Recent advances in intelligent image search and video retrieval /

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Bibliographic Details
Imprint:Cham, Switzerland : Springer, 2017.
Description:1 online resource
Series:Intelligent systems reference library ; volume 121
Intelligent systems reference library ; v. 121.
Format: E-Resource Book
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Other authors / contributors:Liu, Chengjun (Computer scientist), editor.
Digital file characteristics:text file PDF
Notes:Includes bibliographical references and index.
Online resource; title from PDF title page (SpringerLink, viewed May 1, 2017).
Summary:This book initially reviews the major feature representation and extraction methods and effective learning and recognition approaches, which have broad applications in the context of intelligent image search and video retrieval. It subsequently presents novel methods, such as improved soft assignment coding, Inheritable Color Space (InCS) and the Generalized InCS framework, the sparse kernel manifold learner method, the efficient Support Vector Machine (eSVM), and the Scale-Invariant Feature Transform (SIFT) features in multiple color spaces. Lastly, the book presents clothing analysis for subject identification and retrieval, and performance evaluation methods of video analytics for traffic monitoring. Digital images and videos are proliferating at an amazing speed in the fields of science, engineering and technology, media and entertainment. With the huge accumulation of such data, keyword searches and manual annotation schemes may no longer be able to meet the practical demand for retrieving relevant content from images and videos, a challenge this book addresses.
Other form:Print version: Recent advances in intelligent image search and video retrieval. Cham, Switzerland : Springer, 2017 3319520806 9783319520803
Standard no.:10.1007/978-3-319-52081-0