Abstract
Acknowledged guidelines and standards such as those formerly governing project planning in analogue aerial photogrammetry are still missing in UAV photogrammetry. The reasons are many, from a great variety of projects goals to the number of parameters involved: camera features, flight plan design, block control and georeferencing options, Structure from Motion settings, etc. Above all, perhaps, stands camera calibration with the alternative between pre- and on-the-job approaches. In this paper we present a Monte Carlo simulation study where the accuracy estimation of camera parameters and tie points’ ground coordinates is evaluated as a function of various project parameters. A set of UAV (Unmanned Aerial Vehicle) synthetic photogrammetric blocks, built by varying terrain shape, surveyed area shape, block control (ground and aerial), strip type (longitudinal, cross and oblique), image observation and control data precision has been synthetically generated, overall considering 144 combinations in on-the-job self-calibration. Bias in ground coordinates (dome effect) due to inaccurate pre-calibration has also been investigated. Under the test scenario, the accuracy gap between different block configurations can be close to an order of magnitude. Oblique imaging is confirmed as key requisite in flat terrain, while ground control density is not. Aerial control by accurate camera station positions is overall more accurate and efficient than GCP in flat terrain.
Highlights
Accurate knowledge of camera interior orientation elements and proper mathematical modelling of the image formation process are key elements for image metrology
Images have been acquired with a DJI (Shenzhen, China) Phantom 3 equipped with a FC300X camera with a resolution of 4000 × 3000 pixels, a pixel size of
144,000 camera calibration parameter sets estimated in the Bundle BlockAdjustment (BBA) of the Monte Carlo (MC) simulations in the nine block configurations of the experiment, we investigated the 3D tie point coordinates sensitivity to pre-calibrated camera parameters, i.e., the dependence of the dome size on the pre-calibration block configuration, through a second MC simulation
Summary
Accurate knowledge of camera interior orientation elements and proper mathematical modelling of the image formation process are key elements for image metrology. The process leading to the estimation of such model parameters, has long been (and still is) one of the most researched topics in close range photogrammetry [2] as well as in computer vision [3,4]. At least in the former area, there is general agreement on conditions providing optimal results [1,5]: camera parameters should be estimated in a Least Squares Bundle Block. Evaluating the effects of residual calibration errors on tie point accuracy, in the case of pre-calibration as well as of on-the-job self-calibration, on the other hand, is of relevant interest, especially from a practical point of view
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