Multisensor Fusion for Computer Vision

By: J. K. Aggarwal (Editor)

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Hardcover | 22 January 1993

At a Glance

Hardcover
472 Pages

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23.39 x 15.6 x 2.54

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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.

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Non-Fiction Computing & I.T.Computer Science Digital Signal Processing (DSP)Artificial Intelligence Computer Vision Graphical & Digital Media Applications Image Processing

Preface
Principles and Issues in Multisensor Fusion
Information Integration and Model Selection in Computer Vision	p. 3
Principles and Techniques for Sensor Data Fusion	p. 15
The Issues, Analysis, and Interpretation of Multisensor Images	p. 37
Physically-Based Fusion of Visual Data over Space, Time, and Scale	p. 63
What Can Be Fused?	p. 71
Information Fusion for Navigation
Kalman Filter-Based Algorithms for Estimating Depth from Image Sequences	p. 87
Robust Linear Rules for Nonlinear Systems	p. 131
Geometric Sensor Fusion in Robotics (Abstract)	p. 151
Cooperation between 3D Motion Estimation and Token Trackers (Abstract)	p. 153
Three-Dimensional Fusion from a Monocular Sequence of Images	p. 155
Multisensor Fusion for Object Recognition
Fusion of Range and Intensity Image Data for Recognition of 3D Object Surfaces	p. 171
Integrating Driving Model and Depth for Identification of Partially Occluded 3D Models	p. 195
Fusion of Color and Geometric Information	p. 213
Evidence Fusion Using Constraint Satisfaction Networks	p. 239
Multisensor Information Integration for Object Identification	p. 255
Computer Architectures for Multisensor Fusion
Distributing Inferential Activity for Synchronic and Diachronic Data Fusion	p. 279
Real-Time Perception Architectures: The SKIDS Project	p. 293
Algorithms on a SIMD Processor Array	p. 307
Shape and Curvature Data Fusion by Conductivity Analysis (Abstract)	p. 323
A Knowledge-Based Sensor Fusion Editor	p. 325
Applications of Multisensor Fusion
Multisensor Change Detection for Surveillance Applications	p. 345
Multisensor Techniques for Space Robotics	p. 367
Coordinated Use of Multiple Sensors in a Robotic Workcell	p. 395
Neural Network Based Inspection of Machined Surfaces Using Multiple Sensors	p. 421
Adaptive Visual/Auditory Fusion in the Target Localization System of the Barn Owl	p. 439
Index of Key Terms	p. 451
Workshop Speakers	p. 455
Table of Contents provided by Blackwell. All Rights Reserved.

Multisensor Fusion for Computer Vision

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