Speedy Sparse Bundle Adjustment for Video/Image Sequences

ABSTRACT: VSI proposes a flexible sensor estimation framework for airborne calibration processing of image streams over long time periods. The components of the framework will consist of existing software and libraries. The plugin-based framework provides flexibility to switch the components easily. The core of the framework is a belief propagation engine to globally optimize the sensor parameters. The input to the approach is an image stream and its associated navigational data when available. The proposed framework is an online system wherein the sensor estimation is continuously refined as more spatial overlap is discovered. The proposed system can be dynamically tuned for either speed/efficiency or accuracy, depending on the requirements of the operator. The central tenets of the proposed approach are (i) use temporal ordering of the images to increase the computation efficiency, (ii) use spatial overlap of the images which are temporally disjoint to correct for any accumulated drift and (iii) to locally optimize the sensor parameters and use the belief propagation to globally optimize the sensor parameters for hundred thousands of images. BENEFIT: Sensor estimation capabilities for airborne image acquisition systems for Remote Sensing Applications. On-board processing capabilities for updating traffic reports.