani,
  • Joelle Thollot, Nicolas Castagné
  • ICA INPG
  • ARTIS-GRAVIR/IMAG INRIA

2
The agora of Argos
  • Center of the social life
  • A visitor should have a
    feeling of this
  • We need to put people
    walking around during our walkthrough session
  • CG research question how to animate a crowd and
    to render it in real time ?

3
What kind of crowd
  • We focus on collective behavior
  • One character has to avoid others and buildings
  • We try to produce some emergent behaviors flows,
    files, groups
  • We need a generative model

4
State of the art
  • Three main approaches
  • Kinematic key frames and interpolations preset
    the animation
  • Agent systems agents are managed in real time by
    rules of behavior defined with automata
  • Particle-based system particles are animated in
    real time by the application of different forces
  • Particle systems seem to be well adapted
    generative and simple, no need for special rules

5
Our methodology
  • Analysis of the dynamic of a crowd
  • Dynamic structures
  • Traffic jams
  • Flows
  • Queues
  • Obstacle avoidance
  • Distance around obstacles apparent volume
  • Distance around people psychophysical volume

6
Our methodology
  • Synthesis of the dynamic effects
  • One character one particle on a 2D ground
  • Building several particules
  • Elastic interaction, piecewise linear
  • Thresholds given by the analysis

7
Results
  • 2D visualization of the trajectories

 
Avoidance of two persons passing face to face
The red discs form a queue and the green ones jam
together
8
3D visualization
  • NPR style
  • Coherent with the style of the scene
  • Historical references for the costumes
  • Real-time rendering
  • Each character is a billboard
  • We texture it with a movie of a walking person
    20 points of view and 8 different characters

Loscos et al. 02
9
Conclusion
  • Results
  • Reproduction of complex dynamic behaviors
  • Simple interaction model between pairs of objects
  • 3D real-time visualization
  • Future works
  • Allowing the user to interact with the crowd
  • real-time simulation
  • Anisotropic model of a character front/back
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