Preface ........................................................ xv
Contributors ................................................. xvii
1. Multimedia Metadata 2.0: Challenges of Collaborative
Content Modeling ............................................. 1
DAMON DAYLAMANIZAD AND HARRY AGIUS
1.1. Introduction ............................................... 1
1.2. Challenges of MM 2.0 ....................................... 3
1.2.1. Standardization ..................................... 3
1.2.2. Folksonomies ........................................ 5
1.2.3. Awareness ........................................... 7
1.2.4. Community ........................................... 9
1.3. Suitability of MPEG-7 in Meeting the Challenges ........... 10
1.3.1. Meeting Standardization Challenges ................. 10
1.3.2. Meeting Folksonomic Challenges ..................... 12
1.3.3. Meeting Awareness Challenges ....................... 15
1.3.4. Meeting Community Challenges ....................... 16
1.4. Conclusion ................................................ 16
Acknowledgment ................................................. 17
References ..................................................... 17
2. Research Directions toward User-Centric Multimedia .......... 21
BERNHARD REITERER, JANINE LACHNER, ANDREAS LORENZ,
ANDREAS ZIMMERMANN, AND HERMANN HELLWAGNER
2.1. Introduction .............................................. 21
2.2. Vision of User-Centric Multimedia ......................... 22
2.3. Personalization and Context Management .................... 25
2.3.1. Adaptation Targets ................................. 26
2.3.2. Properties of Users and Context .................... 27
2.3.2.1. Interindividual Differences and
Intraindividual Differences ............... 27
2.3.2.2. Environmental Differences ................. 28
2.3.3. Approaches to User Modeling ........................ 29
2.3.3.1. Monolithic User Modeling .................. 30
2.3.3.2. User-Modeling Servers ..................... 30
2.3.3.3. Modularization of User Models ............. 31
2.3.3.4. Ubiquitous User Modeling .................. 31
2.3.4. Approaches to Context Management ................... 32
2.4. Content Adaptation ........................................ 33
2.4.1. Concepts for Adaptation ............................ 33
2.4.2. Utility-Based Multimedia Adaptation ................ 35
2.4.3. Knowledge-Based Media Adaptation ................... 35
2.5. Implications .............................................. 36
2.5.1. User Modeling and Context Management ............... 36
2.5.2. Advanced Interfaces for Converging Devices ......... 37
2.5.3. Extending Multimedia Adaptation Decision Taking .... 38
2.6. Conclusion ................................................ 39
Acknowledgment ................................................. 40
References ..................................................... 41
3. User-Centered Adaptation of User Interfaces for
Heterogeneous Environments .................................. 43
JAN MESKENS, MIEKE HAESEN, KRIS LUYTEN, AND KARIN
CONINX
3.1. Introduction .............................................. 43
3.2. MuiCSer Process Framework ................................. 45
3.3. Models .................................................... 47
3.3.1. Presentation Model ................................. 48
3.3.1.1. Form-Based UIDLs .......................... 49
3.3.1.2. High-Level UIDLs .......................... 49
3.3.2. User Model ......................................... 50
3.3.3. Device Model ....................................... 51
3.4. Designing for Transformation .............................. 51
3.4.1. Tools .............................................. 52
3.4.2. Gummy .............................................. 54
3.5. Runtime UI Adaptation ..................................... 56
3.5.1. Adaptation Process ................................. 56
3.5.2. Examples ........................................... 58
3.6. Discussion ................................................ 59
Acknowledgments ................................................ 61
References ..................................................... 62
4. Video Adaptation Based on Content Characteristics and
Hardware Capabilities ....................................... 67
OZGUR DENIZ ÖNÜR AND AYDIN A. ALATAN
4.1. Introduction .............................................. 67
4.2. Utility-Based Video Adaptation ............................ 70
4.2.1. Video Content Characteristics ...................... 71
4.2.2. Hardware Capabilities .............................. 72
4.3. Subjective Video Evaluation Tests ......................... 73
4.3.1. Test Methodology ................................... 73
4.3.1.1. Training Phase ............................ 74
4.3.1.2. Stabilization Phase ....................... 74
4.3.1.3. Testing Phase ............................. 74
4.3.1.4. Comparison of DSIS and DSCQS Methods ...... 74
4.3.2. Subjective Video Evaluation Experiments ............ 75
4.3.2.1. High-End PDA Tests ........................ 75
4.3.2.2. Mobile Phone Tests ........................ 80
4.3.3. Predicting Satisfaction Models for Unknown
Devices ............................................ 84
4.3.3.1. Prediction for High-End PDAs .............. 86
4.3.3.2. Prediction for Mobile Phones .............. 88
4.3.4. Obtaining Optimal User Satisfaction ................ 88
4.4. Conclusions ............................................... 91
References ................................................ 93
5. Toward Next-Generation In-Flight Entertainment Systems:
A Survey of the State of the Art and Possible Extensions .... 95
HAO LIU, BEN SALEM, AND MATTHIAS RAUTERBERG
5.1. Introduction .............................................. 95
5.2. Overview of the Current In-Flight Entertainment
Systems ................................................... 96
5.2.1. Currently Installed In-Flight Entertainment
Systems ................................................... 97
5.2.2. Commercially Available In-Flight Entertainment
Systems ................................................... 99
5.2.3. Discussions and Conclusions ........................ 99
5.3. Extending the Capabilities of In-Flight Entertainment
Systems to Increase Passengers' Comfort Actively and
Intelligently ............................................ 101
5.3.1. Context-Adaptive Systems .......................... 101
5.3.2. User Profiling .................................... 102
5.3.3. Methods of Using Entertainment Services for
Stress Reduction .................................. 104
5.3.3.1. Music .................................... 104
5.3.3.2. Games .................................... 104
5.3.4. Cybernetics Control Systems ....................... 105
5.3.5. A New Framework for Next-Generation In-Flight
Entertainment Systems ............................. 106
5.4. Conclusions .............................................. 108
Acknowledgment ................................................ 108
References .................................................... 109
6. Toward an Adaptive Video Retrieval System .................. 113
FRANK HOPFGARTNER AND JOEMON M. JOSE
6.1. Introduction ............................................. 113
6.2. Background ............................................... 115
6.2.1. Interactive Video Retrieval Systems ............... 116
6.2.2. Personalization ................................... 117
6.2.3. Evolving User Interest ............................ 118
6.2.4. Relevance Ranking ................................. 119
6.2.5. Evaluation Framework .............................. 119
6.3. Research Framework ....................................... 120
6.4. NewsBoy Architecture ..................................... 122
6.4.1. Data Collection ................................... 123
6.4.2. Desktop PC Interface .............................. 126
6.4.3. Profile ........................................... 128
6.4.3.1. Capturing Evolving Interest .............. 129
6.4.3.2. Capturing Multiple Interests ............. 131
6.5. Discussion ............................................... 132
Acknowledgment ................................................ 132
References .................................................... 133
7. On Using Information Retrieval Techniques for Semantic
Media Adaptation ........................................... 137
SEBASTIEN LABORIE AND ANTOINE ZIMMERMANN
7.1. Introduction ............................................. 137
7.2. Related Work ............................................. 138
7.2.1. Media Adaptation .................................. 138
7.2.2. Semantic Information Retrieval and Description .... 139
7.3. Motivating Examples ...................................... 140
7.4. A Framework for Media Adaptation ......................... 142
7.4.1. Description Association (a) ....................... 144
7.4.2. Description Aggregation (b) ....................... 144
7.4.3. Description Similarity (c) ........................ 145
7.4.4. Description Selection (d) ......................... 145
7.4.5. Adaptation Component .............................. 146
7.5. Media Adaptation by Semantic Web Retrieval ............... 147
7.5.1. Scenario .......................................... 148
7.5.2. Module (a) ........................................ 149
7.5.3. Module (b) ........................................ 150
7.5.4. Module (c) ........................................ 151
7.5.5. Module (d) ........................................ 152
7.6. Discussion ............................................... 152
7.7. Conclusion ............................................... 153
References .................................................... 154
8. Interactive Video Browsing of H 264 Content Based on
Just-in-Time Analysis ...................................... 159
KLAUS SCHÖFFMANN AND LASZLO BÖSZÖRMENYI
8.1. Introduction ............................................. 159
8.2. Related Work ............................................. 160
8.3. System Architecture ...................................... 162
8.3.1. Overview .......................................... 162
8.3.2. Video Segmentation ................................ 163
8.3.3. Unit Classification ............................... 163
8.3.4. Visualization and Interactivity ................... 164
8.4. Interactive User Interface ............................... 164
8.4.1. Chronological Shot Navigation ..................... 164
8.4.2. Feature-Based Shot Navigation ..................... 165
8.4.3. Hierarchical Navigation ........................... 166
8.5. Feature Extraction from H.264 ............................ 167
8.5.1. Macroblock Type Distribution ...................... 168
8.5.2. Macroblock Partitioning Scheme .................... 168
8.5.3. Intra prediction Mode Histogram ................... 170
8.5.4. Dominant Motion ................................... 170
8.5.5. Shot Length ....................................... 171
8.5.6. Color Information ................................. 171
8.6. Experimental Results ..................................... 171
8.7. User Study ............................................... 173
8.7.1. Test Setup and Environment ........................ 173
8.7.2. Evaluation ........................................ 173
8.7.3. Questionnaire and SUS ............................. 176
8.8. Conclusions .............................................. 177
References .................................................... 179
9. Personalized Faceted Navigation in Semantically Enriched
Information Spaces ......................................... 181
MICHAL TVAROZEK AND MARIA BIELIKOVA
9.1. Introduction1 ............................................ 181
9.2. Related Work ............................................. 183
9.2.1. Keyword-Based Search .............................. 183
9.2.2. Content-Based Search .............................. 183
9.2.3. View-Based Search ................................. 184
9.3. Personalized Faceted Navigation Overview ................. 185
9.4. Model for Relevance Evaluation ........................... 187
9.5. Facet Recommendation ..................................... 190
9.5.1. Facet and Restriction Personalization ............. 190
9.5.2. Dynamic Facet Generation .......................... 191
9.6. Search Result Recommendations ............................ 192
9.7. Evaluation ............................................... 193
9.7.1. Architecture and Implementation ................... 193
9.7.2. Examples and Domains .............................. 195
9.7.2.1. Information Overload Prevention .......... 195
9.7.2.2. Orientation and Guidance Support ......... 196
9.7.2.3. Query Refinement ......................... 196
9.7.2.4. Social Navigation and Collaboration ...... 196
9.7.3. Experiments and Discussion ........................ 197
9.8. Conclusions .............................................. 198
Acknowledgments ............................................... 199
References .................................................... 199
10.Personalized Audiovisual Content-Based Podcasting .......... 203
ELENA SANCHEZ-NIELSEN AND FRANCISCO CHAVEZ-GUTIERREZ
10.1.Introduction ............................................. 203
10.2.State of the Art ......................................... 204
10.2.1.Facing the Multimedia Content Domain .............. 204
10.2.2.Content Delivery Distribution ..................... 205
10.2.3.Podcast Publishing ................................ 206
10.2.4.MPEG-7 ............................................ 207
10.2.5.Semantic Description Tools ........................ 209
10.2.5.1.Abstraction Model ........................ 209
10.2.5.2.Semantic Relations ....................... 209
10.3.Motivating Scenario: Personalized Podcast Publishing
for Parliamentary Web Sites .............................. 210
10.3.1.Legislative Assembly Domain ....................... 210
10.3.2.Need for Personalized Podcast Publishing .......... 211
10.4.Customized Podcast Information System .................... 212
10.4.1.Description of Plenary Sessions Content ........... 212
10.4.2.Metadata and Content Generation ................... 215
10.4.3.Fragmentation ..................................... 219
10.4.4.Customized Feeds Delivery ......................... 220
10.5.System Status ............................................ 221
10.6.Conclusions and Future Work .............................. 222
References .................................................... 223
11.Use of Similarity Detection Techniques for Adaptive News
Content Delivery and User Profiling ........................ 225
BILAL ZAKA, CHRISTIAN SAFRAN, AND FRANK KAPPE
11.1.Introduction ............................................. 225
11.2.Related Work ............................................. 227
11.3.Design of PINC ........................................... 229
11.3.1.News Acquisition and Preprocessing ................ 229
11.3.2.Personalization ................................... 231
11.3.3.Aggregation ....................................... 233
11.3.4.User Interfaces ................................... 233
11.3.4.1.World Wide Web Access .................... 234
11.3.4.2.Speech Interface ......................... 234
11.3.4.3.E-Ink .................................... 235
11.3.4.4.Video .................................... 236
11.4.System Architecture ...................................... 237
11.5.Prototype ................................................ 240
11.6.Summary and Future Work .................................. 241
Acknowledgments ............................................... 242
References .................................................... 243
12.Toward an Adaptive and Personalized Web Interaction Using
Human Factors .............................................. 247
PANAGIOTIS GERMANAKOS, NIKOS TSIANOS, ZACHARIAS
LEKKAS, CONSTANTINOS MOURLAS, MARIO BELK, AND GEORGE
SAMARAS
12.1.Introduction ............................................. 247
12.2.Theoretical Background ................................... 249
12.2.1.Constructive Comparison of Adaptive Hypermedia
and Web Personalization ........................... 249
12.2.2.User Profile Fundamentals ......................... 250
12.2.3.Comprehensive User Profile Used in the
AdaptiveWeb System ................................ 250
12.2.3.1.Traditional User Profile ................. 251
12.2.3.2.User Perceptual Preference
Characteristics .......................... 251
12.2.4.Relating the Comprehensive Profile with the
Information Space: A High-Level Correlation
Diagram ........................................... 253
12.3.Adaptive Web System's Architecture ....................... 255
12.4.Adaptation Process ....................................... 256
12.4.1.User Profile Construction Process ................. 256
12.4.2.Content Authoring and Mapping Process ............. 258
12.4.3.Viewing the Adapted Content: The
Adaptivelnteli Web Environment .................... 263
12.4.3.1.e-Learning Environment ................... 264
12.4.3.2.e-Commerce Environment ................... 264
12.5.Evaluating System Performance ............................ 267
12.6.Evaluation of the e-Learning Paradigm .................... 268
12.6.1.Sampling and Procedure ............................ 268
12.6.2.Results ........................................... 269
12.7.Evaluation of the e-Commerce Paradigm .................... 271
12.7.1.Sampling and Procedure ............................ 271
12.7.2.Implications for an e-Commerce Setting ............ 273
12.7.3.Results ........................................... 273
12.8.Conclusions and Future Work .............................. 275
References .................................................... 278
13.Image-Based Synthesis for Human Facial Expressions ......... 283
NIKOLAOS ERSOTELOS AND FENG DONG
13.1.Introduction ............................................. 283
13.1.1.Aim and Objectives ................................ 284
13.2.Previous Work ............................................ 284
13.3.Existing Techniques and New Approach Implementations ..... 286
13.3.1.Divide a Face into Areas .......................... 288
13.3.2.Elimination of Geometrical Distortion ............. 288
13.3.3.Illumination Transfer ............................. 289
13.3.4.Facial Expression Database ........................ 289
13.3.5.Copy Facial Area: Noise Reduction ................. 290
13.4.Results .................................................. 291
13.5.Discussions and Future Plans ............................. 293
13.6.Conclusion ............................................... 294
References .................................................... 295
14.Image Retrieval Using Particle Swarm Optimization .......... 297
KRISHNA CHANDRAMOULI AND EBROUL IZQUIERDO
14.1.Introduction ............................................. 297
14.2.Particle Swarm Optimization .............................. 300
14.3.Related Work ............................................. 302
14.3.1.Neural Network—Based Relevance Feedback ........... 302
14.3.2.Support Vector Machine (SVM)-Based Relevance
Feedback .......................................... 303
14.4.Proposed Approach ........................................ 304
14.4.1.Visual Search System .............................. 305
14.4.2.Relevance Feedback System ......................... 307
14.5.Experimental Results ..................................... 309
14.5.1.Feature Set ....................................... 309
14.5.2.PSO Implementation ................................ 309
14.5.3.Corel Dataset ..................................... 309
14.5.4.Caltech Dataset ................................... 315
14.6.Conclusions and Future Work .............................. 316
Acknowledgment ................................................ 316
References .................................................... 317
15.Image Description Using Scale-Space Edge Pixel Directions
Histogram .................................................. 321
ANTONIO M.G. PINHEIRO
15.1.Introduction ............................................. 321
15.2.Scale-Space Edge Pixel Directions Histogram .............. 323
15.3.Image Classification Using Scale-Space Edge Pixel
Directions Histogram ..................................... 326
15.3.1.Image Comparison .................................. 326
15.3.2.Classification Using the Nearest Class Mean ....... 329
15.3.3.High-Level Annotation of Images ................... 331
15.4.Final Remarks and Future Work ............................ 338
References ............................................... 339
16.Semantic Language for Description and Detection of Visual
Events ..................................................... 341
AHMED AZOUGH, ALEXANDRE DELTEIL, FABIEN DE MARCHI,
AND MOHANDSAID HACID
16.1.Introduction ............................................. 341
16.2.Related Work ............................................. 343
16.2.1.Semantic Description of Multimedia Resources ...... 343
16.2.2.Detection of Events and High-Level Concepts in
Videos ................................................... 344
16.3.Our Contribution ......................................... 345
16.4.Modeling Visual Events ................................... 346
16.4.1.Video Semantic Structure .......................... 346
16.4.2.Formal Model Language ............................. 346
16.4.2.1.Fuzzy Conceptual Graphs .................. 347
16.4.2.2.Temporal Finite State Machine ............ 348
16.4.3.Hierarchical Description .......................... 348
16.5.High-Level Events Detection .............................. 350
16.5.1.Detection Framework ............................... 350
16.5.1.1.Model Editor ............................. 351
16.5.1.2.Video Annotator .......................... 351
16.5.1.3.Event Detector ........................... 352
16.5.2.Detection Algorithms .............................. 352
16.5.2.1.Model Occurrence ......................... 352
16.5.2.2.Objectlnstances .......................... 353
16.5.2.3.Matching ................................. 353
16.6.Video-Guided Monitoring of Behavior ...................... 354
16.6.1.Monitoring Protocol Construction .................. 356
16.6.2.Monitoring Behavior for Video Surveillance ........ 357
16.6.3.Use Case: Car Theft ............................... 358
16.7.MPEG-7 Annotation Validation ............................. 359
16.8.Conclusion and Perspectives .............................. 362
References .................................................... 363
17.MPEG-7-Based Semantic Indexing of Film Heritage
Audiovisual Content ........................................ 365
YOLANDA COBOS, MARIA TERESA LINAZA, CRISTINA SARASUA,
ANDER GARCIA, AND ISABEL TORRE
17.1.Introduction ............................................. 365
17.2.Related Work ............................................. 366
17.2.1.Description of the MPEG-7 Standard ................ 366
17.2.2.Annotation Tools Based on MPEG-7 .................. 368
17.2.3.Projects Based on the MPEG-7 Standard ............. 370
17.2.4.MPEG-7 and Cultural Heritage ...................... 371
17.3.Application Scenario: The CINeSPACE Project .............. 372
17.3.1.Main Objectives of the Project .................... 372
17.3.2.Architecture of the Content Management System ..... 373
17.3.3.Performance of the Annotation and Retrieval
CINeSPACE System .................................. 374
17.4.CINeSPACE and MPEG-7 ..................................... 375
17.4.1.Motivation for Using MPEG-7 ....................... 375
17.4.2.Requirements for the CINeSPACE Metadata ........... 376
17.4.3.MPEG-7 Descriptors for CINeSPACE Metadata ......... 376
17.4.3.1.Basic Elements ........................... 377
17.4.3.2.User Preferences ......................... 378
17.4.3.3.Visual Descriptors ....................... 378
17.4.3.4.Semantic Features ........................ 378
17.4.3.5.Camera Metadata .......................... 379
17.4.3.6.Global Positioning Data .................. 379
17.5.CINeSPACE Annotation Tool ................................ 379
17.5.1.Image Information Panel ........................... 380
17.5.2.User Preferences Panel ............................ 386
17.5.3.Semantics Panel ................................... 388
17.5.4.Shape Panel and Visuals Panel ..................... 392
17.6.Results .................................................. 392
17.7.Conclusions and Future Work .............................. 394
References .................................................... 395
18.Automatic Feature Extraction to an MPEG-7 Content Model .... 399
M.J. PARMAR AND M.С. ANGELIDES
18.1.Introduction ............................................. 399
18.2.Related Work ............................................. 401
18.2.1.Shots/Actions ..................................... 401
18.2.2.Scenes/Events ..................................... 402
18.2.3.Objects ........................................... 404
18.2.4.Spatial and Temporal Relations .................... 406
18.3.Feature Extraction Framework ............................. 407
18.3.1.Shot Processor .................................... 407
18.3.2.Object Processor .................................. 409
18.3.3.Scene Processor ................................... 411
18.3.4.Spatial Relationships Processor ................... 411
18.3.5.Temporal Relationship Processor ................... 412
18.3.6.Content Modeler ................................... 412
18.4.Modeling Content in MPEG-7 ............................... 413
18.4.1.Scene and Shot Descriptions ....................... 413
18.4.2.Object Representation ............................. 416
18.4.3.Spatial Relationships ............................. 418
18.4.4.Temporal Relationships ............................ 419
18.5.Conclusion ............................................... 420
References .................................................... 421
Index ......................................................... 425
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