About the Book
In this book, the authors present the latest research results in the multimedia and semantic web communities, bridging the "Semantic Gap" This book explains, collects and reports on the latest research results that aim at narrowing the so-called multimedia "Semantic Gap": the large disparity between descriptions of multimedia content that can be computed automatically, and the richness and subjectivity of semantics in user queries and human interpretations of audiovisual media. Addressing the grand challenge posed by the "Semantic Gap" requires a multi-disciplinary approach (computer science, computer vision and signal processing, cognitive science, web science, etc.) and this is reflected in recent research in this area. In addition, the book targets an interdisciplinary community, and in particular the Multimedia and the Semantic Web communities. Finally, the authors provide both the fundamental knowledge and the latest state-of-the-art results from both communities with the goal of making the knowledge of one community available to the other.
Key Features:
Presents state-of-the art research results in multimedia semantics: multimedia analysis, metadata standards and multimedia knowledge representation, semantic interaction with multimedia
Contains real industrial problems exemplified by user case scenarios
Offers an insight into various standardisation bodies including W3C, IPTC and ISO MPEG
Contains contributions from academic and industrial communities from Europe, USA and Asia
Includes an accompanying website containing user cases, datasets, and software mentioned in the book, as well as links to the K-Space NoE and the SMaRT society web sites (http://www.multimediasemantics.com/)
This book will be a valuable reference for academic and industry researchers /practitioners in multimedia, computational intelligence and computer science fields. Graduate students, project leaders, and consultants will also find this book of interest.
Table of Contents:
Foreword xi List of Figures xiii
List of Tables xvii
List of Contributors xix
1 Introduction 1
Raphaël Troncy, Benoit Huet and Simon Schenk
2 Use Case Scenarios 7
Werner Bailer, Susanne Boll, Oscar Celma, Michael Hausenblas and Yves Raimond
2.1 Photo Use Case 8
2.1.1 Motivating Examples 8
2.1.2 Semantic Description of Photos Today 9
2.1.3 Services We Need for Photo Collections 10
2.2 Music Use Case 10
2.2.1 Semantic Description of Music Assets 11
2.2.2 Music Recommendation and Discovery 12
2.2.3 Management of Personal Music Collections 13
2.3 Annotation in Professional Media Production and Archiving 14
2.3.1 Motivating Examples 15
2.3.2 Requirements for Content Annotation 17
2.4 Discussion 18
Acknowledgements 19
3 Canonical Processes of Semantically Annotated Media Production 21
Lynda Hardman, Z¡êljko Obrenovic´ and Frank Nack
3.1 Canonical Processes 22
3.1.1 Premeditate 23
3.1.2 Create Media Asset 23
3.1.3 Annotate 23
3.1.4 Package 24
3.1.5 Query 24
3.1.6 Construct Message 25
3.1.7 Organize 25
3.1.8 Publish 26
3.1.9 Distribute 26
3.2 Example Systems 27
3.2.1 CeWe Color Photo Book 27
3.2.2 SenseCam 29
3.3 Conclusion and Future Work 33
4 Feature Extraction for Multimedia Analysis 35
Rachid Benmokhtar, Benoit Huet, Gaël Richard and Slim Essid
4.1 Low-Level Feature Extraction 36
4.1.1 What Are Relevant Low-Level Features? 36
4.1.2 Visual Descriptors 36
4.1.3 Audio Descriptors 45
4.2 Feature Fusion and Multi-modality 54
4.2.1 Feature Normalization 54
4.2.2 Homogeneous Fusion 55
4.2.3 Cross-modal Fusion 56
4.3 Conclusion 58
5 Machine Learning Techniques for Multimedia Analysis 59
Slim Essid, Marine Campedel, Gaël Richard, Tomas Piatrik, Rachid Benmokhtar and Benoit Huet
5.1 Feature Selection 61
5.1.1 Selection Criteria 61
5.1.2 Subset Search 62
5.1.3 Feature Ranking 63
5.1.4 A Supervised Algorithm Example 63
5.2 Classification 65
5.2.1 Historical Classification Algorithms 65
5.2.2 Kernel Methods 67
5.2.3 Classifying Sequences 71
5.2.4 Biologically Inspired Machine Learning Techniques 73
5.3 Classifier Fusion 75
5.3.1 Introduction 75
5.3.2 Non-trainable Combiners 75
5.3.3 Trainable Combiners 76
5.3.4 Combination of Weak Classifiers 77
5.3.5 Evidence Theory 78
5.3.6 Consensual Clustering 78
5.3.7 Classifier Fusion Properties 80
5.4 Conclusion 80
6 Semantic Web Basics 81
Eyal Oren and Simon Schenk
6.1 The Semantic Web 82
6.2 RDF 83
6.2.1 RDF Graphs 86
6.2.2 Named Graphs 87
6.2.3 RDF Semantics 88
6.3 RDF Schema 90
6.4 Data Models 93
6.5 Linked Data Principles 94
6.5.1 Dereferencing Using Basic Web Look-up 95
6.5.2 Dereferencing Using HTTP 303 Redirects 95
6.6 Development Practicalities 96
6.6.1 Data Stores 97
6.6.2 Toolkits 97
7 Semantic Web Languages 99
Antoine Isaac, Simon Schenk and Ansgar Scherp
7.1 The Need for Ontologies on the Semantic Web 100
7.2 Representing Ontological Knowledge Using OWL 100
7.2.1 OWL Constructs and OWL Syntax 100
7.2.2 The Formal Semantics of OWL and its Different Layers 102
7.2.3 Reasoning Tasks 106
7.2.4 OWL Flavors 107
7.2.5 Beyond OWL 107
7.3 A Language to Represent Simple Conceptual Vocabularies: SKOS 108
7.3.1 Ontologies versus Knowledge Organization Systems 108
7.3.2 Representing Concept Schemes Using SKOS 109
7.3.3 Characterizing Concepts beyond SKOS 111
7.3.4 Using SKOS Concept Schemes on the Semantic Web 112
7.4 Querying on the Semantic Web 113
7.4.1 Syntax 113
7.4.2 Semantics 118
7.4.3 Default Negation in SPARQL 123
7.4.4 Well-Formed Queries 124
7.4.5 Querying for Multimedia Metadata 124
7.4.6 Partitioning Datasets 126
7.4.7 Related Work 127
8 Multimedia Metadata Standards 129
Peter Schallauer, Werner Bailer, Raphaël Troncy and Florian Kaiser
8.1 Selected Standards 130
8.1.1 MPEG-7 130
8.1.2 EBU P_Meta 132
8.1.3 SMPTE Metadata Standards 133
8.1.4 Dublin Core 133
8.1.5 TV-Anytime 134
8.1.6 METS and VRA 134
8.1.7 MPEG-21 135
8.1.8 XMP, IPTC in XMP 135
8.1.9 EXIF 136
8.1.10 DIG35 137
8.1.11 ID3/MP3 137
8.1.12 NewsML G2 and rNews 138
8.1.13 W3C Ontology for Media Resources 138
8.1.14 EBUCore 139
8.2 Comparison 140
8.3 Conclusion 143
9 The Core Ontology for Multimedia 145
Thomas Franz, Raphaël Troncy and Miroslav Vacura
9.1 Introduction 145
9.2 A Multimedia Presentation for Granddad 146
9.3 Related Work 149
9.4 Requirements for Designing a Multimedia Ontology 150
9.5 A Formal Representation for MPEG-7 150
9.5.1 DOLCE as Modeling Basis 151
9.5.2 Multimedia Patterns 151
9.5.3 Basic Patterns 155
9.5.4 Comparison with Requirements 157
9.6 Granddad’s Presentation Explained by COMM 157
9.7 Lessons Learned 159
9.8 Conclusion 160
10 Knowledge-Driven Segmentation and Classification 163
Thanos Athanasiadis, Phivos Mylonas, Georgios Th. Papadopoulos, Vasileios Mezaris, Yannis Avrithis, Ioannis Kompatsiaris and Michael G. Strintzis
10.1 Related Work 164
10.2 Semantic Image Segmentation 165
10.2.1 Graph Representation of an Image 165
10.2.2 Image Graph Initialization 165
10.2.3 Semantic Region Growing 167
10.3 Using Contextual Knowledge to Aid Visual Analysis 170
10.3.1 Contextual Knowledge Formulation 170
10.3.2 Contextual Relevance 173
10.4 Spatial Context and Optimization 177
10.4.1 Introduction 177
10.4.2 Low-Level Visual Information Processing 177
10.4.3 Initial Region-Concept Association 178
10.4.4 Final Region-Concept Association 179
10.5 Conclusions 181
11 Reasoning for Multimedia Analysis 183
Nikolaos Simou, Giorgos Stoilos, Carsten Saathoff, Jan Nemrava, Vojt¡ech Sv´atek, Petr Berka and Vassilis Tzouvaras
11.1 Fuzzy DL Reasoning 184
11.1.1 The Fuzzy DL f-SHIN 184
11.1.2 The Tableaux Algorithm 185
11.1.3 The FiRE Fuzzy Reasoning Engine 187
11.2 Spatial Features for Image Region Labeling 192
11.2.1 Fuzzy Constraint Satisfaction Problems 192
11.2.2 Exploiting Spatial Features Using Fuzzy
Constraint Reasoning 193
11.3 Fuzzy Rule Based Reasoning Engine 196
11.4 Reasoning over Resources Complementary to Audiovisual Streams 201
12 Multi-Modal Analysis for Content Structuring and Event Detection 205
Noel E. O’Connor, David A. Sadlier, Bart Lehane, Andrew Salway, Jan Nemrava and Paul Buitelaar
12.1 Moving Beyond Shots for Extracting Semantics 206
12.2 A Multi-Modal Approach 207
12.3 Case Studies 207
12.4 Case Study 1: Field Sports 208
12.4.1 Content Structuring 208
12.4.2 Concept Detection Leveraging Complementary Text Sources 213
12.5 Case Study 2: Fictional Content 214
12.5.1 Content Structuring 215
12.5.2 Concept Detection Leveraging Audio Description 219
12.6 Conclusions and Future Work 221
13 Multimedia Annotation Tools 223
Carsten Saathoff, Krishna Chandramouli, Werner Bailer, Peter Schallauer and Raphaël Troncy
13.1 State of the Art 224
13.2 SVAT: Professional Video Annotation 225
13.2.1 User Interface 225
13.2.2 Semantic Annotation 228
13.3 KAT: Semi-automatic, Semantic Annotation of Multimedia Content 229
13.3.1 History 231
13.3.2 Architecture 232
13.3.3 Default Plugins 234
13.3.4 Using COMM as an Underlying Model: Issues and Solutions 234
13.3.5 Semi-automatic Annotation: An Example 237
13.4 Conclusions 239
14 Information Organization Issues in Multimedia Retrieval Using Low-Level Features 241
Frank Hopfgartner, Reede Ren, Thierry Urruty and Joemon M. Jose
14.1 Efficient Multimedia Indexing Structures 242
14.1.1 An Efficient Access Structure for Multimedia Data 243
14.1.2 Experimental Results 245
14.1.3 Conclusion 249
14.2 Feature Term Based Index 249
14.2.1 Feature Terms 250
14.2.2 Feature Term Distribution 251
14.2.3 Feature Term Extraction 252
14.2.4 Feature Dimension Selection 253
14.2.5 Collection Representation and Retrieval System 254
14.2.6 Experiment 256
14.2.7 Conclusion 258
14.3 Conclusion and Future Trends 259
Acknowledgement 259
15 The Role of Explicit Semantics in Search and Browsing 261
Michiel Hildebrand, Jacco van Ossenbruggen and Lynda Hardman
15.1 Basic Search Terminology 261
15.2 Analysis of Semantic Search 262
15.2.1 Query Construction 263
15.2.2 Search Algorithm 265
15.2.3 Presentation of Results 267
15.2.4 Survey Summary 269
15.3 Use Case A: Keyword Search in ClioPatria 270
15.3.1 Query Construction 270
15.3.2 Search Algorithm 270
15.3.3 Result Visualization and Organization 273
15.4 Use Case B: Faceted Browsing in ClioPatria 274
15.4.1 Query Construction 274
15.4.2 Search Algorithm 276
15.4.3 Result Visualization and Organization 276
15.5 Conclusions 277
16 Conclusion 279
Raphaël Troncy, Benoit Huet and Simon Schenk
References 281
Author Index 301
Subject Index 303
