Large Scale Multimedia Retrieval And Evaluation PDF Download
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| Author | : John Paquette |
| Publisher | : Createspace Independent Publishing Platform |
| Total Pages | : 130 |
| Release | : 2017-05-09 |
| Genre | : |
| ISBN | : 9781981876488 |
Download Large-Scale Multimedia Retrieval and Evaluation Book in PDF, ePub and Kindle
The papers cover topics ranging from theoretical work to practical implementations and its evaluation, most of them dealing with audio or music media. They are organized in topical sections on evaluation and user studies, audio and music, image retrieval, and similarity and music.
| Author | : Marcin Detyniecki |
| Publisher | : Springer |
| Total Pages | : 150 |
| Release | : 2013-03-15 |
| Genre | : Computers |
| ISBN | : 3642374255 |
Download Adaptive Multimedia Retrieval. Large-Scale Multimedia Retrieval and Evaluation Book in PDF, ePub and Kindle
This book constitutes the refereed post-proceedings of the 9th International Conference on Adaptive Multimedia Retrieval, AMR 2011, held in Barcelona, Spain, in July 2011. The 9 revised full papers and the invited contribution presented were carefully reviewed and selected from numerous submissions. The papers cover topics ranging from theoretical work to practical implementations and its evaluation, most of them dealing with audio or music media. They are organized in topical sections on evaluation and user studies, audio and music, image retrieval, and similarity and music.
| Author | : Stefanos Vrochidis |
| Publisher | : John Wiley & Sons |
| Total Pages | : 421 |
| Release | : 2019-03-18 |
| Genre | : Technology & Engineering |
| ISBN | : 1119377005 |
Download Big Data Analytics for Large-Scale Multimedia Search Book in PDF, ePub and Kindle
A timely overview of cutting edge technologies for multimedia retrieval with a special emphasis on scalability The amount of multimedia data available every day is enormous and is growing at an exponential rate, creating a great need for new and more efficient approaches for large scale multimedia search. This book addresses that need, covering the area of multimedia retrieval and placing a special emphasis on scalability. It reports the recent works in large scale multimedia search, including research methods and applications, and is structured so that readers with basic knowledge can grasp the core message while still allowing experts and specialists to drill further down into the analytical sections. Big Data Analytics for Large-Scale Multimedia Search covers: representation learning, concept and event-based video search in large collections; big data multimedia mining, large scale video understanding, big multimedia data fusion, large-scale social multimedia analysis, privacy and audiovisual content, data storage and management for big multimedia, large scale multimedia search, multimedia tagging using deep learning, interactive interfaces for big multimedia and medical decision support applications using large multimodal data. Addresses the area of multimedia retrieval and pays close attention to the issue of scalability Presents problem driven techniques with solutions that are demonstrated through realistic case studies and user scenarios Includes tables, illustrations, and figures Offers a Wiley-hosted BCS that features links to open source algorithms, data sets and tools Big Data Analytics for Large-Scale Multimedia Search is an excellent book for academics, industrial researchers, and developers interested in big multimedia data search retrieval. It will also appeal to consultants in computer science problems and professionals in the multimedia industry.
| Author | : Edward Y. Chang |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 300 |
| Release | : 2011-08-27 |
| Genre | : Computers |
| ISBN | : 3642204295 |
Download Foundations of Large-Scale Multimedia Information Management and Retrieval Book in PDF, ePub and Kindle
"Foundations of Large-Scale Multimedia Information Management and Retrieval: Mathematics of Perception" covers knowledge representation and semantic analysis of multimedia data and scalability in signal extraction, data mining, and indexing. The book is divided into two parts: Part I - Knowledge Representation and Semantic Analysis focuses on the key components of mathematics of perception as it applies to data management and retrieval. These include feature selection/reduction, knowledge representation, semantic analysis, distance function formulation for measuring similarity, and multimodal fusion. Part II - Scalability Issues presents indexing and distributed methods for scaling up these components for high-dimensional data and Web-scale datasets. The book presents some real-world applications and remarks on future research and development directions. The book is designed for researchers, graduate students, and practitioners in the fields of Computer Vision, Machine Learning, Large-scale Data Mining, Database, and Multimedia Information Retrieval. Dr. Edward Y. Chang was a professor at the Department of Electrical & Computer Engineering, University of California at Santa Barbara, before he joined Google as a research director in 2006. Dr. Chang received his M.S. degree in Computer Science and Ph.D degree in Electrical Engineering, both from Stanford University.
| Author | : Lei Zhu |
| Publisher | : Springer Nature |
| Total Pages | : 217 |
| Release | : 2023-08-04 |
| Genre | : Computers |
| ISBN | : 3031372913 |
Download Multi-modal Hash Learning Book in PDF, ePub and Kindle
This book systemically presents key concepts of multi-modal hashing technology, recent advances on large-scale efficient multimedia search and recommendation, and recent achievements in multimedia indexing technology. With the explosive growth of multimedia contents, multimedia retrieval is currently facing unprecedented challenges in both storage cost and retrieval speed. The multi-modal hashing technique can project high-dimensional data into compact binary hash codes. With it, the most time-consuming semantic similarity computation during the multimedia retrieval process can be significantly accelerated with fast Hamming distance computation, and meanwhile the storage cost can be reduced greatly by the binary embedding. The authors introduce the categorization of existing multi-modal hashing methods according to various metrics and datasets. The authors also collect recent multi-modal hashing techniques and describe the motivation, objective formulations, and optimization steps for context-aware hashing methods based on the tag-semantics transfer.
| Author | : Ivan Giangreco |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2018 |
| Genre | : |
| ISBN | : |
Download Database Support for Large-scale Multimedia Retrieval Book in PDF, ePub and Kindle
| Author | : Henk M. Blanken |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 384 |
| Release | : 2007-08-13 |
| Genre | : Computers |
| ISBN | : 3540728953 |
Download Multimedia Retrieval Book in PDF, ePub and Kindle
Based on more than 10 years of teaching experience, Blanken and his coeditors have assembled all the topics that should be covered in advanced undergraduate or graduate courses on multimedia retrieval and multimedia databases. The single chapters of this textbook explain the general architecture of multimedia information retrieval systems and cover various metadata languages such as Dublin Core, RDF, or MPEG. The authors emphasize high-level features and show how these are used in mathematical models to support the retrieval process. For each chapter, there’s detail on further reading, and additional exercises and teaching material is available online.
| Author | : Peter Schäuble |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 196 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 1461561639 |
Download Multimedia Information Retrieval Book in PDF, ePub and Kindle
Multimedia Information Retrieval: Content-Based Information Retrieval from Large Text and Audio Databases addresses the future need for sophisticated search techniques that will be required to find relevant information in large digital data repositories, such as digital libraries and other multimedia databases. Because of the dramatically increasing amount of multimedia data available, there is a growing need for new search techniques that provide not only fewer bits, but also the most relevant bits, to those searching for multimedia digital data. This book serves to bridge the gap between classic ranking of text documents and modern information retrieval where composite multimedia documents are searched for relevant information. Multimedia Information Retrieval: Content-Based Information Retrieval from Large Text and Audio Databases begins to pave the way for speech retrieval; only recently has the search for information in speech recordings become feasible. This book provides the necessary introduction to speech recognition while discussing probabilistic retrieval and text retrieval, key topics in classic information retrieval. The book then discusses speech retrieval, which is even more challenging than retrieving text documents because word boundaries are difficult to detect, and recognition errors affect the retrieval effectiveness. This book also addresses the problem of integrating information retrieval and database functions, since there is an increasing need for retrieving information from frequently changing data collections which are organized and managed by a database system. Multimedia Information Retrieval: Content-Based Information Retrieval from Large Text and Audio Databases serves as an excellent reference source and may be used as a text for advanced courses on the topic.
| Author | : Michael Christel |
| Publisher | : Springer Nature |
| Total Pages | : 73 |
| Release | : 2022-05-31 |
| Genre | : Computers |
| ISBN | : 3031022580 |
Download Automated Metadata in Multimedia Information Systems Book in PDF, ePub and Kindle
Improvements in network bandwidth along with dramatic drops in digital storage and processing costs have resulted in the explosive growth of multimedia (combinations of text, image, audio, and video) resources on the Internet and in digital repositories. A suite of computer technologies delivering speech, image, and natural language understanding can automatically derive descriptive metadata for such resources. Difficulties for end users ensue, however, with the tremendous volume and varying quality of automated metadata for multimedia information systems. This lecture surveys automatic metadata creation methods for dealing with multimedia information resources, using broadcast news, documentaries, and oral histories as examples. Strategies for improving the utility of such metadata are discussed, including computationally intensive approaches, leveraging multimodal redundancy, folding in context, and leaving precision-recall tradeoffs under user control. Interfaces building from automatically generated metadata are presented, illustrating the use of video surrogates in multimedia information systems. Traditional information retrieval evaluation is discussed through the annual National Institute of Standards and Technology TRECVID forum, with experiments on exploratory search extending the discussion beyond fact-finding to broader, longer term search activities of learning, analysis, synthesis, and discovery. Table of Contents: Evolution of Multimedia Information Systems: 1990-2008 / Survey of Automatic Metadata Creation Methods / Refinement of Automatic Metadata / Multimedia Surrogates / End-User Utility for Metadata and Surrogates: Effectiveness, Efficiency, and Satisfaction
| Author | : Bharadwaj Veeravalli |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 289 |
| Release | : 2006-10-11 |
| Genre | : Computers |
| ISBN | : 0387296751 |
Download Distributed Multimedia Retrieval Strategies for Large Scale Networked Systems Book in PDF, ePub and Kindle
Several works on multimedia storage appear in literature today, but very little if any, have been devoted to handling long duration video retrieval, over large scale networks. Distributed retrieval of multimedia documents, especially the long duration documents, is an imperative step in rendering high-quality, high-fidelity, and cost-effective services for network service providers. Distributed Multimedia Retrieval Strategies for Large Scale Networked Systems presents an up-to-date research status in the domain of distributed video retrieval. This professional book will include several different techniques that are in place for long duration video retrieval. An experimentally tested technology under the JINI platform, demonstrates a practical working system which serves as a feasibility study, as well as the first step in realizing such a technology.
