Multisensor Fusion for Computer Vision - J. K. Aggarwal

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Résumé :
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.

Sommaire:
Information Integration and Model Selection in Computer Vision.- Principles and Techniques for Sensor Data Fusion.- The Issues, Analysis, and Interpretation of Multisensor Images.- Physically-Based Fusion of Visual Data over Space, Time, and Scale.- What Can Be Fused?.- Kalman Filter-Based Algorithms for Estimating Depth from Image Sequences.- Robust Linear Rules for Nonlinear Systems.- Geometric Sensor Fusion in Robotics (Abstract).- Cooperation between 3D Motion Estimation and Token Trackers (Abstract).- Three-Dimensional Fusion from a Monocular Sequence of Images.- Fusion of Range and Intensity Image Data for Recognition of 3D Object Surfaces.- Integrating Driving Model and Depth for Identification of Partially Occluded 3D Models.- Fusion of Color and Geometric Information.- Evidence Fusion Using Constraint Satisfaction Networks.- Multisensor Information Integration for Object Identification.- Distributing Inferential Activity for Synchronic and Diachronic Data Fusion.- Real-Time Perception Architectures: The SKIDS Project.- Algorithms on a SIMD Processor Array.- Shape and Curvature Data Fusion by Conductivity Analysis (Abstract).- A Knowledge-Based Sensor Fusion Editor.- Multisensor Change Detection for Surveillance Applications.- Multisensor Techniques for Space Robotics.- Coordinated Use of Multiple Sensors in a Robotic Workcell.- Neural Network Based Inspection of Machined Surfaces Using Multiple Sensors.- Adaptive Visual/Auditory Fusion in the Target Localization System of the Barn Owl.- Index of Key Terms.- Workshop Speakers.