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 use of general descriptive names, registered names, trademarks, service marks, etc. Violations are liable to prosecution under the respective Copyright Law. Permissions for use may be obtained through RightsLink at the Copyright Clearance Center. 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. 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. 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. Library of Congress Control Number: 2014943409 Springer Cham Heidelberg New York Dordrecht London Springer International Publishing Switzerland 2014 This work is subject to copyright. Pushmeet Kohli Microsoft Research Cambridge UK Zhengyou Zhang Microsoft Research Redmond, WA USA Series editor Sing Bing Kang Interactive Visual Media Group Microsoft Research Redmond, WA USA Jungong Han Civolution Technology Eindhoven The Netherlands Įditors Ling Shao University of Sheffield Sheffield UKįounding editor Sameer Singh Rail Vision Europe Ltd.Ling Shao Jungong Han Pushmeet Kohli Zhengyou Zhang
Ling Shao Jungong Han Pushmeet Kohli Zhengyou Zhang EditorsĬomputer Vision and Machine Learning with RGB-D Sensors Advances in Computer Vision and Pattern Recognition
0 kommentar(er)
