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

Research into the methods and techniques used in simulating crowds has developed extensively within the last few years, particularly in the areas of video games and film. Despite recent impressive results when simulating and rendering thousands of individuals, many challenges still exist in this area. The comparison of simulation with reality, the realistic appearance of virtual humans and their behavior, group structure and their motion, and collision avoidance are just some examples of these challenges. For most of the applications of crowds, it is now a requirement to have real-time simulations – which is an additional challenge, particularly when crowds are very large. Crowd Simulation analyses these challenges in depth and suggests many possible solutions. Daniel Thalmann and Soraia Musse share their experiences and expertise in the application of: · Population modeling · Virtual human animation · Behavioral models for crowds · The connection between virtual and real crowds · Path planning and navigation · Visual attention models · Geometric and populated semantic environments · Crowd rendering The second edition presents techniques and methods developed since the authors first covered the simulation of crowds in 2007. Crowd Simulation includes in-depth discussions on the techniques of path planning, including a new hybrid approach between navigation graphs and potential-based methods. The importance of gaze attention – individuals appearing conscious of their environment and of others – is introduced, and a free-of-collision method for crowds is also discussed.

Over the last several years there has been a growing interest in developing computational methodologies for modeling and analyzing movements and behaviors of ‘crowds' of people. This interest spans several scientific areas that includes Computer Vision, Computer Graphics, and Pedestrian Evacuation Dynamics. Despite the fact that these different scientific fields are trying to model the same physical entity (i.e. a crowd of people), research ideas have evolved independently. As a result each discipline has developed techniques and perspectives that are characteristically their own. The goal of this book is to provide the readers a comprehensive map towards the common goal of better analyzing and synthesizing the pedestrian movement in dense, heterogeneous crowds. The book is organized into different parts that consolidate various aspects of research towards this common goal, namely the modeling, simulation, and visual analysis of crowds. Through this book, readers will see the common ideas and vision as well as the different challenges and techniques, that will stimulate novel approaches to fully grasping “crowds."

This book describes, from a computer science viewpoint the software, methods of simulating and analysing crowds with a particular focus on the effects of panic in emergency situations. The power of modern technology impacts on modern life in multiple ways every day. A variety of scientific models and computational tools have been developed to improve human safety and comfort in built environments. In particular, understanding pedestrian behaviours during egress situations is of considerable importance in such contexts. Moreover, some places are built for large numbers of people (such as train stations and airports and high volume special activities such as sporting events). Simulating Crowds in Egress Scenarios discusses the use of computational crowd simulation to reproduce and evaluate egress performance in specific scenarios. Several case studies are included, evaluating the work and different analyses, and comparisons of simulation data versus data obtained from real-life experiments are given.

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

This volume describes frontiers in social-behavioral modeling for contexts as diverse as national security, health, and on-line social gaming. Recent scientific and technological advances have created exciting opportunities for such improvements. However, the book also identifies crucial scientific, ethical, and cultural challenges to be met if social-behavioral modeling is to achieve its potential. Doing so will require new methods, data sources, and technology. The volume discusses these, including those needed to achieve and maintain high standards of ethics and privacy. The result should be a new generation of modeling that will advance science and, separately, aid decision-making on major social and security-related subjects despite the myriad uncertainties and complexities of social phenomena. Intended to be relatively comprehensive in scope, the volume balances theory-driven, data-driven, and hybrid approaches. The latter may be rapidly iterative, as when artificial-intelligence methods are coupled with theory-driven insights to build models that are sound, comprehensible and usable in new situations. With the intent of being a milestone document that sketches a research agenda for the next decade, the volume draws on the wisdom, ideas and suggestions of many noted researchers who draw in turn from anthropology, communications, complexity science, computer science, defense planning, economics, engineering, health systems, medicine, neuroscience, physics, political science, psychology, public policy and sociology. In brief, the volume discusses: Cutting-edge challenges and opportunities in modeling for social and behavioral science Special requirements for achieving high standards of privacy and ethics New approaches for developing theory while exploiting both empirical and computational data Issues of reproducibility, communication, explanation, and validation Special requirements for models intended to inform decision making about complex social systems