Abstract
Abstract. Facilities such as road, parking lots play an important role in our lives nowadays. Damage to such a vehicle facility can cause human injury, as well as inconvenience and cost. To prevent this, facility monitoring is performed periodically, but the current monitoring method is low efficiency by blocking the facility or performing it late at night. In order to increase the efficiency of monitoring, research using images, especially drone images, was conducted. However, when using a drone image, there is a trade-off relationship between accuracy and processing time. In this study, we propose a real-time drone mapping based on reference images for efficient vehicle facility monitoring. The real-time drone mapping based on the reference image is composed of reference images build, aerial triangulation (AT) based on reference images (refAT), and orthophoto generation. The refAT refers to a method of performing AT by using a reference images as reference data. We compared the processing time and processing accuracy of direct georeferencing and refAT. We built 154 drone reference images in the target area. The refAT showed a processing time of about 8.95 seconds and an accuracy of 3.4 cm, and the direct georeferencing method showed a processing time of about 1.49 seconds and an accuracy of 22.5 m. If the method of this study is used for facility monitoring, it is expected that the efficiency of monitoring will be improved with speed and accuracy.
Highlights
In modern society, transportation is one of the most essential elements
EOPs are used in a field of view (FOV) query to find reference images corresponding to processing range of an acquired image, and keypoints and descriptors are used in image matching with an acquired image
Ae and Ag are established by differentiating the collinear equation for each variable (Ae: EOPs, Ag: ground coordinates), and Ke is set as an identity matrix because the external expression elements of the reference image are used as direct constraints
Summary
The state provides public transportation such as buses and subways to ensure the mobility of people who have difficulty using their own transportation Even if such a system is in place, the utility is significantly reduced if there are no vehicle facilities such as roads or parking lots. Accurate and rapid monitoring of facilities with frequent vehicle access such as roads, tunnel and parking lots is important This is because damage to vehicle facilities affects the transportation function of the region, and affects people's safety. In this paper, we propose a real-time drone mapping based on reference images for efficient monitoring of vehicle facilities such as roads and parking lots. Real-time means that we can process data in region of interest (ROI) instantly, mapping based on reference images represents that we can expect the accuracy comparable to post-processing result. We contribute to image-based monitoring on two aspects – processing time and processing accuracy
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