Multisensor Fusion for Computer Vision

  • J. K. Aggarwal
Conference proceedings

DOI: 10.1007/978-3-662-02957-2

Part of the NATO ASI Series book series (volume 99)

Table of contents (25 papers)

  1. Front Matter
    Pages I-X
  2. Principles and Issues in Multisensor Fusion

    1. Front Matter
      Pages 1-1
    2. The Issues, Analysis, and Interpretation of Multi-Sensor Images
      J. K. Aggarwal, Chen-Chau Chu
      Pages 37-62
    3. What Can be Fused?
      Gerard T. McKee
      Pages 71-84
  3. Information Fusion for Navigation

    1. Front Matter
      Pages 85-85
    2. Kalman Filter-based Algorithms for Estimating Depth from Image Sequences
      Larry Matthies, Richard Szeliski, Takeo Kanade
      Pages 87-130
    3. Geometric Sensor Fusion in Robotics
      Hugh F. Durrant-Whyte
      Pages 151-151
    4. Three-Dimensional Fusion from a Monocular Sequence of Images
      J. L. Jezouin, N. Ayache
      Pages 155-167
  4. Multisensor Fusion for Object Recognition

    1. Front Matter
      Pages 169-169
    2. Fusion of Range and Intensity Image Data for Recognition of 3D object surfaces
      Jianchi Wei, Paul Levi, Ulrich Rembold
      Pages 171-194
    3. Fusion of Color and Geometric Information
      Xavier F. Lebègue, David C. Baker, J. K. Aggarwal
      Pages 213-237
    4. Evidence Fusion Using Constraint Satisfaction Networks
      Andrea Califano, Ruud M. Bolle, Rick Kjeldsen, Russell W. Taylor
      Pages 239-253
    5. Multisensor Information Integration for Object Identification
      A. Mitiche, R. Laganière, T. Henderson
      Pages 255-276
  5. Computer Architectures for Multisensor Fusion

    1. Front Matter
      Pages 277-277

About these proceedings


This volume contains revised papers based on contributions to the NATO Advanced Research Workshop on Multisensor Fusion for Computer Vision, held in Grenoble, France, in June 1989. The 24 papers presented here cover a broad range of topics, including the principles and issues in multisensor fusion, information fusion for navigation, multisensor fusion for object recognition, network approaches to multisensor fusion, computer architectures for multi sensor fusion, and applications of multisensor fusion. The participants met in the beautiful surroundings of Mont Belledonne in Grenoble to discuss their current work in a setting conducive to interaction and the exchange of ideas. Each participant is a recognized leader in his or her area in the academic, governmental, or industrial research community. The workshop focused on techniques for the fusion or integration of sensor information to achieve the optimum interpretation of a scene. Several participants presented novel points of view on the integration of information. The 24 papers presented in this volume are based on those collected by the editor after the workshop, and reflect various aspects of our discussions. The papers are organized into five parts, as follows.


3D Bildverstehen Computer Vision Computer-Sehen Constraint Satisfaction Image understanding Multisensor fusion Navigation Object recognition Sensor fusion Sensorfusion algorithms cognition robot robotics

Editors and affiliations

  • J. K. Aggarwal
    • 1
  1. 1.Computer and Vision Research Center Department of Electrical and Computer EngineeringThe University of Texas at AustinAustinUSA

Bibliographic information

  • Copyright Information Springer-Verlag Berlin Heidelberg 1993
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-642-08135-4
  • Online ISBN 978-3-662-02957-2