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Modeling, Simulation And Visual Analysis Of Crowds
1 Modeling, Simulation and Visual Analysis of Crowds:
A Multidisciplinary Perspective. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Saad Ali, Ko Nishino, Dinesh Manocha, and Mubarak Shah
Part I Crowd Simulation and Behavior Modeling
2 On Force-Based Modeling of Pedestrian Dynamics . . . . . . . . . . . . . . . . . . . . 23
Mohcine Chraibi, Andreas Schadschneider,
and Armin Seyfried
3 Connection Between Microscopic and Macroscopic Models . . . . . . . . . . 43
Jan-Frederik Pietschmann
4 Analysis of Crowd Dynamics with Laboratory Experiments . . . . . . . . . . 67
Maik Boltes, Jun Zhang, and Armin Seyfried
5 Modeling a Crowd of Groups: Multidisciplinary
and Methodological Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
Stefania Bandini and Giuseppe Vizzari
6 Scalable Solutions for Simulating, Animating,
and Rendering Real-Time Crowds of Diverse Virtual Humans . . . . . . . 123
Daniel Thalmann, Helena Grillon, Jonathan Maïm,
and Barbara Yersin
7 Authoring Multi-actor Behaviors in Crowds
with Diverse Personalities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
Mubbasir Kapadia, Alexander Shoulson, Funda Durupinar,
and Norman I. Badler
8 Virtual Tawaf: A Velocity-Space-Based Solution
for Simulating Heterogeneous Behavior in Dense Crowds. . . . . . . . . . . . . 181
Sean Curtis, Stephen J. Guy, Basim Zafar,
and Dinesh Manocha
vii
viii Contents
Part II Visual Analysis of Crowds
9 Crowd Flow Segmentation Using Lagrangian Particle Dynamics . . . . 213
Saad Ali and Mubarak Shah
10 Modeling Crowd Flow for Video Analysis of Crowded Scenes . . . . . . . . 237
Ko Nishino and Louis Kratz
11 Pedestrian Interaction in Tracking: The Social Force
Model and Global Optimization Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267
Laura Leal-Taixé and Bodo Rosenhahn
12 Surveillance of Crowded Environments: Modeling the
Crowd by Its Global Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 295
Antoni B. Chan and Nuno Vasconcelos
13 Inferring Leadership from Group Dynamics
Using Markov Chain Monte Carlo Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . 325
Avishy Y. Carmi, Lyudmila Mihaylova, François Septier,
Sze Kim Pang, Pini Gurfil, and Simon J. Godsill
14 Crowd Counting and Profiling: Methodology and Evaluation . . . . . . . . 347
Chen Change Loy, Ke Chen, Shaogang Gong, and Tao Xiang
15 Anomaly Detection in Crowded Scenes: A Novel
Framework Based on Swarm Optimization and Social
Force Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 383
R. Raghavendra, M. Cristani, A. Del Bue, E. Sangineto,
and V. Murino
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