Virtual Crowds

Virtual Crowds
Methods, Simulation, and Control

Nuria Palechano, Norman Badler, Jan Allbeck
ISBN: 9781598296419 | PDF ISBN: 9781598296426
Copyright © 2008 | 176 Pages | Publication Date: 01/01/2008

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There are many applications of computer animation and simulation where it is necessary to model virtual crowds of autonomous agents. Some of these applications include site planning, education, entertainment, training, and human factors analysis for building evacuation. Other applications include simulations of scenarios where masses of people gather, flow, and disperse, such as transportation centers, sporting events, and concerts. Most crowd simulations include only basic locomotive behaviors possibly coupled with a few stochastic actions. Our goal in this survey is to establish a baseline of techniques and requirements for simulating large-scale virtual human populations. Sometimes, these populations might be mutually engaged in a common activity such as evacuation from a building or area; other times they may be going about their individual and personal agenda of work, play, leisure, travel, or spectator. Computational methods to model one set of requirements may not mesh well with good approaches to another. By including both crowd and individual goals and constraints into a comprehensive computational model, we expect to simulate the visual texture and contextual behaviors of groups of seemingly sentient beings.

Table of Contents: Introduction / Crowd Simulation Methodology Survey / Individual Differences in Crowds / Framework (HiDAC + MACES + CAROSA) / HiDAC: Local Motion / MACES: Wayfinding with Communication and Roles / CAROSA: Functional Crowds / Initializing a Scenario / Evaluating Crowds

Table of Contents

Introduction
Crowd Simulation Methodology Survey
Individual Differences in Crowds
Framework (HiDAC + MACES + CAROSA)
HiDAC: Local Motion
MACES: Wayfinding with Communication and Roles
CAROSA: Functional Crowds
Initializing a Scenario
Evaluating Crowds

About the Author(s)

Nuria Palechano, Universitat Polit

Norman Badler, University of Pennsylvania

Jan Allbeck, University of Pennsylvania

Related Series

Computer Vision

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