Title :
Geocoded terrestrial mosaics using pose sensors and video registration
Author_Institution :
Sarnoff Corp., Princeton, NJ, USA
Abstract :
The paper presents a complete algorithm for building geocoded terrestrial mosaics from aerial video accompanied by GPS/INS readings, without relying on ground survey points or reference imagery to provide geographic control. The 2D mosaic-to-video frame mappings are jointly estimated by bundle adjustment of constraints from pose sensor data and interframe registrations. Multiple-swath video collections are handled by automatically registering spatially adjacent frames across swaths. The proposed approach optimally combines the pose and interframe constraints for geocoding, unlike existing 2D mosaic techniques, while avoiding the complexity of 3D reconstruction. The method was validated on two highly dissimilar operating scenarios, with quantitative evaluation against ground truth supplied by known geocoded reference imagery. One test over hilly terrain found median mosaic continuity and geocoding errors of 1.6 m and 3.1 m, respectively, which is acceptable for many tasks. Characterization of such errors is essential for acceptance of this video mosaic process in critical geospatial applications.
Keywords :
cartography; geographic information systems; image registration; video coding; 2D mosaic-to-video frame mappings; 3D reconstruction; GPS/INS readings; aerial video; automatic registration; bundle adjustment; critical geospatial applications; geocoded reference imagery; geocoded terrestrial mosaics; geocoding errors; geographic control; hilly terrain; interframe constraints; interframe registrations; median mosaic continuity errors; multiple-swath video collections; operating scenarios; pose constraints; pose sensor data; pose sensors; quantitative evaluation; spatially adjacent frames; video registration; Aircraft manufacture; Assembly; Automatic control; Cameras; Global Positioning System; Image reconstruction; Layout; Length measurement; Position measurement; Telemetry;
Conference_Titel :
Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on
Print_ISBN :
0-7695-1272-0
DOI :
10.1109/CVPR.2001.990570