Multisensor Fusion for Computer Vision

- 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