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Titlebook: Local Image Descriptor: Modern Approaches; Bin Fan,Zhenhua Wang,Fuchao Wu Book 2015 The Author(s) 2015 Local feature.Binary descriptor.Com

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發(fā)表于 2025-3-21 19:16:12 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Local Image Descriptor: Modern Approaches
編輯Bin Fan,Zhenhua Wang,Fuchao Wu
視頻videohttp://file.papertrans.cn/588/587666/587666.mp4
概述Maximizes reader insights into local image description, both on classical methods and the state-of-the-art ones.Broadens your understanding on the development of this area and supplies you the most pr
叢書名稱SpringerBriefs in Computer Science
圖書封面Titlebook: Local Image Descriptor: Modern Approaches;  Bin Fan,Zhenhua Wang,Fuchao Wu Book 2015 The Author(s) 2015 Local feature.Binary descriptor.Com
描述This book covers a wide range of local image descriptors, from the classical ones to the state of the art, as well as the burgeoning research topics on this area. The goal of this effort is to let readers know what are the most popular and useful methods in the current, what are the advantages and the disadvantages of these methods, which kind of methods is best suitable for their problems or applications, and what is the future of this area. What is more, hands-on exemplars supplied in this book will be of great interest to Computer Vision engineers and practitioners, as well as those want to begin their research in this area. Overall, this book is suitable for graduates, researchers and engineers in the related areas both as a learning text and as a reference book.
出版日期Book 2015
關鍵詞Local feature; Binary descriptor; Computer vision; Image matching; Invariant descriptor
版次1
doihttps://doi.org/10.1007/978-3-662-49173-7
isbn_softcover978-3-662-49171-3
isbn_ebook978-3-662-49173-7Series ISSN 2191-5768 Series E-ISSN 2191-5776
issn_series 2191-5768
copyrightThe Author(s) 2015
The information of publication is updating

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發(fā)表于 2025-3-21 21:06:41 | 只看該作者
Book 2015n this area. The goal of this effort is to let readers know what are the most popular and useful methods in the current, what are the advantages and the disadvantages of these methods, which kind of methods is best suitable for their problems or applications, and what is the future of this area. Wha
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Intensity Order-Based Local Descriptors,framework by intensity order-based pooling. Then, a local intensity order pattern (LIOP) and how it is used in this framework are introduced. Finally, we demonstrate how we can design a binary descriptor by using the ordinal information in the local image patch.
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Bin Fan,Zhenhua Wang,Fuchao WuMaximizes reader insights into local image description, both on classical methods and the state-of-the-art ones.Broadens your understanding on the development of this area and supplies you the most pr
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Visual Applications,stitch, image retrieval, and localization etc. to name a few. In this chapter, we will introduce some of them, and show how a robust and discriminative descriptor is used in these specific applications.
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