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Multisensor Fusion and Integration for Intelligent Systems

An Edition of the Selected Papers from the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems 2008

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  • © 2009

Overview

Editors:
  1. Hernsoo Hahn
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  2. Hanseok Ko
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  3. Sukhan Lee
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  • Recent research in Multisensor Fusion and Integration for Intelligent Systems
  • Includes a set of selected papers from the International Conference on of Multisensor Fusion and Integration for Intelligent Systems (MFI 2008) to be held in Seoul, Korea, August 20-22, 2008

Part of the book series: Lecture Notes in Electrical Engineering (LNEE, volume 35)

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Table of contents (32 chapters)

  1. Front Matter

    Pages 1-14
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  2. Theories in Data and Information Fusion

    1. Front Matter

      Pages 1-2
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  3. Theories in data and information fusion

    1. Performance Analysis of GPS/INS Integrated System by Using a Non-Linear Mathematical Model

      • Khalid Touil, Mourad Zribi, Mohammed Benjelloun
      Pages 3-14

    2. Object-Level Fusion and Confidence Management in a Multi-Sensor Pedestrian Tracking System

      • Fadi Fayad, Véronique Cherfaoui
      Pages 15-31

    3. Effective Lip Localization and Tracking for Achieving Multimodal Speech Recognition

      • Wei Chuan Ooi, Changwon Jeon, Kihyeon Kim, Hanseok Ko, David K. Han
      Pages 33-43

    4. Optimal View Selection and Event Retrieval in Multi-Camera Office Environment

      • Han-Saem Park, Soojung Lim, Jun-Ki Min, Sung-Bae Cho
      Pages 45-53

    5. Fusion of Multichannel Biosignals Towards Automatic Emotion Recognition

      • Jonghwa Kim, Elisabeth André
      Pages 55-68

    6. A Comparison of Track-to-Track Fusion Algorithms for Automotive Sensor Fusion

      • Stephan Matzka, Richard Altendorfer
      Pages 69-81

    7. Effective and Efficient Communication of Information

      • Jan Willem Marck, Leon Kester, Miranda van Iersel, Jeroen Bergmans, Eelke van Foeken
      Pages 83-95

    8. Most Probable Data Association with Distance and Amplitude Information for Target Tracking in Clutter

      • Taek Lyul Song
      Pages 97-109

    9. Simultaneous Multi-Information Fusion and Parameter Estimation for Robust 3-D Indoor Positioning Systems

      • Hui Wang, Andrei Szabo, Joachim Bamberger, Uwe D. Hanebeck
      Pages 111-125

    10. Efficient Multi-Target Tracking with Sub-Event IMM-JPDA and One-Point Prime Initialization

      • Seokwon Yeom
      Pages 127-142

    11. Enabling Navigation of MAVs through Inertial, Vision, and Air Pressure Sensor Fusion

      • Clark N. Taylor
      Pages 143-158

  4. Multi-Sensor Fusion and Integration in Robotics and Vision

    1. Front Matter

      Pages 159-161
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  5. Multi-sensor fusion and integration in robotics and vision

    1. Enhancement of Image Degraded by Fog Using Cost Function Based on Human Visual Model

      • Dongjun Kim, Changwon Jeon, Bonghyup Kang, Hanseok Ko
      Pages 163-171

    2. Pedestrian Route Guidance by Projecting Moving Images

      • Takuji Narumi, Yasushi Hada, Hajime Asama, Kunihiro Tsuji
      Pages 173-186

    3. Recognizing Human Activities from Accelerometer and Physiological Sensors

      • Sung-Ihk Yang, Sung-Bae Cho
      Pages 187-199

    4. The “Fast Clustering-Tracking” Algorithm in the Bayesian Occupancy Filter Framewok

      • Kamel Mekhnacha, Yong Mao, David Raulo, Christian Laugier
      Pages 201-219

    5. Compliant Physical Interaction Based on External Vision-Force Control and Tactile-Force Combination

      • Mario Prats, Philippe Martinet, Sukhan Lee, Pedro J. Sanz
      Pages 221-233

    6. iTASC: A Tool for Multi-Sensor Integration in Robot Manipulation

      • Ruben Smits, Tinne De Laet, Kasper Claes, Herman Bruyninckx, Joris De Schutter
      Pages 235-254
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Keywords

About this book

The ?eld of multi-sensor fusion and integration is growing into signi?cance as our societyisintransitionintoubiquitouscomputingenvironmentswithroboticservices everywhere under ambient intelligence. What surround us are to be the networks of sensors and actuators that monitor our environment, health, security and safety, as well as the service robots, intelligent vehicles, and autonomous systems of ever heightened autonomy and dependability with integrated heterogeneous sensors and actuators. The ?eld of multi-sensor fusion and integration plays key role for m- ing the above transition possible by providing fundamental theories and tools for implementation. This volume is an edition of the papers selected from the 7th IEEE International Conference on Multi-Sensor Integration and Fusion, IEEE MFI‘08, held in Seoul, Korea, August 20–22, 2008. Only 32 papers out of the 122 papers accepted for IEEE MFI’08 were chosen and requested for revision and extension to be included in this volume. The 32 contributions to this volume are organized into three parts: Part I is dedicated to the Theories in Data and Information Fusion, Part II to the Multi-Sensor Fusion and Integration in Robotics and Vision, and Part III to the Applications to Sensor Networks and Ubiquitous Computing Environments. To help readers understand better, a part summary is included in each part as an introduction. The summaries of Parts I, II, and III are prepared respectively by Prof. Hanseok Ko, Prof. Sukhan Lee and Prof. Hernsoo Hahn.

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