Analysis of Face Recognition Methods in Linear Subspace
How to extract discriminant features from face images is a key problem to face recognition. Many methods have been proposed, and among these methods linear subspace analysis method has been given more and more attention owing to its good properties, since
- PDF / 60,646,492 Bytes
- 3,404 Pages / 453.543 x 683.15 pts Page_size
- 98 Downloads / 195 Views
Shaozi Li Qun Jin Xiaohong Jiang James J. (Jong Hyuk) Park Editors
Frontier and Future Development of Information Technology in Medicine and Education ITME 2013
Lecture Notes in Electrical Engineering Volume 269
For further volumes: http://www.springer.com/series/7818
Shaozi Li Qun Jin Xiaohong Jiang James J. (Jong Hyuk) Park •
•
Editors
Frontier and Future Development of Information Technology in Medicine and Education ITME 2013
123
Editors Shaozi Li Cognitive Science Xiamen University Xiamen People’s Republic of China
Xiaohong Jiang School of Systems Information Science Future University Hakodate Hakodate, Hokkaido Japan
Qun Jin Networked Information Systems Lab, Human Informatics and Cognitive Sciences Waseda University Waseda Japan
James J. (Jong Hyuk) Park Department of Computer Science and Engineering Seoul National Universityof Science and Technology (SeoulTech) Seoul Korea, Republic of South Korea
ISSN 1876-1100 ISBN 978-94-007-7617-3 DOI 10.1007/978-94-007-7618-0
ISSN 1876-1119 (electronic) ISBN 978-94-007-7618-0 (eBook)
Springer Dordrecht Heidelberg New York London Library of Congress Control Number: 2013948373 Springer Science+Business Media Dordrecht 2014 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. Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher’s location, in its current version, and permission for use must always be obtained from Springer. Permissions for use may be obtained through RightsLink at the Copyright Clearance Center. Violations are liable to prosecution under the respective Copyright Law. 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. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
Message from the ITME 2013 Gen
