Frame-Frame Matching for Realtime Consistent Visual Mapping

Many successful indoor mapping techniques employ frame-to-frame matching of laser scans to produce detailed local maps, as well as closing large loops. In this paper, we propose a framework for applying the same techniques to visual imagery, matching visual frames with large numbers of point features. The relationship between frames is kept as a nonlinear measurement, and can be used to solve large loop closures quickly. Both monocular (bearing-only) and binocular vision can be used to generate matches. Other advantages of our system are that no special landmark initialization is required, and large loops can be solved very quickly.

Authors

• Kurt Konolige
• Motilal Agrawal

Keywords

• Simultaneous localization and mapping
• Large-scale systems
• Nonlinear systems
• Cameras
• Information filters
• Robotics and automation
• Constraint optimization
• Bandwidth
• Mobile robots
• Global Positioning System
• Feature Points
• Large Loop
• Loop Closure
• Image Features
• Large Systems
• Consistent Estimates
• Original System
• Precise Results
• Pose Estimation
• Null Space
• Motion Estimation
• Camera Frame
• Feature Tracking
• Structure From Motion
• Inertial System
• Set Of Frames
• Inverse Covariance
• Bundle Adjustment
• Visual Matching
• Visual Odometry
• Synthetic Measure
• Rigid Transformation
• Mapping System
• Image Point