Abstract
Positioning the pixels of ground control points (GCPs) in drone images is an issue of great concern in the field of drone photogrammetry. The current mainstream automatic approaches are based on standardized markers, such as circular coded targets and point coded targets. There is no denying that introducing standardized markers improves the efficiency of positioning GCP pixels. However, the low flexibility leads to some drawbacks, such as the heavy logistical input in placing and maintaining GCP markers. Especially as drone photogrammetry steps into the era of large scenes, the logistical input in maintaining GCP markers becomes much more costly. This paper proposes a novel positioning method applicable for non-standardized GCPs. Firstly, regions of interest (ROIs) are extracted from drone images with stereovision technologies. Secondly, the quality of ROIs is evaluated using image entropy, and then the outliers are filtered by an adjusted boxplot. Thirdly, pixels of interest are searched with a corner detector, and the precise imagery coordinates are obtained by subpixel optimization. Finally, the verification was carried out in an urban scene, and the results show that this method has good applicability to the GCPs on road traffic signs, and the accuracy rate is over 95%.
Highlights
Drone photogrammetry is a relatively new technique that has gradually become popular because of its flexibility and cost-efficient data acquisition
The key to achieving high precision is to establish an accurate correspondence between drone images and the spatial world
The relative spatial poses of drone images are recovered with multi-view constraints from feature correspondences, and image regions of interest are extracted through ray projection
Summary
Drone photogrammetry is a relatively new technique that has gradually become popular because of its flexibility and cost-efficient data acquisition. The key to achieving high precision is to establish an accurate correspondence between drone images and the spatial world. This correspondence is established with the so-called ground control points (GCPs). If any unexpected error occurs during attaching, the effectiveness of GCPs would decrease significantly In this regard, the pixel positioning of GCPs is a fundamental and essential aspect of drone photogrammetry
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