1 May 2017 Geopositioning with a quadcopter: Extracted feature locations and predicted accuracy without a priori sensor attitude information
Author Affiliations +
This paper presents an overview of the Full Motion Video-Geopositioning Test Bed (FMV-GTB) developed to investigate algorithm performance and issues related to the registration of motion imagery and subsequent extraction of feature locations along with predicted accuracy. A case study is included corresponding to a video taken from a quadcopter. Registration of the corresponding video frames is performed without the benefit of a priori sensor attitude (pointing) information. In particular, tie points are automatically measured between adjacent frames using standard optical flow matching techniques from computer vision, an a priori estimate of sensor attitude is then computed based on supplied GPS sensor positions contained in the video metadata and a photogrammetric/search-based structure from motion algorithm, and then a Weighted Least Squares adjustment of all a priori metadata across the frames is performed. Extraction of absolute 3D feature locations, including their predicted accuracy based on the principles of rigorous error propagation, is then performed using a subset of the registered frames. Results are compared to known locations (check points) over a test site. Throughout this entire process, no external control information (e.g. surveyed points) is used other than for evaluation of solution errors and corresponding accuracy.
Conference Presentation
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
John Dolloff, John Dolloff, Bryant Hottel, Bryant Hottel, David Edwards, David Edwards, Henry Theiss, Henry Theiss, Aaron Braun, Aaron Braun, "Geopositioning with a quadcopter: Extracted feature locations and predicted accuracy without a priori sensor attitude information", Proc. SPIE 10199, Geospatial Informatics, Fusion, and Motion Video Analytics VII, 1019906 (1 May 2017); doi: 10.1117/12.2263856; https://doi.org/10.1117/12.2263856


Back to Top