Volume 99 1993

Multisensor Fusion for Computer Vision

Editors:

ISBN: 978-3-642-08135-4 (Print) 978-3-662-02957-2 (Online)

Table of contents (25 chapters)

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  1. Front Matter

    Pages I-X

  2. Principles and Issues in Multisensor Fusion

    1. Front Matter

      Pages 1-1

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      Book Chapter

      Pages 3-13

      Information Integration and Model Selection in Computer Vision

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      Book Chapter

      Pages 15-36

      Principles and Techniques for Sensor Data Fusion

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      Book Chapter

      Pages 37-62

      The Issues, Analysis, and Interpretation of Multi-Sensor Images

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      Book Chapter

      Pages 63-69

      Physically-Based Fusion of Visual Data over Space, Time, and Scale

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      Book Chapter

      Pages 71-84

      What Can be Fused?

  3. Information Fusion for Navigation

    1. Front Matter

      Pages 85-85

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      Book Chapter

      Pages 87-130

      Kalman Filter-based Algorithms for Estimating Depth from Image Sequences

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      Book Chapter

      Pages 131-150

      Robust Linear Rules for Nonlinear Systems

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      Book Chapter

      Pages 151-151

      Geometric Sensor Fusion in Robotics

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      Book Chapter

      Pages 153-153

      Cooperation between 3D Motion Estimation and Token Trackers

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      Book Chapter

      Pages 155-167

      Three-Dimensional Fusion from a Monocular Sequence of Images

  4. Multisensor Fusion for Object Recognition

    1. Front Matter

      Pages 169-169

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      Book Chapter

      Pages 171-194

      Fusion of Range and Intensity Image Data for Recognition of 3D object surfaces

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      Book Chapter

      Pages 195-211

      Integrating Driving Model and Depth for Identification of Partially Occluded 3D Models

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      Book Chapter

      Pages 213-237

      Fusion of Color and Geometric Information

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      Book Chapter

      Pages 239-253

      Evidence Fusion Using Constraint Satisfaction Networks

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      Book Chapter

      Pages 255-276

      Multisensor Information Integration for Object Identification

  5. Computer Architectures for Multisensor Fusion

    1. Front Matter

      Pages 277-277

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      Book Chapter

      Pages 279-291

      Distributing Inferential Activity for Synchronic and Diachronic Data Fusion

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      Book Chapter

      Pages 293-305

      Real-Time Perception Architectures: The SKIDS Project

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      Book Chapter

      Pages 307-322

      Algorithms on a SIMD processor array

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      Book Chapter

      Pages 323-323

      Shape and Curvature Data Fusion by Conductivity Analysis

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      Book Chapter

      Pages 325-341

      A Knowledge Based Sensor Fusion Editor

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