Visual Information Retrieval using Java and LIRE (Paperback)

Mathias Lux, Oge Marques

  • 出版商: Morgan & Claypool
  • 出版日期: 2013-01-01
  • 售價: $1,550
  • 貴賓價: 9.5$1,473
  • 語言: 英文
  • 頁數: 112
  • 裝訂: Paperback
  • ISBN: 1608459187
  • ISBN-13: 9781608459186
  • 相關分類: Java 程式語言
  • 海外代購書籍(需單獨結帳)

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商品描述

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

商品描述(中文翻譯)

視覺資訊檢索(Visual information retrieval,簡稱VIR)是一個活躍且充滿活力的研究領域,旨在提供組織、索引、註釋和從大型非結構化儲存庫中檢索視覺資訊(圖像和視頻)的方法。VIR的目標是按照與給定查詢相關性排序的匹配項目,這通常以示例圖像和/或一系列關鍵字的形式表達。在其早期(1995-2000年),研究工作主要由圖像和視頻處理社區貢獻的基於內容的方法主導。在過去的十年中,人們廣泛認識到,由於圖像的視覺內容與其語義解釋之間的不一致性所帶來的挑戰,也被稱為語義差距,需要巧妙地使用文本元數據(除了從圖像的像素內容中提取的信息)來使圖像和視頻檢索解決方案更加高效和有效。縮小(或至少縮小)語義差距的需求一直是當前VIR研究的推動力之一。此外,其他相關的研究問題和市場機會也開始出現,為計算機科學家和工程師提供了一系列令人興奮的問題。在這本介紹性的書中,我們專注於VIR問題的一個子集,其中媒體由圖像組成,索引和檢索方法基於這些圖像的像素內容,這種方法被稱為基於內容的圖像檢索(CBIR)。我們提供了CBIR概念、技術、算法和評估指標的實施導向概述。大多數章節都有使用Java編寫的示例,使用了Lucene(一個基於Java的開源索引和搜索實現)和LIRE(Lucene Image REtrieval,一個基於Java的開源CBIR庫)。目錄:引言/資訊檢索:選定的概念和技術/視覺特徵/索引視覺特徵/LIRE:一個可擴展的Java CBIR庫/結論。