Local Image Descriptor: Modern Approaches
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
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Bin Fan Zhenhua Wang Fuchao Wu
Local Image Descriptor: Modern Approaches 123
SpringerBriefs in Computer Science Series editors Stan Zdonik, Brown University, Providence, USA Shashi Shekhar, University of Minnesota, Minneapolis, USA Jonathan Katz, University of Maryland, College Park, USA Xindong Wu, University of Vermont, Burlington, USA Lakhmi C. Jain, University of South Australia, Adelaide, Australia David Padua, University of Illinois Urbana-Champaign, Urbana, USA Xuemin (Sherman) Shen, University of Waterloo, Waterloo, Canada Borko Furht, Florida Atlantic University, Boca Raton, USA V.S. Subrahmanian, University of Maryland, College Park, USA Martial Hebert, Carnegie Mellon University, Pittsburgh, USA Katsushi Ikeuchi, University of Tokyo, Tokyo, Japan Bruno Siciliano, Università di Napoli Federico II, Napoli, Italy Sushil Jajodia, George Mason University, Fairfax, USA Newton Lee, Newton Lee Laboratories, LLC, Tujunga, USA
More information about this series at http://www.springer.com/series/10028
Bin Fan Zhenhua Wang Fuchao Wu •
Local Image Descriptor: Modern Approaches
123
Bin Fan Institute of Automation Chinese Academy of Sciences Beijing China
Fuchao Wu Institute of Automation Chinese Academy of Sciences Beijing China
Zhenhua Wang School of EEE Nanyang Technological University Singapore Singapore
ISSN 2191-5768 ISSN 2191-5776 (electronic) SpringerBriefs in Computer Science ISBN 978-3-662-49171-3 ISBN 978-3-662-49173-7 (eBook) DOI 10.1007/978-3-662-49173-7 Library of Congress Control Number: 2015959572 © Springer-Verlag Berlin Heidelberg 2015 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper This Springer imprint is published by SpringerNature The registered company is Springer-Verlag GmbH Berlin Heidelberg
Foreword 1
Over the last 15 years, feature point descriptors have become indispensable tools in the computer vision community. They are essential components of applications ranging from image retrieval to multi-image stereo ma
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