Virtual crowds: steps toward behavioral realism
Gespeichert in:
| Hauptverfasser: | , , , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
[San Rafael, California]
Morgan & Claypool Publishers
[2016]
|
| Schriftenreihe: | Synthesis lectures on visual computing
# 20 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis Klappentext |
| Beschreibung: | "This volume is a printed version of a work that appears in the Synthesis digital library of engineering and computer science" |
| Beschreibung: | xxi, 248 Seiten |
| ISBN: | 9781627058285 |
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Datensatz im Suchindex
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| adam_text | XI
Contents
Preface...............................................................xix
Acknowledgments.......................................................xxi
1 Introduction............................................................1
PARTI Multi-Agent Collision Avoidance ..................................5
2 Background..............................................................7
2.1 Centralized Approaches............................................7
2.2 Agent-based Approaches............................................7
2.2.1 Data-driven Approaches......................................8
2.2.2 Predictive Approaches.......................................8
2.3 Locomotion Synthesis..............................................9
2.4 Challenges and Proposed Solutions.................................9
2.4.1 Particle-based Agent Models................................10
2.4.2 Decoupling between Steering and Locomotion.................10
2.4.3 Generalization and Applicability of Data-driven Approaches.11
3 Footstep-based Navigation and Animation for Crowds.....................13
3.1 Introduction.....................................................13
3.2 Locomotion Model.................................................15
3.2.1 Inverted Pendulum Model....................................15
3.2.2 Footstep Actions...........................................16
3.2.3 Locomotion Constraints.....................................17
3.2.4 Cost Function..............................................18
3.3 Planning Algorithm...............................................19
3.4 Evaluation.......................................................20
3.4.1 Interfacing with Motion Synthesis..........................22
XU
4 Following Footstep Trajectories in Real Time....................................23
4.1 Animating from Footsteps................................................ 23
4.2 Framework Overview.......................................................24
4.3 Footstep-based Locomotion ...............................................25
4.3.1 Motion Clip Analysis..............................................25
4.3.2 Footstep and Root Trajectories....................................27
4.3.3 Online Selection..................................................27
4.3.4 Interpolation.....................................................28
4.3.5 Inverse Kinematics................................................29
4.4 Incorporating Root Movement Fidelity.....................................29
4.5 Results .................................................................33
4.5.1 Foot Placement Accuracy...........................................33
4.5.2 Performance ......................................................34
5 Context-sensitive Data-driven Crowd Simulation..................................37
5.1 Steering in Context......................................................37
5.2 Steering Contexts........................................................38
5.3 Initial Implementation...................................................39
5.3.1 Training Data Generation..........................................39
5.3.2 Oracle Algorithm..................................................41
5.3.3 Decision Trees....................................................42
5.3.4 Steering at Runtime...............................................44
5.4 Results .................................................................44
5.4.1 Classifier Accuracy...............................................44
5.4.2 Runtime...........................................................45
5.4.3 Collisions........................................................46
6 Conclusion .....................................................................49
6.1 Footstep-based Collision Avoidance.......................................49
6.2 Footstep-based Locomotion ...............................................49
6.3 Context-based Steering...................................................50
XI11
PART II Multi-agent Navigation............................................S3
7 Background................................................................55
7.1 Navigation Meshes...................................................55
7.2 Planning............................................................57
8 Navigation Meshes.........................................................59
8.1 NavMeshes from 3D Geometry: NEOGEN..................................59
8.1.1 GPU Coarse Voxelization.......................................60
8.1.2 Layer Extraction and Labeling.................................62
8.1.3 Layer Refinement..............................................63
8.1.4 NavMesh Generation............................................67
8.2 Results ............................................................69
8.3 Limitations and Discussion..........................................72
9 Multi-domain Planning in Dynamic Environments.............................75
9.1 Multi-domain Planning ............................................ 75
9.2 Overview ...........................................................76
9.3 Planning Domains....................................................77
9.3.1 Multiple Domains of Control...................................77
9.4 Problem Decomposition and Multi-domain Planning.....................79
9.4.1 Planning Tasks and Events.....................................81
9.5 Relationship between Domains........................................82
9.5.1 Domain Mapping................................................83
9.5.2 Mapping Successive Waypoints to Independent Planning Tasks....83
9.6 Results ............................................................83
9.6.1 Comparative Evaluation of Domain Relationships................83
9.6.2 Performance ..................................................85
9.6.3 Scenarios.....................................................87
10 Conclusion ...............................................................89
PART III Perception.......................................................91
11 Background................................................................93
XIV
12 Sound Propagation and Perception for Autonomous Agents.......................97
12.1 Sound Categorization and Representation ............................. 99
12.1.1 Sound Feature Selection and Categorization......................100
12.1.2 Sound Packet Representation (SPR)...............................100
12.1.3 SPR Selection for Hierarchical Cluster Analysis.................102
12.2 Sound Packet Propagation ..............................................105
12.2.1 Transmission Line Matrix Using Uniform Grids....................105
12.2.2 Pre-computation for TLM using a Quad-Tree.......................106
12.3 Sound Perception and Behaviors.........................................109
12.3.1 Effect of Sound Degradation on Perception.......................109
12.3.2 Hierarchical Sound Perception Model.............................109
12.3.3 Sound Attention and Behavior Model..............................Ill
12.4 Experiment Results.....................................................Ill
12.4.1 Applications ...................................................114
13 Multi-sense Attention for Autonomous Agents..................................117
13.1 Introduction...........................................................117
13.2 Methodology............................................................119
13.2.1 Object and Action Representations...............................119
13.2.2 Sense Preprocessing ............................................119
13.2.3 Sensing.........................................................120
13.3 Hierarchical Aggregate Clustering .....................................122
13.3.1 Environment-centric Clustering..................................122
13.3.2 Agent-centric Clustering........................................123
13.3.3 Aggregate Properties............................................126
13.4 Analysis and Results...................................................127
14 Semantics in Virtual Environments ...........................................131
14.1 Incorporating Semantics................................................131
14.1.1 Lexical Databases...............................................132
14.1.2 Modularized Smart Objects.......................................132
14.2 Semantic Generation....................................................132
14.2.1 Hierarchy Generation............................................133
14.2.2 Semantic Modularization.........................................136
14.2.3 Runtime Performance.............................................136
14.3 Limitations............................................................139
XV
15 Conclusion ..........................................................141 I
PART IV Agent-Object Interactions and Crowd
Heterogeneity..........................................143
16 Background...........................................................145
17 Parameterized Memory Models........................................ 149
17.1 Memory System..................................................150
17.1.1 Memory Representation...................................150
17.1.2 Sensory Memory..........................................151
17.1.3 Working Memory..........................................151
17.1.4 Long-term Memory........................................152
17.2 Example and Analysis...........................................153
17.3 Future Work.................................................. 156
18 Individual Differences...............................................159
18.1 Personality....................................................159
18.1.1 Personality-to-Behavior Mapping.........................160
18.1.2 User Studies on Personality.............................163
18.2 Roles and Needs................................................166
18.2.1 Approach................................................166
18.2.2 Implementation..........................................168
19 Conclusion ..........................................................173
PART V Behavior and Narrative........................................175
20 Background...........................................................177
21 An Open Source Platform for Authoring Functional Crowds..............181
21.1 ADAPT..........................................................181
21.2 Framework......................................................182
21.2.1 Full-body Character Control.............................182
XVI
21.2.2 Steering and Path-finding........................................184
21.2.3 Behavior ........................................................184
21.3 Shadows in Full-body Character Animation...............................185
21.3.1 Choreographers...................................................185
21.3.2 The Coordinator................................................ 186
21.3.3 Using Choreographers and the Coordinator.........................188
21.3.4 Example Choreographers........................................ 189
21.4 Character Behavior.........................„ ,.........................191
21.4.1 The ADAPT Character Stack ......................................191
21.4.2 Body Capabilities ............................................. 192
21.5 Character Interactions.............................................. 194
21.5.1 Characters Interacting with Each Other .........................194
21.5.2 Characters Interacting with the Environment ....................196
21.6 Results ............................................................ 196
21.6.1 Multi-actor Simulations..........................................196
21.6.2 Computational Performance...................................... 197
22 Event-centric Planning for Narrative Synthesis............. . ................ 199
22.1 Problem Domain and Formulation.........................................200
22.1.1 State Space ....................................................201
22.1.2 Action Space ....................................................202
22.1.3 Goal Specification........................................... 203
22.2 Planning in Event Space..................................................204
22.3 Runtime and Simulation ..................................................204
22.3.1 Event Loading and Dispatch .....................................204
22.3.2 Handling Dynamic World Changes...................................205
22.3.3 Intelligent Ambient Character Behavior ..........................207
22.4 Results .. 207
22.4.1 Environment Design............................................ 208
22.4.2 Object State Description ........................................208
22.4.3 Authored Events................................................ 209
22.4.4 Generated Narrative............................................ 209
22.4.5 Reacting to User Intervention....................................212
23 Conclusion .................................................................. 215
24 Epilogue ......................................................................217
XVII
Bibliography................................... ....................... ,219
Authors’ Biographies........................................................ 247
Series Editor: Brian A. Barsky, The University of California, Berkeley
Virtual Crowds
Steps Toward Behavioral Realism
Mubbasir Kapadia, Rutgers University
Nuria Pelechano, Universität Politécnica de Catalunya (UPC)
Jan Allbeck, George Mason University
Norm Badler, University of Pennsylvania
This volume presents novel computational models for representing digital humans and their inter-
actions with other virtual characters and meaningful environments. In this context, we describe ef-
ficient algorithms to animate, control, and author human-like agents having their own set of unique
capabilities, personalities, and desires. We begin with the lowest level of footstep determination to
steer agents in collision-free paths. Steering choices are controlled by navigation in complex environ-
ments, including multi-domain planning with dynamically changing situations. Virtual agents are
given perceptual capabilities analogous to those of real people, including sound perception, multi-
sense attention, and understanding of environment semantics which affect their behavior choices.
The roles and impacts of individual attributes, such as memory and personality are explored. The
animation challenges of integrating a number of simultaneous behavior and movement demands on
an agent are addressed through an open source software system. Finally, the creation of stories and
narratives with groups of agents subject to planning and environmental constraints culminates the
presentation.
|
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| series2 | Synthesis lectures on visual computing |
| spelling | Kapadia, Mubbasir 1985- Verfasser (DE-588)1112047085 aut Virtual crowds steps toward behavioral realism Mubbasir Kapadia, Nuria Pelechano, Jan Allbeck, Norm Badler [San Rafael, California] Morgan & Claypool Publishers [2016] xxi, 248 Seiten txt rdacontent n rdamedia nc rdacarrier Synthesis lectures on visual computing # 20 "This volume is a printed version of a work that appears in the Synthesis digital library of engineering and computer science" Crowds Collective behavior Intelligent agents (Computer software) Mensch-Maschine-Kommunikation (DE-588)4125909-9 gnd rswk-swf Menschenmenge (DE-588)4604994-0 gnd rswk-swf Virtuelle Realität (DE-588)4399931-1 gnd rswk-swf Navigation (DE-588)4041457-7 gnd rswk-swf Verhalten (DE-588)4062860-7 gnd rswk-swf Menschenmenge (DE-588)4604994-0 s Verhalten (DE-588)4062860-7 s Navigation (DE-588)4041457-7 s Mensch-Maschine-Kommunikation (DE-588)4125909-9 s Virtuelle Realität (DE-588)4399931-1 s DE-604 Pelechano, Nuria Verfasser aut Allbeck, Jan Verfasser (DE-588)1089523408 aut Badler, Norman I. Verfasser (DE-588)139470077 aut Erscheint auch als Online-Ausgabe 978-1-62705-829-2 Synthesis lectures on visual computing # 20 (DE-604)BV043726735 20 Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029072792&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029072792&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext |
| spellingShingle | Kapadia, Mubbasir 1985- Pelechano, Nuria Allbeck, Jan Badler, Norman I. Virtual crowds steps toward behavioral realism Synthesis lectures on visual computing Crowds Collective behavior Intelligent agents (Computer software) Mensch-Maschine-Kommunikation (DE-588)4125909-9 gnd Menschenmenge (DE-588)4604994-0 gnd Virtuelle Realität (DE-588)4399931-1 gnd Navigation (DE-588)4041457-7 gnd Verhalten (DE-588)4062860-7 gnd |
| subject_GND | (DE-588)4125909-9 (DE-588)4604994-0 (DE-588)4399931-1 (DE-588)4041457-7 (DE-588)4062860-7 |
| title | Virtual crowds steps toward behavioral realism |
| title_auth | Virtual crowds steps toward behavioral realism |
| title_exact_search | Virtual crowds steps toward behavioral realism |
| title_full | Virtual crowds steps toward behavioral realism Mubbasir Kapadia, Nuria Pelechano, Jan Allbeck, Norm Badler |
| title_fullStr | Virtual crowds steps toward behavioral realism Mubbasir Kapadia, Nuria Pelechano, Jan Allbeck, Norm Badler |
| title_full_unstemmed | Virtual crowds steps toward behavioral realism Mubbasir Kapadia, Nuria Pelechano, Jan Allbeck, Norm Badler |
| title_short | Virtual crowds |
| title_sort | virtual crowds steps toward behavioral realism |
| title_sub | steps toward behavioral realism |
| topic | Crowds Collective behavior Intelligent agents (Computer software) Mensch-Maschine-Kommunikation (DE-588)4125909-9 gnd Menschenmenge (DE-588)4604994-0 gnd Virtuelle Realität (DE-588)4399931-1 gnd Navigation (DE-588)4041457-7 gnd Verhalten (DE-588)4062860-7 gnd |
| topic_facet | Crowds Collective behavior Intelligent agents (Computer software) Mensch-Maschine-Kommunikation Menschenmenge Virtuelle Realität Navigation Verhalten |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029072792&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029072792&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV043726735 |
| work_keys_str_mv | AT kapadiamubbasir virtualcrowdsstepstowardbehavioralrealism AT pelechanonuria virtualcrowdsstepstowardbehavioralrealism AT allbeckjan virtualcrowdsstepstowardbehavioralrealism AT badlernormani virtualcrowdsstepstowardbehavioralrealism |