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1 edition of Efficient caption-based retrieval of multimedia information found in the catalog.

Efficient caption-based retrieval of multimedia information

Neil C. Rowe

Efficient caption-based retrieval of multimedia information

by Neil C. Rowe

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  • 27 Currently reading

Published by Naval Postgraduate School, Available from National Technical Information Service in Monterey, Calif, Springfield, Va .
Written in English

    Subjects:
  • INFORMATION RETRIEVAL

  • About the Edition

    We describe MARIE-1 and MARIE-2, information retrieval systems for multimedia data. They exploit captions on the data and perform natural-language processing of them and English retrieval requests. Some content analysis of the data is also Performed to obtain additional descriptive information. The key to getting this approach to work is sufficient fast processing. We achieve this by decomposing the problem into information filters and applying a new theory of optimal information filtering which we have developed.

    Edition Notes

    Other titlesNPS-CS-94-008.
    Statementby Neil C. Rowe
    ContributionsNaval Postgraduate School (U.S.). Dept. of Computer Science
    The Physical Object
    Pagination14 p. :
    Number of Pages14
    ID Numbers
    Open LibraryOL25510623M

      Abstract: The need for Multimedia Indexing and Retrieval (MIR) is rising because of huge amount of videos are producing day by day. This requires techniques for indexing and retrieving multimedia information. This paper surveys the multimedia indexing and retrieval techniques. Introducing Multimedia Information Retrieval to libraries The paper aims to introduce libraries to the view that operating within the terms of traditional Information Retrieval (IR), only through textual language, is limitative, and that considering broader criteria, as those of Multimedia Information Retrieval (MIR), is necessary.

    Semantic concept-based query expansion and re-ranking for multimedia retrieval. In Proceedings of the 15th International Conference on Multimedia. ACM, New York, Google Scholar Digital Library; Natsev, A. P., Naphade, M. R., and Tešić, J. Learning the semantics of multimedia queries and concepts from a small number of examples. Content Based Multimedia Information Retrieval To Support Digital Libraries Mohammad Nabil Almunawar Faculty of Business, Economics & Policy Studies Universiti Brunei Darussalam e-mail: [email protected] Abstract Content-based multimedia information retrieval is an interesting research area since it.

    modalities (e.g., auditory, visual, haptic/gestural). This book focuses on tools and techniques that support efficient and effective indexing, browsing, retrieval, interaction with and visualization of multimedia. Multimedia digital libraries which incorporate text, graphics, audio, and video are central to. Overview The goals of the MARS project is to design and develop an integrated multimedia information retrieval and database management infrastructure, entitled Multimedia Analysis and Retrieval System (MARS), that supports multimedia information as first-class objects suited for storage and retrieval based on their content. Specifically, research in the MARS project is categorized into the.


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Efficient caption-based retrieval of multimedia information by Neil C. Rowe Download PDF EPUB FB2

We describe MARIE-1 and MARIE-2, information retrieval systems for multimedia data. They exploit captions on the data and perform natural-language processing of them and English retrieval : Neil Rowe. Efficient caption-based retrieval of multimedia information.

By Neil C. Rowe. Download PDF (1 MB) Abstract. Approved for public release; distribution is describe MARIE-1 and MARIE-2, information retrieval systems for multimedia data. They exploit captions on the data and perform natural-language processing of them and English Author: Neil C.

Rowe. Retrieval of Efficient caption-based retrieval of multimedia information book data is different from retrieval of structured data. A key problem in multimedia databases is search, and the proposed solutions to the problem of multimedia information retrieval span a rather wide spectrum of topics outside the traditional database area, ranging from information retrieval and human–computer interaction to computer vision and pattern recognition.

Information retrieval (IR) is the activity of obtaining information system resources that are relevant to an information need from a collection of those resources.

Searches can be based on full-text or other content-based indexing. Information retrieval is the science of searching for information in a document, searching for documents themselves, and also searching for the metadata that. This novel content-based concept of information handling needs to be integrated with more traditional semantics.

Multimedia Information Retrieval focuses on the tools of processing and searching applicable to the content-based management of new multimedia documents. Translated from Italian by Giles Smith, the book is divided into two parts.

At its very core multimedia information retrieval means the process of searching for and finding multimedia documents; the corresponding research field is concerned with building the best possible multimedia search engines. The intriguing bit here is that the query itself can be a multimedia excerpt: For example, when you walk around in an unknown place and stumble across an interesting.

The book concludes with an overview of state-of-the-art research projects in the area of multimedia information retrieval, which gives an indication of the research and development trends and, thereby, a glimpse of the future world. Table of Contents: What is Multimedia Information Retrieval.

the information retrieval. zFeature dimension reduction – High dimensional features zIndexing and retrieval techniques for the feature space Similarity measurement on query features zHow to integrate various indexing and retrieval techniques for effective retrieval of multimedia documents.

zSame as DBMS, efficient search is the main performance. Textual information embedded in multimedia can provide a vital tool for indexing and retrieval.

Text extraction process has many inherent problems due to the. MS ' Workshop on multimedia information retrieval on The many faces of multimedia semantics An efficient manual image annotation approach based on tagging and browsing Pages 13– Abstract: Semantic filtering and retrieval of multimedia content is crucial for efficient use of the multimedia data repositories.

Video query by semantic keywords is one of the most difficult problems in multimedia data retrieval. The difficulty lies in the mapping between low-level video representation and high-level semantics. Buy Organization and Retrieval of Multimedia Information by M.

Burke (ISBN: ) from Amazon's Book Store. Free UK delivery on eligible orders. Free UK delivery on eligible orders. Time-based method of human-computer interaction for controlling storage and retrieval of multimedia information.

Content-Based Multimedia Retrieval: /ch In the past decade, there has been rapid growth in the use of digital media, such as images, video. The book concludes with an overview of state-of-the-art research projects in the area of multimedia information retrieval, which gives an indication of the research and development trends and, thereby, a glimpse of the future world.

Multimedia Representation: /ch In recent years, the rapid expansion of multimedia applications, partly due to the exponential growth of. information storage and retrieval, the systematic process of collecting and cataloging data so that they can be located and displayed on request.

Computers and data processing techniques have made possible the high-speed, selective retrieval of large amounts of information for government, commercial, and academic purposes.

The University of Glasgow is a registered Scottish charity: Registration Number SC School of Computing Science. Contact us; Sitemap; Legal. Accessibility statement; Freedom. Multimedia information retrieval (MMIR or MIR) is a research discipline of computer science that aims at extracting semantic information from multimedia data sources.

[failed verification] Data sources include directly perceivable media such as audio, image and video, indirectly perceivable sources such as text, semantic descriptions, biosignals as well as not perceivable sources such as.

This book will provide readers with an up-to-date and comprehensive picture of cutting edge technologies in multimedia information retrieval and management, which directly affect our industry, economy and social life The book is divided into two major parts: Technological Fundamentals which covers the core theories of the area; and Applications.

Multimedia data mining is an interdisciplinary field that integrates image processing and understanding, computer vision, data mining, and pattern recognition. Issues in multimedia data mining include content-based retrieval and similarity search, and generalization and multidimensional analysis.

Multimedia data cubes contain additional. Abstract. Learning a good ranking function plays a key role for many applications including the task of (multimedia) information retrieval. While there are a few rank learning methods available, most of them need to explicitly model the relations between every pair of relevant and irrelevant documents, and thus result in an expensive training process for large collections.

This book explains what is possible in multimedia information retrieval today and what is not. We introduce the basic concepts, explain why the first step is always summarization and the second classification, which is essentially applying human understanding of Reviews: 3.Content-based multimedia information retrieval is an interesting research area since it allows retrieval based on inherent characteristic of multimedia objects.

For example retrieval based on.