Key-Frame SLAM Based on Motion Estimation and Stochastic Filtering Using Stereo Vision
Motion estimation approaches using various vision sensors enable the robust estimation of successive camera poses. However, motion estimation itself inevitably involves pose errors that result in an inaccurate and inconsistent map. To solve this problem,
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Sensors and Systems Technology Advancement and Application Demonstrations
Smart Sensors and Systems
Yongpan Liu • Youn-Long Lin • Chong-Min Kyung Hiroto Yasuura Editors
Smart Sensors and Systems Technology Advancement and Application Demonstrations
Editors Yongpan Liu Circuits and Systems Division Tsinghua University Circuits and Systems Division Beijing, China Chong-Min Kyung #310 IT Convergence Building (N1) Center for Integrated Smart Sensors Yuseong-gu, Daejeon, Korea (Democratic People’s Republic of)
Youn-Long Lin National Tsing Hua University Hsichu, Taiwan Hiroto Yasuura Kyushu University Fukuoka Shi, Japan
ISBN 978-3-030-42233-2 ISBN 978-3-030-42234-9 (eBook) https://doi.org/10.1007/978-3-030-42234-9 © Springer Nature Switzerland AG 2020 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, expressed 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
Internet of Things (IoTs) is becoming the key technology for smart social information systems. To realize the smart society by IoTs, effective sensing technologies of various aspects of physical world are required. The huge sensing data should be intelligently processed and integrated by smart sensor systems. This book shows essential issues of the IoTs and smart sensor technologies in various aspects, from fundamental devices to actual social applications. Following previous three editions, this book brings together multidisciplinary sensor technology from biological, optical, chemical, and electrical domains. The research field is expanding to various application areas, and new researches are being explored. This book presents up-to-date approaches of sensor devices and smart sensor systems in real-world applications including biomedical, video, and fundamental IoT techniques. Chap
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