Crowd Simulation	3
	Preface	6
	Acknowledgements	8
	Contents	9
	Chapter 1: Introduction	14
	1.1 Requirements and Constraints for Crowd Modeling	15
	1.2 Crowd Simulation Areas	16
	References	17
	Chapter 2: State-of-the-Art	21
	2.1 Crowd Dynamics	22
	2.2 Sociological Models of Crowds	22
	2.3 Crowd Simulation	23
	2.4 Behavioral Animation of Groups and Crowds	24
	2.5 Crowd Management Training Systems	27
	2.6 Group Behavior in Robotics and Arti?cial Life	28
	2.7 Environment Modeling for Crowds	28
	2.7.1 Environment Models	28
	2.7.2 Path Planning	29
	2.7.3 Collision Avoidance	31
	2.8 Crowd Rendering	32
	2.9 Crowds in Non-real-time Productions	34
	2.10 Crowds in Games	35
	2.11 Crowd Scenario Authoring	36
	References	37
	Chapter 3: Modeling of Populations	43
	3.1 Introduction	43
	3.2 Creative Methods	44
	3.3 Body Shape Capture	45
	3.4 Interpolated Techniques	46
	3.5 A Model for Generation of Population	48
	3.5.1 De?nition of the Initial Data	50
	3.5.2 Choice of a Template	50
	3.5.3 De?nition of New Somatotypes	50
	3.5.4 Calculation of In?uence of Sample Somatotypes	51
	3.5.5 Calculation of Mesh Variation	52
	3.5.6 Body Parts' Deformation	53
	3.5.7 Results and Discussion	55
	Microscopic Analysis	55
	Macroscopic Analysis	58
	3.6 Using Computer Vision to Generate Crowds	58
	3.6.1 A Model for Generating Crowds Based on Pictures	59
	Skeleton Initialization	60
	Image Segmentation	61
	Learning the Color Model	62
	Finding the Silhouette	63
	Silhouette Processing	65
	3D Pose Identi?cation	66
	Virtual Human Reconstruction	67
	3.6.2 Results	68
	3.7 Crowd Appearance Variety	69
	3.7.1 Variety at Three Levels	70
	3.7.2 Color Variety	71
	Principles of the Method	72
	HSB Color Spaces	73
	The Need for Better Color Variety	74
	Segmentation Maps	75
	Principles of Segmentation	75
	Color Variety Storage	77
	3.7.3 Accessories	78
	Simple Accessories	80
	Complex Accessories	81
	Loading and Initialization	82
	Rendering	83
	Empty Accessories	85
	Color Variety Storage	87
	Scalability	87
	3.8 Final Remarks	90
	References	90
	Chapter 4: Virtual Human Animation	93
	4.1 Introduction	93
	4.2 Related Work in Locomotion Modeling	94
	4.2.1 Kinematic Methods	94
	4.2.2 Physically Based Methods	95
	4.2.3 Motion Interpolation	96
	4.2.4 Statistical Models	98
	4.3 Principal Component Analysis	99
	4.3.1 Motion Capture Data Process	99
	4.3.2 Full-Cycle Model	100
	Input Data	100
	Main PCA	100
	4.3.3 Motion Extrapolation	102
	Second PCA Level (Sub-PCA Level 1)	103
	Third PCA Level (Sub-PCA Level 2)	104
	4.4 Walking Model	105
	4.4.1 Motion Interpolation and Extrapolation	105
	4.5 Motion Retargeting and Timewarping	107
	4.6 Motion Generation	110
	4.6.1 Speed Control	110
	4.6.2 Type of Locomotion Control	111
	4.6.3 Personi?cation Control	111
	4.6.4 Motion Transition	112
	4.6.5 Results	112
	4.7 Animation Variety	114
	4.7.1 Accessory Movements	115
	4.8 Steering	116
	4.8.1 The Need for a Fast Trajectory Control	116
	4.8.2 The Seek and Funneling Controllers	117
	4.9 Final Remarks	119
	References	119
	Chapter 5: Behavioral Animation of Crowds	123
	5.1 Introduction	123
	5.2 Related Work	123
	5.3 Crowd Behavioral Models	126
	5.3.1 PetroSim's Behavioral Model	126
	Knowledge	127
	Status	127
	Intentions and Decision Process	128
	Simplifying the FSMs	129
	An Example of FSM	129
	Results	131
	5.3.2 A Physically Based Behavioral Model	132
	Interaction with Environment	133
	Agents' Perception	134
	Agents' Decision and Action	135
	Results	137
	5.4 Crowds Navigation	138
	5.4.1 Robot Motion Planning	139
	Discrete Motion Planning	139
	Exact Motion Planning	140
	Sampling-Based Methods	140
	Reactive Methods	141
	Multiple Robots	141
	5.4.2 Crowd Motion Planning	141
	Models for Safety Applications	142
	Models for Entertainment Applications	143
	Models for Virtual Reality Applications	145
	5.4.3 A Decomposition Approach for Crowd Navigation	146
	Objectives	146
	Navigation Graphs	148
	Path Planning with Variety	150
	Scalable Simulation	152
	5.4.4 An Hybrid Architecture Based on Regions of Interest (ROI)	154
	5.5 A Collision Avoidance Method Based on the Space Colonization Algorithm	157
	5.5.1 The Crowd Model: Biocrowds	158
	Input	159
	Initialization	159
	Computation of the Motion Direction	159
	Computation of the Velocity Vector	161
	Elimination of Collision Between Finite-Sized Agents	161
	5.5.2 Experimental Results	162
	Impact of the Density of Markers	162
	The Shape of Trajectories	164
	Collision Avoidance	164
	The Stopping Effects	167
	Interactive Crowd Control	168
	5.6 Gaze Behaviors for Virtual Crowd Characters	169
	5.6.1 Simulation of Attentional Behaviors	170
	Attention Models	170
	5.6.2 Gaze Behaviors for Crowds	171
	Interest Points	171
	5.6.3 Automatic Interest Point Detection	172
	5.6.4 Motion Adaptation	173
	Spatial Resolution	174
	Temporal Resolution	175
	5.7 Final Remarks	176
	References	176
	Chapter 6: Relating Real Crowds with Virtual Crowds	181
	6.1 Introduction	181
	6.2 Studying the Motion of Real Groups of People	181
	6.2.1 Crowd Characteristics	181
	6.2.2 Crowd Events	184
	6.2.3 Parameters for Simulating Virtual Crowds Using Real Crowd Information	185
	6.2.4 Simulating Real Scenes	185
	First Sequence: People Passing Through a Door	186
	Second Sequence: People Waiting and Entering the Train	188
	6.3 Sociological Aspects	189
	6.4 Computer Vision for Crowds	191
	6.4.1 A Brief Overview on People Tracking	191
	6.5 An Approach for Crowd Simulation Using Computer Vision	193
	6.5.1 Using Computer Vision for People Tracking	194
	6.5.2 Clustering of Coherent Trajectories	196
	6.5.3 Generation of Extrapolated Velocity Fields	197
	6.5.4 Simulation Based on Real Data	198
	6.5.5 Some Examples	200
	6.6 Final Remarks	202
	References	203
	Chapter 7: Crowd Rendering	206
	7.1 Introduction	206
	7.2 Virtual Human Representations	207
	7.2.1 Human Template	207
	7.2.2 Deformable Mesh	207
	7.2.3 Rigid Mesh	209
	7.2.4 Impostor	209
	7.3 Architecture Pipeline	210
	7.3.1 Human Data Structures	212
	7.3.2 Pipeline Stages	214
	7.4 Motion Kits	222
	7.4.1 Data Structure	222
	7.4.2 Architecture	224
	7.5 Database Management	226
	7.6 Shadows	227
	7.7 Crowd Patches	229
	7.7.1 Introduction	229
	7.7.2 Patches and Patterns	230
	Patches	230
	Patterns	231
	7.7.3 Creating Patches	231
	Patterns Assembly	232
	Static Objects and Endogenous Trajectories	232
	Exogenous Trajectories: Case of Walking Humans	232
	7.7.4 Creating Worlds	233
	Assembly of Patches	233
	Patch Templates	234
	7.7.5 Applications and Results	235
	Results	236
	7.8 Final Remarks	237
	References	237
	Chapter 8: Populated Environments	239
	8.1 Introduction	239
	8.2 Terrain Modeling	240
	8.2.1 Plants and Lakes	242
	8.2.2 Sky and Clouds	243
	8.3 Generation of Virtual Environments	243
	8.4 A Model for Floor Plans Creation	245
	8.4.1 Treemaps and Squari?ed Treemaps	246
	8.4.2 The Proposed Model	248
	Including Connections Among the Rooms	249
	Including Corridors on the Floor Plans	250
	3D House Generation	252
	8.4.3 Results	253
	8.5 Informed Environment	256
	8.5.1 Data Model	259
	8.5.2 Topo Mesh	261
	8.6 Building Modeling	263
	8.7 Landing Algorithms	263
	8.8 Ontology-Based Simulation	264
	8.8.1 Using Ontology for Crowd Simulation in Normal Life Situations	266
	8.8.2 Applying Ontology to VR Environment	267
	8.8.3 The Prototype of UEM	267
	8.8.4 Simulation Results	270
	8.9 Real-Time Rendering and Visualization	271
	8.10 Implementation Aspects	273
	8.11 Final Remarks	273
	References	274
	Chapter 9: Applications: Case Studies	277
	9.1 Introduction	277
	9.2 Crowd Simulation for Virtual Heritage	277
	9.2.1 Virtual Population of Worshippers Performing Morning Namaz Prayer Inside a Virtual Mosque	278
	System Design	278
	Scenario Creation	279
	9.2.2 Virtual Roman Audience in the Aphrodisias Odeon	281
	Crowd Engine Resume	281
	High-Fidelity Actors	282
	Scenario Authoring	283
	Audience Placement	283
	9.2.3 Populating Ancient Pompeii with Crowds of Virtual Romans	284
	Semantics to Behavior	286
	Long Term vs Short Term Behaviors	287
	Results	287
	9.3 Immersion in a Crowd	288
	9.4 Crowdbrush	289
	9.4.1 Brushes	291
	Scenario Management	293
	Scripting	293
	Results	295
	9.5 Safety Systems	296
	9.6 Olympic Stadium	297
	9.7 Final Remarks	300
	References	300
	Book Contribution	302
	Index	304