Recent Advances in Intelligent Image Search and Video Retrieval

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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.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.


Presents advanced pattern recognition and machine learning methods using sparse representation and Introduces innovative similarity Addresses both theory and practice Includes supplementary material: sn.pub/extras

Inhalt

Feature Representation and Extraction for Image Search and Video Retrieval.- Learning and Recognition Methods for Image Search and Video Retrieval.- Improved Soft Assignment Coding for Image Classication.- Inheritable Color Space (InCS) and Generalized InCS Framework with Applications to Kinship Verication.- Novel Sparse Kernel Manifold Learner for Image Classication Applications.- A New Efcient SVM (eSVM) with Applications to Accurate and Efcient Eye Search in Images.- SIFT Features in Multiple Color Spaces for Improved Image Classication.- Clothing Analysis for Subject Identication and Retrieval.- Performance Evaluation of Video Analytics for Trafc Incident Detection and Vehicle Counts Collection.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783319520803
    • Genre Technology Encyclopedias
    • Auflage 1st edition 2017
    • Editor Chengjun Liu
    • Lesemotiv Verstehen
    • Anzahl Seiten 256
    • Herausgeber Springer
    • Größe H241mm x B160mm x T20mm
    • Jahr 2017
    • EAN 9783319520803
    • Format Fester Einband
    • ISBN 3319520806
    • Veröffentlichung 19.04.2017
    • Titel Recent Advances in Intelligent Image Search and Video Retrieval
    • Autor Chengjun Liu
    • Untertitel Contributions to the 9th Workshop on Cyclostationary Systems and Their Applicati
    • Gewicht 553g
    • Sprache Englisch

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