國立虎尾科技大學 |

Recent advances in intelligent image search and video retrieval

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Recent advances in intelligent image search and video retrieval/ edited by Chengjun Liu.
其他作者:	Liu, Chengjun.
出版者:	Cham :Springer International Publishing : : 2017.,
面頁冊數:	xvii, 235 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
標題:	Information retrieval. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-52081-0
ISBN:	9783319520810

Recent advances in intelligent image search and video retrieval
Recent advances in intelligent image search and video retrieval[electronic resource] /edited by Chengjun Liu. - Cham :Springer International Publishing :2017. - xvii, 235 p. :ill., digital ;24 cm. - Intelligent systems reference library,v.1211868-4394 ;. - Intelligent systems reference library ;v. 3..

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 Classiﬁcation -- Inheritable Color Space (InCS) and Generalized InCS Framework with Applications to Kinship Veriﬁcation -- Novel Sparse Kernel Manifold Learner for Image Classiﬁcation Applications -- A New Efﬁcient SVM (eSVM) with Applications to Accurate and Efﬁcient Eye Search in Images -- SIFT Features in Multiple Color Spaces for Improved Image Classiﬁcation -- Clothing Analysis for Subject Identiﬁcation and Retrieval -- Performance Evaluation of Video Analytics for Trafﬁc Incident Detection and Vehicle Counts Collection.

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.

ISBN: 9783319520810

Standard No.: 10.1007/978-3-319-52081-0doiSubjects--Topical Terms:

563691
Information retrieval.

LC Class. No.: ZA3075

Dewey Class. No.: 025.0425

Recent advances in intelligent image search and video retrieval
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520 $a 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.
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