Semantic-Based Visual Information Retrieval

Semantic-Based Visual Information Retrieval PDF Author: Zhang, Yu-Jin
Publisher: IGI Global
ISBN: 1599043726
Category : Computers
Languages : en
Pages : 368

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Book Description
"This book presents state-of-the-art advancements and developments in the field, and also brings a selection of techniques and algorithms about semantic-based visual information retrieval. It covers many critical issues, such as: multi-level representation and description, scene understanding, semantic modeling, image and video annotation, human-computer interaction, and more"--Provided by publisher.

Visual Information Retrieval

Visual Information Retrieval PDF Author: Alberto del Bimbo
Publisher: Princeton University Press
ISBN: 9781558606241
Category : Computers
Languages : en
Pages : 296

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Book Description
The increasing use of multimedia in computer applications has increased the relevance of visual databases. These databases now need new methods for archiving and retrieving information, and this text concentrates on meeting such a need.

Semantic-Based Visual Information Retrieval

Semantic-Based Visual Information Retrieval PDF Author: Zhang, Yu-Jin
Publisher: IGI Global
ISBN: 1599043726
Category : Computers
Languages : en
Pages : 368

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Book Description
"This book presents state-of-the-art advancements and developments in the field, and also brings a selection of techniques and algorithms about semantic-based visual information retrieval. It covers many critical issues, such as: multi-level representation and description, scene understanding, semantic modeling, image and video annotation, human-computer interaction, and more"--Provided by publisher.

Principles of Visual Information Retrieval

Principles of Visual Information Retrieval PDF Author: Michael S. Lew
Publisher: Springer Science & Business Media
ISBN: 1447137027
Category : Computers
Languages : en
Pages : 366

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Book Description
This text introduces the basic concepts and techniques in VIR. In doing so, it develops a foundation for further research and study. Divided into two parts, the first part describes the fundamental principles. A chapter is devoted to each of the main features of VIR, such as colour, texture and shape-based search. There is coverage of search techniques for time-based image sequences or videos, and an overview of how to combine all the basic features described and integrate them into the search process. The second part looks at advanced topics such as multimedia query. This book is essential reading for researchers in VIR, and final-year undergraduate and postgraduate students on courses such as Multimedia Information Retrieval, Multimedia Databases, and others.

Visual Information Retrieval Using Java and LIRE

Visual Information Retrieval Using Java and LIRE PDF Author: Lux Mathias
Publisher: Springer Nature
ISBN: 3031022823
Category : Mathematics
Languages : en
Pages : 96

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Book Description
Visual information retrieval (VIR) is an active and vibrant research area, which attempts at providing means for organizing, indexing, annotating, and retrieving visual information (images and videos) from large, unstructured repositories. The goal of VIR is to retrieve matches ranked by their relevance to a given query, which is often expressed as an example image and/or a series of keywords. During its early years (1995-2000), the research efforts were dominated by content-based approaches contributed primarily by the image and video processing community. During the past decade, it was widely recognized that the challenges imposed by the lack of coincidence between an image's visual contents and its semantic interpretation, also known as semantic gap, required a clever use of textual metadata (in addition to information extracted from the image's pixel contents) to make image and video retrieval solutions efficient and effective. The need to bridge (or at least narrow) the semantic gap has been one of the driving forces behind current VIR research. Additionally, other related research problems and market opportunities have started to emerge, offering a broad range of exciting problems for computer scientists and engineers to work on. In this introductory book, we focus on a subset of VIR problems where the media consists of images, and the indexing and retrieval methods are based on the pixel contents of those images -- an approach known as content-based image retrieval (CBIR). We present an implementation-oriented overview of CBIR concepts, techniques, algorithms, and figures of merit. Most chapters are supported by examples written in Java, using Lucene (an open-source Java-based indexing and search implementation) and LIRE (Lucene Image REtrieval), an open-source Java-based library for CBIR. Table of Contents: Introduction / Information Retrieval: Selected Concepts and Techniques / Visual Features / Indexing Visual Features / LIRE: An Extensible Java CBIR Library / Concluding Remarks

Visualization for Information Retrieval

Visualization for Information Retrieval PDF Author: Jin Zhang
Publisher: Springer Science & Business Media
ISBN: 3540751483
Category : Computers
Languages : en
Pages : 300

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Book Description
Information visualization offers a way to reveal hidden patterns in a visual presentation and allows users to seek information from a visual perspective. Readers of this book will gain an in-depth understanding of the current state of information retrieval visualization. They will be introduced to existing problems along with technical and theoretical findings. The book also provides practical details for the implementation of an information retrieval visualization system.

Textual and Visual Information Retrieval using Query Refinement and Pattern Analysis

Textual and Visual Information Retrieval using Query Refinement and Pattern Analysis PDF Author: S.G. Shaila
Publisher: Springer
ISBN: 9811325596
Category : Computers
Languages : en
Pages : 141

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Book Description
This book offers comprehensive coverage of information retrieval by considering both Text Based Information Retrieval (TBIR) and Content Based Image Retrieval (CBIR), together with new research topics. The approach to TBIR is based on creating a thesaurus, as well as event classification and detection. N-gram thesaurus generation for query refinement offers a new method for improving the precision of retrieval, while event classification and detection approaches aid in the classification and organization of information using web documents for domain-specific retrieval applications. In turn, with regard to content based image retrieval (CBIR) the book presents a histogram construction method, which is based on human visual perceptions of color. The book’s overarching goal is to introduce readers to new ideas in an easy-to-follow manner.

ImageCLEF

ImageCLEF PDF Author: Henning Müller
Publisher: Springer Science & Business Media
ISBN: 3642151817
Category : Computers
Languages : en
Pages : 554

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Book Description
The pervasive creation and consumption of content, especially visual content, is ingrained into our modern world. We’re constantly consuming visual media content, in printed form and in digital form, in work and in leisure pursuits. Like our cave– man forefathers, we use pictures to record things which are of importance to us as memory cues for the future, but nowadays we also use pictures and images to document processes; we use them in engineering, in art, in science, in medicine, in entertainment and we also use images in advertising. Moreover, when images are in digital format, either scanned from an analogue format or more often than not born digital, we can use the power of our computing and networking to exploit images to great effect. Most of the technical problems associated with creating, compressing, storing, transmitting, rendering and protecting image data are already solved. We use - cepted standards and have tremendous infrastructure and the only outstanding ch- lenges, apart from managing the scale issues associated with growth, are to do with locating images. That involves analysing them to determine their content, clas- fying them into related groupings, and searching for images. To overcome these challenges we currently rely on image metadata, the description of the images, - ther captured automatically at creation time or manually added afterwards.

Web Semantics for Textual and Visual Information Retrieval

Web Semantics for Textual and Visual Information Retrieval PDF Author: Singh, Aarti
Publisher: IGI Global
ISBN: 1522524843
Category : Computers
Languages : en
Pages : 311

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Book Description
Modern society exists in a digital era in which high volumes of multimedia information exists. To optimize the management of this data, new methods are emerging for more efficient information retrieval. Web Semantics for Textual and Visual Information Retrieval is a pivotal reference source for the latest academic research on embedding and associating semantics with multimedia information to improve data retrieval techniques. Highlighting a range of pertinent topics such as automation, knowledge discovery, and social networking, this book is ideally designed for researchers, practitioners, students, and professionals interested in emerging trends in information retrieval.

Multimedia Information Retrieval and Management

Multimedia Information Retrieval and Management PDF Author: David Feng
Publisher: Springer Science & Business Media
ISBN: 3662053004
Category : Technology & Engineering
Languages : en
Pages : 494

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Book Description
Everything you ever wanted to know about multimedia retrieval and management. This comprehensive book offers a full picture of the cutting-edge technologies necessary for a profound introduction to the field. Leading experts also cover a broad range of practical applications.

Visual Indexing and Retrieval

Visual Indexing and Retrieval PDF Author: Jenny Benois-Pineau
Publisher: Springer Science & Business Media
ISBN: 1461435889
Category : Computers
Languages : en
Pages : 113

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Book Description
The research in content-based indexing and retrieval of visual information such as images and video has become one of the most populated directions in the vast area of information technologies. Social networks such as YouTube, Facebook, FileMobile, and DailyMotion host and supply facilities for accessing a tremendous amount of professional and user generated data. The areas of societal activity, such as, video protection and security, also generate thousands and thousands of terabytes of visual content. This book presents the most recent results and important trends in visual information indexing and retrieval. It is intended for young researchers, as well as, professionals looking for an algorithmic solution to a problem.