Visual Information Retrieval (The Morgan Kaufmann Series In Multimedia Information And Systems)

Visual Information Retrieval (The Morgan Kaufmann Series in Multimedia Information and Systems)

Amazon.com ReviewVisual Information Retrieval, written by the head of the Systems and Information Department at the University of Florence in Italy, is a must-have for anyone developing systems for cataloging, searching, and retrieving visual-based data.A growing percentage of stored computer information is visual media, whether it's still images or video clips. This kind of data has a very different format and structure than text-based data, and cataloging, sorting, and searching non-text-based data presents a tremendous challenge to the contemporary database programmer.This is not a book for the casual programmer. It offers high-level suggestions on how to build the architecture for such systems, key theories on how to represent this kind of visual content, how to build similarity models, and indexing methods.It continues with examples of how to index and catalog still images based on color, texture, shape, and spatial relationship similarity.Chapter 6 details the problems and current solutions for content-based video retrieval. Detecting sharp transitions, how to analyze compressed and uncompressed streams, and gradual transition detection are just a few of the problems presented. The solutions presented are practical and fascinating.Visual Information Retrieval is a clearly written, although sometimes dense, handbook. The author uses a generous amount of examples of mathematical formulas, illustrations, and color plates. Clearly not a book for every database programmer--but a mandatory reference book for anyone building visual retrieval systems. --Mike CaputoThe increasing use of multimedia in computer applications has increased the relevance of visual databases. These visual databases require new methods for archiving and retrieving information, as traditional approaches used previously to index textual data are no longer appropriate. Visual Information Retrieval concentrates on solutions for representation, indexing, and querying by content of visual information, reviewing the main approaches and techniques available. Single image indexing, querying and retrieval by content, video segmentation, annotation, and content-based indexing are all examined. The book will appeal to practitioners and graduates/researchers involved in visual database issues in multimedia and image processing.From the Back CoverThe increasing use of multimedia in computer applications has increased the relevance of visual databases. These visual databases require new methods for archiving and retrieving information, as traditional approaches used previously to index textual data are no longer appropriate. Visual Information Retrieval concentrates on solutions for representation, indexing, and querying by content of visual information, reviewing the main approaches and techniques available. Single image indexing, querying and retrieval by content, video segmentation, annotation, and content-based indexing are all examined. The book will appeal to practitioners and graduates/researchers involved in visual database issues in multimedia and image processing.About the AuthorAlberto del Bimbo was with IBM Italy SpA from 1977 to 1988. In 1995, he started teaching as a full professor of computer systems at the Faculty of Engineering at the University of Florence, Italy, where he presently serves as the Director of the Dipartimento of Sistemi e Informatica. He is a member of IEEE and IAPR and presently serves as the chairman of the Italian chapter of IAPR. His scientific interests cover pattern recognition, image databases, multimedia, visual languages, and advanced man-machine interaction. He is the author of over 140 scientific publications appearing in international journals and conference proceedings. He has been the chairman of international conferences in the fields of image processing and multimedia computing. He is presently an associate editor of Pattern Recognition, Journal of Visual Languages and Computing,