By Topic

Geo-Referencing of Video Flow From Small Low-Cost Civilian UAV

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Guoqing Zhou ; Dept. of Civil Eng. & Technol., Old Dominion Univ., Norfolk, VA, USA

This paper presents a method of geo-referencing the video data acquired by a small low-cost UAV, which is specifically designed as an economical, moderately functional, small airborne platform intended to meet the requirement for fast-response to time-critical events in many small private sectors or government agencies for the small areas of interest. The developed mathematical model for geo-locating video data can simultaneously solve the video camera's interior orientation parameter (IOP) (including lens distortion), and the exterior orientation parameters (EOPs) of each video frame. With the experimental data collected by the UAV at the established control field located in Picayune, Mississippi, the results reveal that the boresight matrix, describing the relationship between attitude sensor and video camera, in a low-cost UAV system will not be able to remain a constant. This result is inconsistent with the calibrated results from the previous airborne mapping system because the boresight matrix was usually assumed to be a constant over an entire mission in a traditional airborne mapping system. Thus, this paper suggests that the exterior orientation parameters of each video frame in a small low-cost UAV should be estimated individually. With the developed method, each video is geo-orthorectified and then mosaicked together to produce a 2-D planimetric mapping. The accuracy of the 2-D planimetric map can achieve 1-2 pixels, i.e., 1-2 m, when comparing with the 43 check points measured by differential GPS (DGPS) survey.

Published in:

Automation Science and Engineering, IEEE Transactions on  (Volume:7 ,  Issue: 1 )