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.
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.
Foreword xi List of Figures xiii List of Tables xvii List of
Contributors xix 1 Introduction 1 Raphael 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, Zeljko 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, Gael 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, Gael
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, Raphael 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, Raphael 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, Vojtech 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 Raphael 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 Raphael Troncy, Benoit Huet and
Simon Schenk References 281 Author Index 301 Subject Index 303
