Multimedia Semantics – Metadata, Analysis and Interaction

Dr. Raphael Troncy, Centre for Mathematics and Computer Science, Netherlands Raphael Troncy obtained his Master's thesis with honours in computer science at the University Joseph Fourier of Grenoble, France. He received his PhD with honours in 2004. His research interests include Semantic Web and Multimedia Technologies, Knowledge Representation, Ontology Modeling and Alignment. Raphael Troncy is an expert in audio visual metadata and in combining existing metadata standards (such as MPEG-7) with current Semantic Web technologies. Dr. Benoit Huet, Institut EURECOM, France Benoit Huet received his BSc degree in computer science and engineering from the Ecole Superieure de Technologie Electrique (Groupe ESIEE, France) in 1992. In 1993, he was awarded the MSc degree in Artificial Intelligence from the University of Westminster (UK) with distinction. He received his PhD degree in Computer Science from the University of York (UK). His research interests include computer vision, content-based retrieval, multimedia data mining and indexing (still and/or moving images) and pattern recognition. Simon Schenk, University of Koblenz-Landau, Germany Simon Schenk is a research and teaching assistant at the Information Systems and Semantic Web Group of University of Koblenz-Landau.Simon is working towards his PhD degree under the supervision of Professor Dr. Steffen Staab. Previously, he has worked as a consultant for Capgemini. Schenk studied at NORDAKADEMIE University of Applied Sciences, Germany and Karlstads Universitet, Sweden and received his diploma in Computer Science and Business Management from NORDAKADEMIE in 2004.

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