Recent Advances in Intelligent Image Search and Video Retrieval Softcover Repri Edition Contributor(s): Liu, Chengjun (Editor) |
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ISBN: 331984816X ISBN-13: 9783319848167 Publisher: Springer OUR PRICE: $208.99 Product Type: Paperback - Other Formats Published: May 2018 |
Additional Information |
BISAC Categories: - Computers | Computer Graphics - Technology & Engineering | Engineering (general) - Computers | Intelligence (ai) & Semantics |
Dewey: 006.3 |
Series: Intelligent Systems Reference Library |
Physical Information: 0.54" H x 6.14" W x 9.21" (0.80 lbs) 235 pages |
Descriptions, Reviews, Etc. |
Publisher Description: 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. |