Hierarchical Perceptual Grouping for Object Recognition Theoretical
This unique text/reference presents a unified approach to the formulation of Gestalt laws for perceptual grouping, and the construction of nested hierarchies by aggregation utilizing these laws. The book also describes the extraction of such construc
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Eckart Michaelsen Jochen Meidow
Hierarchical Perceptual Grouping for Object Recognition Theoretical Views and Gestalt-Law Applications
Advances in Computer Vision and Pattern Recognition Founding editor Sameer Singh, Rail Vision, Castle Donington, UK Series editor Sing Bing Kang, Microsoft Research, Redmond, WA, USA Advisory Board Horst Bischof, Graz University of Technology, Austria Richard Bowden, University of Surrey, Guildford, UK Sven Dickinson, University of Toronto, ON, Canada Jiaya Jia, The Chinese University of Hong Kong, Hong Kong Kyoung Mu Lee, Seoul National University, South Korea Yoichi Sato, The University of Tokyo, Japan Bernt Schiele, Max Planck Institute for Computer Science, Saarbrücken, Germany Stan Sclaroff, Boston University, MA, USA
More information about this series at http://www.springer.com/series/4205
Eckart Michaelsen Jochen Meidow •
Hierarchical Perceptual Grouping for Object Recognition Theoretical Views and Gestalt-Law Applications
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Eckart Michaelsen Fraunhofer IOSB Ettlingen, Baden-Württemberg, Germany
Jochen Meidow Fraunhofer IOSB Ettlingen, Baden-Württemberg, Germany
ISSN 2191-6586 ISSN 2191-6594 (electronic) Advances in Computer Vision and Pattern Recognition ISBN 978-3-030-04039-0 ISBN 978-3-030-04040-6 (eBook) https://doi.org/10.1007/978-3-030-04040-6 Library of Congress Control Number: 2018960737 © Springer Nature Switzerland AG 2019 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. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Preface
Around the year 2008, I realized that much of what we had published as knowledge-based methods for image analysis was actually perceptual grouping. Moreover, these perceptual grouping rules were those that turned out to be more robust than the actual automat
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