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Multimedia database

About: Multimedia database is a research topic. Over the lifetime, 1404 publications have been published within this topic receiving 19856 citations. The topic is also known as: Multimedia database & MMDB.


Papers
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Patent
02 Feb 2007
TL;DR: In this article, a system and method for searching multimedia databases using a pictorial language, input via an iconic interface and making use of trained ontologies, is presented, where the result images are returned to the user in order of their relevance to the query.
Abstract: A system and method for searching multimedia databases using a pictorial language, input via an iconic interface and making use of trained ontologies, i.e., trained data models. An iconic graphic user interface (GUI) allows a user to specify a pictorial query that may include one or more one or more key-images and optional text input. Similarities between the query key-images and images in a multimedia database based on a pictorial edit distance are used to select the images that are the closest match to the query. The result images are returned to the user in order of their relevance to the query.

34 citations

Proceedings ArticleDOI
12 Aug 2007
TL;DR: A new max margin learning approach called Enhanced Max Margin Learning (EMML) framework is developed and applied to the Berkeley Drosophila embryo image database, and the performance comparison with a state-of-the-art multimodal data mining method is reported.
Abstract: The problem of multimodal data mining in a multimedia database can be addressed as a structured prediction problem where we learn the mapping from an input to the structured and interdependent output variables. In this paper, built upon the existing literature on the max margin based learning, we develop a new max margin learning approach called Enhanced Max Margin Learning (EMML) framework. In addition, we apply EMML framework to developing an effective and efficient solution to the multimodal data mining problem in a multimedia database. The main contributions include: (1) we have developed a new max margin learning approach - the enhanced max margin learning framework that is much more efficient in learning with a much faster convergence rate, which is verified in empirical evaluations; (2) we have applied this EMML approach to developing an effective and efficient solution to the multimodal data mining problem that is highly scalable in the sense that the query response time is independent of the database scale, allowing facilitating a multimodal data mining querying to a very large scale multimedia database,and excelling many existing multimodal data mining methods in the literature that do not scale up at all; this advantage is also supported through the complexity analysis as well as empirical evaluations against a state-of-the-art multimodal data mining method from the literature. While EMML is a general framework, for the evaluation purpose, we apply it to the Berkeley Drosophila embryo image database, and report the performance comparison with a state-of-the-art multimodal data mining method.

34 citations

Proceedings ArticleDOI
18 Apr 2011
TL;DR: It is shown how the distance's inherent parameters determine the indexability and the relationship between effectiveness and efficiency on numerous image databases is analyzed and analyzed.
Abstract: The Signature Quadratic Form Distance has been introduced as an adaptive similarity measure coping with flexible content representations of various multimedia data. Although the Signature Quadratic Form Distance has shown good retrieval performance with respect to their qualities of effectiveness and efficiency, its applicability to index structures remains a challenging issue due to its dynamic nature. In this paper, we investigate the indexability of the Signature Quadratic Form Distance regarding metric access methods. We show how the distance's inherent parameters determine the indexability and analyze the relationship between effectiveness and efficiency on numerous image databases.

33 citations

Proceedings ArticleDOI
05 Aug 1998
TL;DR: The similarity measures of video content are investigated and a series of similarity measures based on the similarity of frame sequence which take temporal ordering into consideration are proposed.
Abstract: Video retrieval is one of the important design issues of multimedia database management systems. The distinguished features of video retrieval lie in the similarity measures and content-based retrieval. Most research on content-based video retrieval represents the content of video as a set of frames leaving out the temporal ordering of frames in the shot. In this paper, the similarity measures of video content are investigated. We propose a series of similarity measures based on the similarity of frame sequence which take temporal ordering into consideration. The corresponding algorithms are also presented. The effectiveness of the developed similarity measures measured by precision and recall is also described.

33 citations

Book
01 Jan 2003
TL;DR: This book discusses the real-time nature of Multimedia data, and the Semantic Nature ofMultimedia Data, and some of the techniques used to design and implement these systems.
Abstract: Contents 1 Introduction to Multimedia Databases 1.1 Introduction 1.2 What is Essential about Database Systems? 1.3 What is Different about Multimedia Data? 1.4 Multimedia Applications 1.5 What is in the Rest of the Book? 2 Multimedia Data 2.1 Multimedia Data Size 2.2 Real-time Nature of Multimedia 2.3 Why is the Semantic Nature of Multimedia Data a Problem? 2.4 Summary of Chapter 3 The Human Sensory System and Multimedia 3.1 Introduction - Human Information Processing 3.2 Human Brain and Multimedia Information 3.3 The Senses 3.4 Converting Data into Sensory Perception 3.5 Summary of Chapter 4 An Introduction to SQL and Multimedia 4.1 Introduction to SQL 4.2 Methods Using PL/SQL Stored Procedures 4.3 Manipulating Large Objects 4.4 Summary of Chapter 5 Querying Multimedia Data 5.1 Introduction 5.2 Manipulating Multimedia Data 5.3 What is the Classification Problem? 5.4 Summary of Chapter 6 Modeling Multimedia Databases 6.1 Issues of Designing Multimedia Database Management Systems 6.2 Semantic Data Modeling 6.3 Object-oriented Design 6.4 Object Methods 6.5 Object-relational Approach 6.6 Notes 7 Using Multimedia Metadata 7.1 Introduction 7.2 Classifying Metadata 7.3 Generating and Extracting Metadata 7.4 The Role of Metadata Standards 7.5 Digital Rights Management 7.6 Domain-dependent Metadata 7.7 Developing Ontologies 7.8 Summary of Chapter 8 Multimedia Database Architecture and Performance 8.1 Introduction to Multimedia Architecture Requirements 8.2 Performance Issues in Specific Implementations 8.3 Content Management 8.4 Summary of Chapter 9 Multimedia and the Internet 9.1 Introduction 9.2 Delivery of Multimedia Data 9.3 Media Streams 9.4 Network Protocols 9.5 User Datagram Protocol 9.6 Quality-of-service Issues - Internet Service Models 9.7 Packets and Datagrams - Sequence and Loss 9.8 Network Architecture 9.9 Requirements of Applications Involving Multicasting and Interactivity 9.10 Sumamry of Chapter 10 Dealing with Text Databases 10.1 Introduction 10.2 Querying Character Data Using SQL 10.3 Statistical Methods for Text Analysis 10.4 Querying Multimedia Text 10.5 Content-dependent Metadata 10.6 Indexing Technologies for Text 10.7 Summary of Chapter 11 Dealing with Image Databases 11.1 Introduction 11.2 Technologies for Image Processing 11.3 The Role of Feature Extraction 11.4 Retrieval Methods 11.5 Image Analysis and Object Recognition 11.6 Image Classification 11.7 Image Database Software 11.8 Developing Image Media Databases 11.9 Summary of Chapter 12 Dealing with Video Databases 12.1 Introduction 12.2 Video Analysis and Segmentation 12.3 Storage of Video Objects 12.4 Disk Scheduling 12.5 Dealing with Moving Images 12.6 Metadata for Speech 12.7 Metadata for Video 12.8 Manipulating Video Data 12.9 Video Query Process 12.10 Video Applications 12.11 Summary of Chapter Appendices Appendix A Normalization and Relational Databases Appendix B Metadata Standards Appendix C SQL Notes Appendix D Acronyms Appendix E Glossary Appendix F References Index Dunckley: Multimedia Databases Running heads Introduction to Multimedia Databases Introduction What is Essential about Database Systems? What is Different about Multimedia Data? Multimedia Applications What is in the Rest of the Book? Multimedia Data Multimedia Data Size Real-time Nature of Multimedia The Semantic Nature of Multimedia Data Summary of Chapter The Human Sensory System and Multimedia Introduction - Human Information Processing Human Brain and Multimedia Information The Senses Converting Data into Sensory Perception Summary of Chapter An Introduction to SQL and Multimedia Introduction to SQL Methods Using PL/SQL Stored Procedures Manipulating Large Objects Summary of Chapter Querying Multimedia Data Introduction Manipulating Multimedia Data What is the Classification Problem? Summary of Chapter Modeling Multimedia Databases Designing Multimedia Database Management Systems Semantic Data Modeling Object-oriented Design Object Methods Object-relational Approach Notes Using Multimedia Metadata Introduction Classifying Metadata Generating and Extracting Metadata The Role of Metadata Standards Digital Rights Management Domain-dependent Metadata Developing Ontologies Summary of Chapter Multimedia Database Architecture and Performance Introduction to Multimedia Architecture Requirements Performance Issues in Specific Implementations Content Management Summary of Chapter Multimedia and the Internet Introduction Delivery of Multimedia Data Media Streams Network Protocols User Datagram Protocol Quality-of-service Issues - Internet Service Models Packets and Datagrams - Sequence and Loss Network Architecture Applications Involving Multicasting and Interactivity Sumamry of Chapter Dealing with Text Databases Introduction Querying Character Data Using SQL Statistical Methods for Text Analysis Querying Multimedia Text Content-dependent Metadata Indexing Technologies for Text Summary of Chapter Dealing with Image Databases Introduction Technologies for Image Processing The Role of Feature Extraction Retrieval Methods Image Analysis and Object Recognition Image Classification Image Database Software Developing Image Media Databases Summary of Chapter Dealing with Video Databases Introduction Video Analysis and Segmentation Storage of Video Objects Disk Scheduling Dealing with Moving Images Metadata for Speech Metadata for Video Manipulating Video Data Video Query Process Video Applications Summary of Chapter Appendices Normalization and Relational Databases Metadata Standards SQL Notes Acronyms Glossary References Index Index

32 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20232
20224
202113
20206
201911
201824