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Multisensor Fusion and Integration in the Wake of Big Data, Deep Learning and Cyber Physical System

An Edition of the Selected Papers from the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2017)

  • Conference proceedings
  • © 2018

Overview

Editors:
  1. Sukhan Lee

    1. Intelligent Systems Research Institute, Sungkyunkwan University, Suwon, Korea (Republic of)

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  2. Hanseok Ko

    1. School of Electrical Engineering, Korea University, Seoul, Korea (Republic of)

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  3. Songhwai Oh

    1. Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea (Republic of)

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  • Presents recent research in multisensor fusion and integration for intelligent systems
  • Includes selected papers from the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2017) held in Daegu, Korea, November 27–29, 2017
  • Focuses on multisensor fusion and integration in the wake of big data, deep learning, and cyber physical systems
  • Discusses how the multisensor fusion and integration technologies are applied to smart machines, which mark the beginning of things to things integration and human to machine integration

Part of the book series: Lecture Notes in Electrical Engineering (LNEE, volume 501)

Included in the following conference series:

Conference proceedings info: MFI 2017.

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Table of contents (17 papers)

  1. Front Matter

    Pages i-viii
    Download chapter PDF

  2. Multi-sensor Fusion: Theory and Practice

    1. Front Matter

      Pages 1-3
      Download chapter PDF

    2. Covariance Projection as a General Framework of Data Fusion and Outlier Removal

      • Sukhan Lee, Muhammad Abu Bakr
      Pages 5-21

    3. State Estimation in Networked Control Systems with Delayed and Lossy Acknowledgments

      • Florian Rosenthal, Benjamin Noack, Uwe D. Hanebeck
      Pages 22-38

    4. Performance of State Estimation and Fusion with Elliptical Motion Constraints

      • Qiang Liu, Nageswara S. V. Rao
      Pages 39-51

    5. Relevance and Redundancy as Selection Techniques for Human-Autonomy Sensor Fusion

      • Justin D. Brody, Anna M. R. Dixon, Daniel Donavanik, Ryan M. Robinson, William D. Nothwang
      Pages 52-75

    6. Classification of Reactor Facility Operational State Using SPRT Methods with Radiation Sensor Networks

      • Camila Ramirez, Nageswara S. V. Rao
      Pages 76-97

    7. Improving Ego-Lane Detection by Incorporating Source Reliability

      • Tran Tuan Nguyen, Jens Spehr, Jonas Sitzmann, Marcus Baum, Sebastian Zug, Rudolf Kruse
      Pages 98-118

    8. Applying Knowledge-Based Reasoning for Information Fusion in Intelligence, Surveillance, and Reconnaissance

      • Achim Kuwertz, Dirk Mühlenberg, Jennifer Sander, Wilmuth Müller
      Pages 119-139

    9. Multiple Classifier Fusion Based on Testing Sample Pairs

      • Gaochao Feng, Deqiang Han, Yi Yang, Jiankun Ding
      Pages 140-152

  3. Multi-sensor Fusion Applications in Robotics

    1. Front Matter

      Pages 153-155
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    2. Bayesian Estimator Based Target Localization in Ship Monitoring System Using Multiple Compact High Frequency Surface Wave Radars

      • Sangwook Park, Chul Jin Cho, Younglo Lee, Andrew Da Costa, SangHo Lee, Hanseok Ko
      Pages 157-167

    3. SLAM-Based Return to Take-Off Point for UAS

      • Daniel Bender, Wolfgang Koch, Daniel Cremers
      Pages 168-185

    4. Underwater Terrain Navigation During Realistic Scenarios

      • Mårten Lager, Elin A. Topp, Jacek Malec
      Pages 186-209

    5. Supervised Calibration Method for Improving Contrast and Intensity of LIDAR Laser Beams

      • Mohammad Aldibaja, Noaki Suganuma, Keisuke Yoneda, Ryo Yanase, Akisue Kuramoto
      Pages 210-218

    6. Multi-object Tracking Based on a Multi-layer Particle Filter for Unclustered Spatially Extended Measurements

      • Johannes Buyer, Martin Vollert, Mihai Kocsis, Nico Sußmann, Raoul Zöllner
      Pages 219-238

    7. Ensemble Kalman Filter Variants for Multi-Object Tracking with False and Missing Measurements

      • Fabian Sigges, Marcus Baum
      Pages 239-252

    8. Fall Detection with Unobtrusive Infrared Array Sensors

      • Xiuyi Fan, Huiguo Zhang, Cyril Leung, Zhiqi Shen
      Pages 253-267

    9. Subtle Hand Action Recognition in Factory Based on Inertial Sensors

      • Yanyan Bao, Fuchun Sun, Xinfeng Hua, Bin Wang, Jianqin Yin
      Pages 268-283

    10. Kinematics, Dynamics and Control of an Upper Limb Rehabilitation Exoskeleton

      • Qingcong Wu, Ziyan Shao
      Pages 284-298
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  1. Multisensor Fusion and Integration in the Wake of Big Data, Deep Learning and Cyber Physical System

Keywords

About this book

This book includes selected papers from the 13th IEEE International Conference on Multisensor Integration and Fusion for Intelligent Systems (MFI 2017) held in Daegu, Korea, November 16–22, 2017. It covers various topics, including sensor/actuator networks, distributed and cloud architectures, bio-inspired systems and evolutionary approaches, methods of cognitive sensor fusion, Bayesian approaches, fuzzy systems and neural networks, biomedical applications, autonomous land, sea and air vehicles, localization, tracking, SLAM, 3D perception, manipulation with multifinger hands, robotics, micro/nano systems, information fusion and sensors, and multimodal integration in HCI and HRI. The book is intended for robotics scientists, data and information fusion scientists, researchers and professionals at universities, research institutes and laboratories.

Editors and Affiliations

  • Intelligent Systems Research Institute, Sungkyunkwan University, Suwon, Korea (Republic of)

    Sukhan Lee

  • School of Electrical Engineering, Korea University, Seoul, Korea (Republic of)

    Hanseok Ko

  • Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea (Republic of)

    Songhwai Oh

Bibliographic Information

  • Book Title: Multisensor Fusion and Integration in the Wake of Big Data, Deep Learning and Cyber Physical System

  • Book Subtitle: An Edition of the Selected Papers from the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2017)

  • Editors: Sukhan Lee, Hanseok Ko, Songhwai Oh

  • Series Title: Lecture Notes in Electrical Engineering

  • DOI: https://doi.org/10.1007/978-3-319-90509-9

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer International Publishing AG, part of Springer Nature 2018

  • Hardcover ISBN: 978-3-319-90508-2Published: 05 July 2018

  • Softcover ISBN: 978-3-030-08030-3Published: 20 December 2018

  • eBook ISBN: 978-3-319-90509-9Published: 04 July 2018

  • Series ISSN: 1876-1100

  • Series E-ISSN: 1876-1119

  • Edition Number: 1

  • Number of Pages: VIII, 300

  • Number of Illustrations: 142 b/w illustrations

  • Topics: Communications Engineering, Networks, Computational Intelligence, Robotics and Automation

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