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Towardsa Theory of Multimedia Database Systems Sherry Marcus and V.S. Subrahmanian1

1．Introduction1

2．Basic Ideas Underlying the Framework3

3．Media Instances4

3．1 The Clinton Example5

3．2 Examples of Media-Instances8

4．Indexing Structures and a Query Language for Multimedia Systems12

4．1 Frame-Based Query Language12

4．2 The Frame Data Structure15

4．3 Query Processing Algorithms21

4．4 Updates in Multimedia Databases22

5．1 Generation of Media Events = Query Processing24

5．Multimedia Presentations24

5．2 Synchronization = Constraint Solving27

5．3 Internal Synchronization28

5．4 Media Buffers28

6．Related Work29

7．Conclusions31

A Unified Approach to Data Modelling and Retrieval for a Class of Image Database Applications37

Venkat N Gudivada Vijay V Raghavan and Kanonluk Vanapipat37

1．Introduction37

2．Approaches to Image Data Modeling39

2．1 Terminology40

2．2 Conventional Data Models40

2．3 Image Processing/Graphics Systems with Database Functionality41

2．5 Extensible Data Models42

2．4 Extended Conventional Data Models42

3．Requirements Analysis of Application Areas43

3．1 A Taxonomy for Image Attributes43

2．6 Other Data Models43

3．2 A Taxonomy for Retrieval Types46

3．3 Art Galleries and Museums48

3．4 Interior Design48

3．5 Architectural Design49

3．6 Real Estate Marketing49

3．7 Face Information Retrieval50

4．Logical Representations51

5．Motivations for the Proposed Data Model52

6．1 Data Model53

6．An Overview of AIR Framework53

6．2 The Proposed DBMS Architecture57

7． Image Database Systems Based on AIR Model58

8．Image Retrieval Applications Based on the Prototype Implementation of AIR Framework61

8．1 Realtors Information System61

8．2 Face Information Retrieval System62

9．Research Issues in AIR Framework64

9．1 Query Interface64

9．2 Algorithms for RSC and RSS Queries67

9．3 Relevance Feedback Modeling and Improving Retrieval Effectiveness68

9．4 Elicitation of Semantic Attributes69

10．Conclusions and Future Direction70

A．Image Logical Structures74

The QBISM Medical Image DBMS Manish Arya, William Cody, Christos Faloutsos, Joel Richardson, and Art79

1．Introduction79

2．The Medical Application81

2．1 Problem Definition81

2．2 Data Characteristics82

3．Logical Design83

3．1 Data Types83

3．2 Spatial Operations83

3．3 Schema84

3．4 Queries85

4．Physical Database Design86

4．1 Representation of a VOLUME87

4．2 Representation of a REGION88

4．3 Conclusions89

5．System Issues89

5．1 Starburst Extensions89

5．2 System Architecture90

6．Performance Experiments93

6．1 Experimental Environment93

6．2 Single-study Queries94

6．3 Multi-study Queries96

6．4 Results from the Performance Experiments97

7．Conclusions and Future WorR97

A. Prasad Sistla and Clement Yu101

1．Introduction101

Retrieval of Pictures Using Approximate Matching101

2．Picture Representation102

3．User Interface103

4．Computation of Similarity Values105

4．1 Similarity Functions105

4．2 Object Similarities106

4．3 Similarities of Non-spatial Relationships107

4．4 Spatial Similarity Functions108

5．Conclusion111

Ink as a First- Class Datatype in Multimedia Databases Walid G. Aref, Daniel Barbara. and Daniel Lop113

1．Introduction113

2．Ink as First- Class Data114

2．1 Expressiveness of Ink115

2．2 Approximate Ink Matching116

3．Pictographic Naming117

3．1 Motivation118

3．2 A Pictographic Browser120

3．3 The Window Algorithm121

3．4 Hidden Markov Models122

4．The ScriptSearch Algorithm124

4．1 Definitions125

4．2 Approaches to Searching Ink126

4．3 Searching for Patterns in Noisy Text128

4．4 The ScriptSearch Algorithm129

4．5 Evaluation of ScriptSearch132

4．6 Experimental Results134

4．7 Discussion136

5．1 The HMM-Tree137

5．Searching Large Databases137

5．2 The Handwritten Trie149

5．3 Inter-character Strokes160

5．4 Performance160

6．Conclusions160

Indexing for Retrieval by Similarity H.V. Jagadish165

1．Introduction165

2．Shape Matching166

2．1 Rectangular Shape Covers167

2．2 Storage Structure169

2．3 Queries171

2．4 Approximate Match172

2．5 An Example177

2．6 Experiment178

3．Word Matching180

4．Discussion181

Filtering Distance Queries in Image Retrieval185

A. Belussi, E. Bertino. A. Biavasco, and S. Rizzo185

1．Introduction185

2．Spatial Access Methods and Image Retrieval187

2．1 Query Processor187

2．2 Image Objects and Spatial Predicates189

3．Snapshot191

3．1 Regular Grid with Locational Keys192

3．2 Clustering Technique194

3．3 Extensible Hashing195

3．4 Organization of Snapshot198

4．Filtering Metric Queries with Snapshot201

4．1 Search Algorithm202

4．2 Min Algorithm205

5．Optimization of Spatial Queries210

6．Conclusions and Future Work211

Stream-based Versus Structured Video Objects: Issues, Solutions, and Challenges Shahram Ghandehariza215

1．Introduction215

2．Stream-based Presentation217

2．1 Continuous Display218

2．2 Pipelining to Minimize Latency Time224

2．3 High Bandwidth Objects and Scalable Servers225

2．4 Challenges226

3．Structured Presentation227

3．1 Atomic Object Layer229

3．2 Composed Object Layer231

3．3 Challenges232

4．Conclusion235

The Storage and Retrieval of Continuous Media Data Banu Ozden. Rajeev Rastogi and Avi Silberschatz237

1．Introduction237

2．Retrieving Continuous Media Data238

3．Matrix-Based Allocation240

3．1 Storage Allocation241

3．2 Buffering243

3．3 Repositioning243

3．4 Implementation of VCR Operations244

4．Variable Disk Transfer Rates245

5．Horizontal Partitioning247

5．1 Storage Allocation248

5．2 Retrieval250

6．Vertical Partitioning250

6．1 Size of Buffers252

6．2 Data Retrieval255

7．Related Work257

8．Research Issues257

8．1 Load Balancing and Fault Tolerance Issues257

8．2 Storage Issues258

8．3 Data Retrieval Issues259

9．Concluding Remarks260

1．Introduction263

Querying Multimedia Databases in SQL Sherry Marcus263

2．Automobile Multimedia Database Example265

3．Logical Query Language269

4．Querying Multimedia Databases in SQL270

5．Expressing User Requests in SQL274

6．Conclusions276

Multimedia Authoring Systems Ross Cutler and Kasim Selcuk Candan279

1．Introduction279

2．Underlying Technology280

2．1 ODBC280

2．2 OLE281

2．3 DDE281

2．4 DLL281

3．Sample Application- Find-Movie282

2．5 MCI282

4．Multimedia Toolbook 3.0283

5．IconAuthor 6.0287

6．Director 4.0289

7．MAS s and Current Technology290

7．1 How to improve MAS s?291

7．2 How to Benefit from MAS s in Multimedia Research294

8．Conclusion295

Metadata for Building the Multimedia Patch Quilt Vipul Kashyap, Kshitij Shah, and Amit Sheth297

1．Introduction297

2．Characterization of the Ontology300

2．1 Terminological Commitments: Constructing an Ontology301

2．2 Controlled Vocabulary for Digital Media302

2．3 Better understanding of the query304

2．4 Ontology Guided Extraction of Metadata305

3．Construction and Design of Metadata306

3．1 Classification of Metadata307

3．2 Meta-correlation: The Key to Media-Independent Semantic Correlation309

3．3 Extractors for Metadata312

3．4 Storage of Metadata314

4．Association of Digital Media Data with Metadata315

4．1 Association of Metadata with Image Data315

4．2 Association of Symbolic Descriptions with Image Data316

4．3 Metadata for Multimedia Objects316

5．Conclusion317

Contributors321