|Statement||by Jenny Benois-Pineau, Frédéric Precioso, Matthieu Cord|
|Series||SpringerBriefs in Computer Science|
|Contributions||Precioso, Frédéric, Cord, Matthieu, SpringerLink (Online service)|
|The Physical Object|
|Format||[electronic resource] /|
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. The areas of societal activity, such as, video protection and security, also generate thousands and thousands of terabytes of visual content. This book provides a deep analysis and wide coverage of the very strong trend in computer vision and visual indexing and retrieval, covering such topics as incorporation of models of Human Visual attention into analysis and retrieval tasks. 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).Reviews: 2. Therefore, the representation, indexing and search techniques of image and video data has been a longstanding focus in research fields such as computer vision, multimedia analysis, and information retrieval, while serving as an emerging demand to improve the multimedia search services for big companies such as Google and Yahoo!.
Through mass-digitization projects and with the use of OCR technologies, digitized books are becoming available on the Web and in digital libraries. The unprecedented scale of these efforts, the unique characteristics of the digitized material as well as the unexplored possibilities of user interactions make full-text book search an exciting area of information retrieval (IR) [ ]. LIRE: Lucene Image Retrieval LIRE is a Java library that provides a simple way to retrieve images and photos based on color and texture characteristics. LIRE creates a Lucene index of image features for content based image retrieval (CBIR) using local and global state-of-the-art methods. Introduction to Information Retrieval. This is the companion website for the following book. Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze, Introduction to Information Retrieval, Cambridge University Press. You can order this book at CUP, at your local bookstore or on the best search term to use is the ISBN: Index construction. Hardware basics; Blocked sort-based indexing; Single-pass in-memory indexing; Distributed indexing; Dynamic indexing; Other types of indexes; References and further reading. Index compression. Statistical properties of terms in information retrieval. Heaps' law: Estimating the number of terms; Zipf's law: Modeling the.
In indexing decisions, concepts are recorded as data elements organised into easily accessible forms for retrieval. These records can appear in various forms, e.g. back-of-the-book indexes, indexes to catalogues and bibliographies, machine files, etc. The process of indexing has a close resemblance to the search process. Abstract. 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. Information Retrieval System Notes Pdf – IRS Notes Pdf book starts with the topics Classes of automatic indexing, Statistical indexing. Natural language, Concept indexing, Hypertext linkages,Multimedia Information Retrieval – Models and Languages – Data Modeling, Query Languages, lndexingand Searching. Here we view video retrieval from a different angle. We seek to construct a video Index to suit various users' needs. However, constructing a video Index is far more complex than constructing an index for books. For books, the form of an index is fixed (e.g., key words). For videos, the viewer's interests may cover a wide range.