Handbook of Multimedia for Digital Entertainment and Arts (eBook)

The list of contributors includes:Jakob Abesser, Fraunhofer Institute, Ilmenau, GermanyHarry Agius, Brunel University, Uxbridge, United KingdomDewan Tanvir Ahmed, University of Ottawa, Ottawa, CanadaSalah Uddin Ahmed, Norwegian University of Science and Technology, NorwayMarios Angelides, Brunel University, Uxbridge, United KingdomLora Aroyo, Eindhoven University of Technology, Eindhoven, The NetherlandsShumeet Baluja, Google, Mountain View, CA, USAPieter Bellekens, Eindhoven University of Technology, Eindhoven, The NetherlandsOliver Bimber, Bauhaus University, Weimar, Germany Leslie Bishko, Emily Carr University, Vancouver, CanadaAlan Bovik, University of Texas at Austin, Austin, Texas, USAKarlheinz Brandenburg, Fraunhofer Institute, Ilmenau, GermanyPedro Sergio Branco, University of Minho, Guimaraes, PortugalAnthony Brooks, Aalborg University, Esbjerg, DenmarkSiwoo Byun, Anyang University, Anyang, KoreaYiwei Cao, Technical University of Aachen, Aachen, GermanyCristoforo Camerano, University of Catania, ItalyPetros Caravelas, Athens University of Economics and Business, Athens, GreeceMatina Charami, Athens University of Economics and Business, Athens, GreeceMichele Covell, Google, Mountain View, CA, USAChristian Dittmar, Fraunhofer Institute, Ilmenau, GermanyPeter Dunker, Fraunhofer Institute, Ilmenau, GermanyMagy Seif El-Nasr, Simon Fraser University, Vancouver, CanadaStefano Ferretti, University of Bologna, Bologna, ItalyMichael Fink, The Hebrew University of Jerusalem, IsraelJenneke Fokker, Delft University of Technology, Delft, The NetherlandsLuigi Fortuna, University of Catania, ItalyMattia Frasca, University of Catania, ItalyYeung Siu Fung, The Chinese University of Hong Kong, Ma Liu Shui, ChinaMarco Furini, University of Modena and Reggio Emilia, ItalyDaniel Gartner, Fraunhofer Institute, Ilmenau, GermanyHolger Grossmann, Fraunhofer Institute, Ilmenau, GermanyMatthias Gruhne, Fraunhofer Institute, Ilmenau, GermanyIan Gwilt, University of Technology, Sydney, AustraliaMasaki Hoshino, Sony Corporation, Tokyo, JapanGeert-Jan Houben, Eindhoven University of Technology, Eindhoven, The NetherlandsWolfgang Hürst, Utrecht University, Utrecht, The NetherlandsLetizia Jaccheri, Norwegian University of Science and Technology, NorwayMatthias Jarke, Technical University of Aachen, Aachen, GermanySung Ho Jin, Information and Communications University, Daejeon, KoreaYohan Jin, University of Texas at Dallas, Texas, USANaoki Kamimaeda, Sony Corporation, Tokyo, JapanMohan Kankanhalli, National University of Singapore, SingaporeMunchurl Kim, Information and Communication University, Daejeon, KoreaMunjo Kim, Information and Communication University, Daejeon, KoreaRalf Klamma, Technical University of Aachen, Aachen, GermanyBumshik Lee, Information and Communication University, Daejeon, KoreaHan Kyu Lee, Electronics and Telecommunications Research Institute, Daejeon, KoreaHeekyung Lee, Electronics and Telecommunications Research Institute, Daejeon, KoreaIn-Kwon Lee, Yonsei University, Seoul, KoreaGeorge Lekakos, Athens University of Economics and Business, Athens, GreeceHua-Fu Li, Kainan University, Taoyuan, TaiwanJeongyeon Lim, Information and Communication University, Daejeon, KoreaJohn C.S. Lui, The Chinese University of Hong Kong, Ma Liu Shui, ChinaRastislav Lukac, Epson Canada Ltd., Toronto, CanadaHanna Lukashevich, Fraunhofer Institute, Ilmenau, GermanyAderito Fernandes Marcos, University of Minho, Guimaraes, PortugalDavid Milam, Simon Fraser University, Surrey, CanadaManuela Montangero, University of Modena and Reggio Emilia, ItalyAnush K. Moorthy, University of Texas at Austin, Austin, Texas, USAMichael Nixon, Simon Fraser University, Vancouver, CanadaStefanie Nowak, Fraunhofer Institute, Ilmenau, GermanyJohan Pouwelse, Delft University of Technology, Delft, The NetherlandsB. Prabhakaran, University of Texas at Dallas, Texas, USAMarcel Reinders, Delft University of Technology, Delft, The NetherlandsYong Man Ro, Information and Communications University, Daejeon, KoreaGraham Sellers, Advanced Micro Devices, Orlando, Florida, USAKalpana Seshadrinathan, University of Texas at Austin, Austin, Texas, USAShervin Shirmohammadi, University of Ottawa, Ottawa, CanadaAnastas Sofokleus, Brunel University, Uxbridge, United KingdomSara Owsley Sood, Pomona College, Claremont, CA, USA Flavia Sparacino, Sensing Places and MIT, Santa Monica, CA, USAMyunghoon Suk, University of Texas at Dallas, Texas, USATomohiro Tsunoda, Sony Corporation, Tokyo, JapanAthanasios Vasiliakos, University of Peloponnese, Nauplion, GreeceArjen de Vries, CWI, Amsterdam, The NetherlandsRon Wakkary, Simon Fraser University, Surrey, CanadaJun Wang , Delft University of Technology, Delft, The NetherlandsHuaxin Wei, Simon Fraser University, Vancouver, CanadaKay Wolter, Fraunhofer Institute, Ilmenau, GermanyLinxing Xiao, Tsinghua University, Beijing, ChinaWeiQi Yan, Queen’s University of Belfast, Belfast, UKXubo Yang, Shanghai Jiao Tong University, Shanghai, ChinaJong-Chul Yoon, Yonsei University, Seoul, KoreaDamon Daylamani Zad, Brunel University, Uxbridge, United KingdomNelson Troca Zagalo, University of Minho, Braga, PortugalVeronica Zammitto, Simon Fraser University, Vancouver, CanadaJie Zhou, Tsinghua University, Beijing, China

Preface 5
Contents 7
Contributors 11
Part I DIGITAL ENTERTAINMENT TECHNOLOGIES 17
1 Personalized Movie Recommendation 18
Introduction 18
Background Theory 20
Recommender Systems 20
Collaborative Filtering 21
Data Collection -- Input Space 21
Neighbors Similarity Measurement 22
Neighbors Selection 23
Recommendations Generation 24
Content-based Filtering 24
Other Approaches 25
Comparing Recommendation Approaches 26
Hybrids 27
MoRe System Overview 28
Recommendation Algorithms 31
Pure Collaborative Filtering 31
Pure Content-Based Filtering 32
Hybrid Recommendation Methods 35
Experimental Evaluation 36
Conclusions and Future Research 38
2 Cross-category Recommendation for Multimedia Content 42
Introduction 42
Technological Overview 43
Overview 43
Multimedia Content Recommendation 43
Basic Technologies Involving CF 44
Basic Technologies Involving CBF 44
Key Elements of a Content Recommendation System Using CBF 44
Content Profiling 46
Manual Tagging 46
Automatic Tagging 47
1) Automatic Tagging from Textual Information 47
2) Automatic Tagging from Visual Information 48
3) Automatic Tagging from Audio Information 50
Context Learning 51
User Preference Learning 51
Matching 52
1) VSM 52
2) NB Classifier 53
3) Other Approaches 54
Typical Cases of Multimedia Content Recommendation System 54
1) Content-meta-based Search 56
2) Context-aware Search 56
3) User-preference-based Search 56
Cross-category Recommendation 56
Key Points of a Cross-category Recommendation 56
Category Common Metadata 57
Separate User Preference Generation for Each Category 58
Embodiment of Recommendation Engine: Voyager Engine (VE) 58
Overview 59
Explanation of Component 59
Key Methods to Realize Cross-category Recommendation 60
AME 60
ICF 62
RCF 63
Example of Practical Applications 64
Multimedia Content Recommendation 64
branco 65
SensMe 65
Cross-category Recommendation 66
VAIO Giga Pocket Digital 66
TV Kingdom Service 67
Difficulties 69
Summary and Future Prospects 70
3 Semantic-Based Framework for Integration and Personalization of Television Related Media 73
Introduction 73
Related Work 74
Application Scenario 76
TV-Anytime 77
TV-Anytime Phase I 77
TV-Anytime Phase II 79
Semantically Enriched Content Model 80
Personalized Home Media Center 85
Design of Personalized Home Media Center 85
User Modeling 90
Context 91
Events 92
Cold Start 93
Import of known user profiles 94
Classification of users in groups 96
Personalized Content Search 97
Personalized Presentations 99
Implementation 100
SenSee Server 100
iFanzy 101
Conclusions 103
4 Personalization on a Peer-to-Peer Television System 105
Introduction 105
Related Work 107
Recommendation 107
Distributed Recommendation 108
Learning User Interest 109
System Design 109
User Profiling from Zapping Behavior 110
BuddyCast Profile Exchange 110
Recommendation by Relevance Models 112
Item-based Generation Model 113
User-based Generation Model 115
Statistical Ranking Mechanisms 116
Personalized User Interfaces 117
Experiments and Results 119
Data Set 119
Observations of the Data Set 120
Learning the User Interest Threshold 122
Convergence Behavior of BuddyCast 123
Recommendation Performance 123
Conclusions 126
5 A Target Advertisement System Based on TV Viewer's Profile Reasoning 128
Introduction 128
Architecture of Proposed Target Advertisement System 129
Proposed Profile Reasoning Algorithm 130
Analysis of Features Depending on User Profiles 131
Feature Extraction 134
The First Stage Classifier 136
The Second Stage Classifier 137
The Third Stage Classifier 138
Target Advertisement Contents Selection Method 139
Target Advertisement Contents Selection Method 140
Experimental Results 140
Experimental Result of Profile Reasoning 140
The Implementation Result of the Prototype Target Advertisement System 146
Conclusion 149
6 Digital Video Quality Assessment Algorithms 151
Introduction 151
HVS -- Based Approaches 154
Digital Video Quality Metric 155
Scalable Wavelet-Based Distortion Metric 155
Structural and Information-Theoretic approaches 156
Structural Similarity Index 156
Video Visual Information Fidelity 157
Feature Based Approaches 159
Video Quality Metric 159
Motion Modeling Based Approaches 160
Speed-Weighted SSIM 161
Motion Based Video Integrity Evaluation 162
Performance Evaluation & Validation
Conclusions & Future Directions
7 Countermeasures for Time-Cheat Detection in Multiplayer Online Games 169
Introduction 169
Background on System Architectures 170
System Model 171
Modeling Game Time 172
Time Cheats 175
Look-Ahead Cheat 176
Fast Rate Cheat 177
Suppress-Correct Cheat 178
Cheating Prevention 178
Cheating Detection 180
Conclusions and Future Directions 185
8 Zoning Issues and Area of Interest Management in Massively Multiplayer Online Games 187
Introduction 187
Challenges and Requirements 188
MMOG Architecture -- An Overview 189
MMOG Classification 189
Communication Architecture 189
Virtual Space Decomposition - Zoning 191
Zone Definition 191
Multiple Zones and its Space 192
Area of Interest Management 193
Interest Management Models 193
Publisher-Subscriber Model 194
Space Model 194
Region Model 195
Implementation Intelligence 195
Message Aggregation 195
Message Compression 195
Dead Reckoning 196
Interest Management Algorithms 196
Proximity Algorithms 196
Comparison of Euclidean Distance and Hexagonal Tile Algorithms 198
Euclidean Distance Algorithm 198
Hexagonal Tile Algorithm 198
Visibility Algorithms 199
Comparison of Ray and Tile Visibility Approach 200
Ray visibility 200
Tile visibility 200
Reachability Algorithms 200
Comparison of Tile Distance and Tile Neighbor Algorithms 201
Tile distance 201
Tile neighbor 201
Zone Crossing in P2P MMOGs 201
Different Interest Management Models -- Research Perspectives 203
Conclusions and Future Directions 205
9 Cross-Modal Approach for Karaoke Artifacts Correction 208
Karaoke 208
Preprocessing: noise detection and removal. 215
Tempo handling. 216
Tune handling. 220
Pitch handling. 221
Detection of Highlighted Video Captions 223
Algorithm for Karaoke Adjustment 225
Results 225
Conclusion 227
10 Dealing Bandwidth to Mobile Clients Using Games 230
Introduction 230
Resource Allocation Taxonomies 231
Resource Allocation Using Game Theory 233
Dealing Bandwidth Using a Game 236
The Three Phase Bandwidth Dealing Game 236
k-calculation Phase 237
Main Game Phase 239
Round 0 - base bandwidth dealing (BBD): 239
Round 1 - dynamic bandwidth dealing (DBD): 239
Round 2 - remainder bandwidth dealing (RBD): 242
Streaming-Seat Reallocation Phase 242
Concluding Discussion 242
11 Hack-proof Synchronization Protocol for Multi-player Online Games 247
Introduction 247
Backgrounds 248
Dead-reckoning 248
Linear Extrapolation 250
Speed-hack 251
Hack-proof Synchronization Protocol 253
Countermeasure 254
Invulnerability 255
Handling Missing Packets 256
Modified Dead-reckoning Protocol 256
Invulnerability 258
Extension 259
Handling Missing Packets 259
Enhanced Invulnerable Protocol 259
Handling Missing Packets 264
Extensions 264
Proof of Invulnerability 265
Implementation 267
Network Overhead 268
Related Works 269
Conclusion 273
12 Collaborative Movie Annotation 275
Introduction 275
Collaborative Retrieval and Tagging 276
Collaborative Retrieval 276
Collaborative Tagging of Non-Video Media 277
Collaborative Tagging of Video Media 278
Summary 280
Experiment Design 280
Video Metadata Tools and Content 281
User Groups and Tasks 282
Experiment Results 283
Research Method: Grounded Theory 283
Movie Content Metadata Creation 285
Most Commonly Used Tags 285
Relationships between Tags 288
System Features 291
An Architecture for a Collaborative Movie Annotation System 291
Metadata Scheme 292
System Architecture 294
Resources 295
Annotation 295
Retrieval 295
Community Interaction and Profiling 296
Concluding Discussion 296
Part II DIGITAL AUDITORY MEDIA 299
13 Content Based Digital Music Management and Retrieval 300
Introduction 300
Music Visualization: Tension Visualization Approach 301
Noisy Level Calculation 301
Tempo Estimation 304
Music Summarization: Key Segment Extraction Approach 305
Description of Key Segment 306
Key-Segment Extraction 306
Music Similarity Measure: Chroma-Histogram Approach 308
Feature Extraction 309
Model Construction 310
Distance Measure 311
An Realized Music Archive Management System 311
Conclusion and Future Directions 313
14 Incentive Mechanisms for Mobile Music Distribution 316
Introduction 316
The Current Mobile Music Market 317
Communication Infrastructure 318
Pricing Strategy 318
Copyright Protection 319
A Multi-Channel Distribution Approach 319
Multi-Channel Mobile Distribution 320
An Incentive Mechanism 321
Evaluation of the Multi-Channel Distribution Strategy 324
Wireless Music store 324
Cellphone Network Operators 325
Customer Point of View 325
Selfish distribution. 326
Equal distribution. 326
Higher Reward. 326
Minimum Reward. 327
Proportional distribution. 328
Higher Reward. 328
Related Work 331
Conclusions 332
15 Pattern Discovery and Change Detection of Online Music Query Streams 335
Introduction 335
Problem Definition of Pattern Discovery of Music Query Streams 339
Mining of Frequent Temporal Patterns in Music Query Streams 340
Data Processing: Bit-sequence Representation 340
The Proposed Algorithm FTP-stream 341
Window Initialization Phase of FTP-stream Algorithm 341
Window Sliding Phase of FTP-stream Algorithm 342
Frequent Temporal Pattern Generation Phase of FTP-stream 342
Experimental Evaluation of Pattern Discovery of Music Query Streams 343
Change Detection of Online Music Query Streams 347
Problem Definition 347
Detecting Changes from User-centered Music Query Streams 348
The Proposed Summary Data Structure MSC-list 348
The Proposed MQS-change Algorithm 349
Connection Between FTP-stream and MQS-change 351
Experimental Results of MQS-change Algorithm 353
Conclusions 354
16 Music Search and Recommendation 356
Introduction 356
Acoustic Features for Music Modeling 357
Low-level Audio Features 358
Mel-Frequency Cepstral Coefficients 359
Audio Spectrum Envelope 360
Audio Spectrum Flatness 360
Linear Predictive Coding 360
Zero Crossing Rate 361
Audio Spectrum Centroid 361
Audio Spectrum Spread 361
Mid-level Audio Features 361
Rhythmic Mid-level Features 362
Harmonic Mid-level Features 362
High-level Music Features 364
Statistical Modeling and Similarity Measures 365
Dimension Reduction 365
Principal Component Analysis 366
Self-Organizing Maps 366
Linear Discriminant Analysis 366
Statistical Models of The Song 367
Distance Measures 368
``In the Mood'' -- Towards Capturing Music Semantics 369
Classification Models 370
Classification Based on Gaussian Mixture Models 370
Classification Based on Support Vector Machines 370
Mood Semantics 371
Mood Models 371
Mood Classification 372
Music Recommendation 373
Visualizing Music for Navigation and Exploration 376
Visualization of Songs 376
Visualization of Music Archives 377
Navigation and Exploration in Music Archives 378
Summary and Open Issues 380
Applications 380
Business to Business Applications 381
Business to Consumer Applications 382
Future Directions and Challenges 383
17 Automated Music Video Generation Using Multi-levelFeature-based Segmentation 392
Introduction 392
Related Work 393
System Overview 393
Video Segmentation and Analysis 394
Segmentation by Contour Shape Matching 394
Video Feature Analysis 396
Detecting Significant Regions 397
Music Segmentation and Analysis 400
Novelty Scoring 400
Music Feature Analysis 401
Matching Music and Video 402
Experimental Results 404
Conclusion 407
Part III DIGITAL VISUAL MEDIA 409
18 Real-Time Content Filtering for Live Broadcasts in TV Terminals 410
Introduction 410
Real-time Content Filtering System 411
Filtering System Structure 411
Real-Time Content Filtering Algorithm 412
Filtering System Analysis 414
Modeling of a Filtering System 414
Experiments 417
Applied Filtering Algorithm for Soccer Videos 417
Experimental Results with Soccer Videos 420
Discussion 424
Conclusion 424
19 Digital Theater: Dynamic Theatre Spaces 427
Introduction 427
Interactive Theater 428
Interactive Theater Architecture 430
Embodied mixed reality space and Live 3D actors 430
Hardware setup 430
Interactive Theatre system 433
Automated Performance by Digital Actors 436
Human/machine collaborative performance 436
The Pattern Game 437
One Word Story 439
The Association Engine 441
Experiencing a Performance 443
Completely Automated Performances 444
Story Discovery 445
Conclusions 447
20 Video Browsing on Handheld Devices 450
Introduction 450
A Short Review of Video Browsing Techniques for Larger Displays 451
Mobile Video Usage and Need for Browsing 454
Timeline-Based Mobile Video Browsing and Related Problems 455
Implementation 457
Flicking vs. Elastic Interfaces 457
Linear vs. Circular Interaction Patterns 461
One-handed Content-Based Mobile Video Browsing 466
Summary and Outlook 470
21 Projector-Camera Systems in Entertainment and Art 473
Introduction 473
Visualization with Projector-Camera Systems 474
Inverting the Light Transport 474
Geometric Image Correction 475
Photometric Image Correction 476
Defocus Compensation 477
Structured Light Scanning 478
Interaction with Projector-Camera Systems 479
Interaction with Spatial Projector 480
Physically Viewing Interaction 481
Near Distance Interaction 481
Far Distance Interaction 483
Interaction with Handheld Projectors 484
Image Stabilizing 484
Pointing Techniques 485
Selection and Manipulation 485
Multi-user Interaction 486
Environment Awareness 487
Interaction Design and Paradigm 487
Application Examples 489
Embedded Multimedia Presentations 489
Superimposing Museum Artifacts 489
Spatial Augmented Reality 490
Flexible Digital Video Composition 492
Interactive Attraction Installations 493
The Future of Projector-Camera Systems 494
22 Believable Characters 499
Introduction 499
Character Personality 502
Body Type Theories 503
Psychodynamic Theories 505
Traits Theories 507
Factor Theories 508
Johnstone's Fast Food Stanislavsky Model 510
Personality and Believable Characters 511
Nonverbal Behavior Theory and Models 513
Structural Approach 515
Descriptive Approach 516
Social and Communication 516
Gesture 517
Delsarte 518
Laban Movement Analysis 519
Effort Overview 520
Understanding the Subtle Meaning of Nonverbal Behaviors 523
Nonverbal Behavior and Adaptive Believable Character 524
Animation Techniques 525
Animation and Adaptive Believable Character 527
Conclusions and Open Problems 527
23 Computer Graphics Using Raytracing 531
Introduction 531
The Origins of Raytracing 532
Raytracing 533
The Raycasting Algorithm 533
Ray Intersection Tests 535
Performing Surface Shading 536
Generation of Secondary Rays 539
Controlling Scene Complexity 541
Image Quality Issues 543
Acceleration of Raytracing 546
Bounding Volumes 546
Space Partitioning Tree Structures 547
Hardware Accelerated Raytracing 548
Summary 549
24 The 3D Human Motion Control Through Refined Video Gesture Annotation 552
Introduction 552
Related Work 553
Proposed Approach 554
Human Motion Analysis & Comparison
Video Human Motion Feature Extraction 556
3D Human Motion Capture Data 558
Motion Feature Value Comparison between 3D Motion Capture and Video Human Motion 561
Controlling 3D Human Motion using Video Human Motion Annotation 562
Conclusion 563
Part IV DIGITAL ART 566
25 Information Technology and Art: Concepts and Stateof the Practice 567
Introduction 567
The Conceptual Framework 569
Who 569
Where 570
Why 571
What 573
Description of the Projects 575
Flyndre 575
Who 576
Where 577
Why 577
What 577
Sonic Onyx 578
Who 579
Why 579
Where 579
What 579
The Open Wall 579
Who 580
Why 580
Where 581
What 581
Chaotic Robots For Art (Fig.4) 582
Who 582
Where 583
Why 583
What 584
Interactive Bubble Robots For Art 585
Who 585
Where 586
Why 586
What 586
Discussion and Conclusion 587
26 Augmented Reality and Mobile Art 593
Introduction 593
Overview of AR 593
AR Mobile Art 594
Case Study: AR Mobile Art 595
Conclusion 598
27 The Creation Process in Digital Art 600
Introduction 600
Digital Art Fundamentals 603
Definitions 604
Creation Process 605
The Process 607
The Creative Design Space Architecture 609
Discussion 612
Conclusions and Future Work 613
28 Graphical User Interface in Art 615
Introduction 615
Strategies for the Re-contextualization of the GUIin Art Practice 616
The Visual and Conceptual Configuration of the GUI 617
The GUI as an Environment for Art Practice 618
Conclusion 620
29 Storytelling on the Web 2.0 as a New Means of Creating Arts 621
Introduction 621
Use Scenarios 623
Related Work 624
Community of Practice and Web 2.0 626
Knowledge Work and Web 2.0 626
Storytelling on Web 2.0 628
Existing Storytelling Platforms 629
YouTell: A Web 2.0 Service for Community Based Storytelling 631
Virtual Campfire 631
The Role Model 634
Web 2.0 for Storytelling: Tagging and Rating 635
Profile-based Story Searching 635
Expert Finding System 637
Web 2.0 for the Expert-finding Algorithm 639
Implementation of the YouTell Prototype 639
YouTell Evaluation 641
Prototype Testing 641
Profile Based Story Search 642
Expert Finding Algorithm 643
Summary 644
Part V CULTURE OF NEW MEDIA 649
30 A Study of Interactive Narrative from User's Perspective 650
Introduction 650
Previous Research 651
Interactive Narrative Architectures 651
Evaluating the User's Experience within Interactive Narrative 653
Façade 654
Method 654
Study Design 656
Participants 656
Procedure 657
Analysis 658
Theoretical Lenses for Discussing Participants' Experience 658
Summary of Participants' Statements 659
Results 660
Lens 1: System Constraints (Informed by Boundaries, Freedom, Goals, and Control) 660
Phase I: Initial Conceptions of IN Pertaining to System Constrains Lens 662
Phase II: Pre Play Conceptions of IN from the Façade Description Pertaining to System Constrains Lens 662
Phase IV: Façade Post-play Interview Pertaining to System Constrains Lens 663
Lens 2: Role Play 664
Phase I: Initial Conceptions of IN Pertaining to Role Play Lens 667
Preparation for Role Play 667
The Process of Role Playing 668
Phase II: Pre Play Conceptions of IN from the Façade Description Pertaining to Role Play Lens 668
Preparation for Role Play 669
The Process of Role Playing 669
Phase IV: Façade Post-play Interview Pertaining to Role Play Lens 670
Preparation for Role Play 670
The Process of Role Playing 671
Reflections on Interactive Narrative 673
Conclusion 676
31 SoundScapes/Artabilitation -- Evolution of a Hybrid Human Performance Concept, Method Apparatus Where Digital Interactive Media, The Arts, Entertainment are Combined 679
Introduction 679
Background 680
Painting for Life 683
Strategies of Use 684
All-inclusive Inquiry 687
System Actability, Usability, Usefulness and Affordability 688
Untraditional Therapeutic Practice 688
Transcending to and from Entertainment and the Arts 690
Underground Non-formal Learning 691
ArtAbilitation Workshops, Casa da Musica, Porto, Portugal 692
Visualizing classical music 697
Conclusions and Future Directions 700
32 Natural Interaction in Intelligent Spaces: Designingfor Architecture and Entertainment 708
Introduction 708
Related Work 710
Smart Spaces 710
Perceptual Intelligence and Natural Interaction 711
Bayesian Networks for User Modeling and Interactive Narrative 712
Criteria for Intelligent Space Design 713
Perceptual Intelligence 713
Interpretive Intelligence 713
Narrative Intelligence 714
Intelligence Modeling 714
Applications 715
Perceptual Intelligence: Navigating the Internet City 715
Natural Interfaces: Motivation 715
City of news: an Internet City in 3D 716
2D Blob Tracking 718
Person Tracking and Shape Recovery 720
Gesture Recognition 721
Comments 722
Interpretive Intelligence: Modeling User Preferences in The Museum Space 722
User Modeling: Motivation 722
The Museum Wearable 723
Sensor-Driven Understanding of Visitors' Interests with Bayesian Networks 724
Model Description, Learning and Validation 727
Comments 729
Narrative Intelligence: Sto(ry)chastics 731
Narrative Intelligence: Motivation 731
Editing Stories for Different Visitor Types and Profiles 731
Comments 735
Discussion and Conclusions 736
33 Mass Personalization: Social and Interactive Applications Using Sound-Track Identification 740
Introduction 740
Personalizing Broadcast Content: Four Applications 742
Personalized Information Layers 742
Ad-hoc Peer Communities 745
Real-time Popularity Ratings 746
Video ``Bookmarks'' 746
Supporting Infrastructure 747
Client-Interface Setup 747
Audio-Database Server Setup 748
Social-Application Server Setup 748
Audio Fingerprinting 749
Hashing Descriptors 749
Within-Query Consistency 751
Post-Match Consistency Filtering 751
Evaluation of System Performance 752
Empirical Evaluation 752
``In-Living-Room'' Experiments 754
Discussion 756
Index 760