Simulating Heterogeneous Crowds with Interactive Behaviors

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ACM Trans
Affine Sequencing
agent-based modelling
behavioural animation
Cage Deformation
Category=UGN
Cell Decomposition
Cellular Automata
Crowd Simulation
Cube Map
Displacement Vector
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
evacuation simulation
Fragment Shader
Geometry Caches
Heterogeneous Crowds
Host Element
Local Clearance
Medial Axis
Motion Blending
Motion Paths
multi-agent systems
Obb
Orca
Pareto Front
Pareto Optimal Front
Pareto Optimality
pedestrian dynamics
quantitative crowd behaviour analysis
Scenario Space
Social Force Model
Spatial Occupancy
Steering Algorithms
virtual environment design

Product details

  • ISBN 9781498730365
  • Weight: 816g
  • Dimensions: 178 x 254mm
  • Publication Date: 27 Sep 2016
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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This book provides a deep understanding of state-of-art methods for simulation of heterogeneous crowds in computer graphics. It will cover different aspects that are necessary to achieve plausible crowd behaviors. The book will be a review of the most recent literature in this field that can help professionals and graduate students interested in this field to get up to date with the latest contributions, and open problems for their possible future research. The chapter contributors are well known researchers and practitioners in the field and they include their latest contributions in the different topics required to achieve believable heterogeneous crowd simulation.

    • Provides crowd simulation methodology to populate virtual environments, for video games or any kind of applications that requires believable multi-agent behavior
    • Presents the latest contributions on crowd simulation, animation, planning, rendering and evaluation with detailed algorithms for implementation purposes
    • Includes perspectives of both academic researchers and industrial practitioners with reference to open source solutions and commercial applications, where appropriate

Nuria Pelechano, Universitat Politècnica de Catalunya

Jan M. Allbeck, George Mason University

Mubbasir Kapadia, Disney Research Zurich / Rutgers University

Norman I. Badler, University of Pennsylvania