This repository contains source code for the paper A Web-based Visualization Tool for 3D Spatial Coverage Measurement of Aerial Images
The link of the paper: to do
The link of the demo video: to do
Since this is a web-based tool, you can directly visit the GitHub Pages: https://mazeyu.github.io/3D_Spatial_Coverage_Model_Demo/
Our website depends on CesiumJS library. Currently, it works on released version 1.62. But problems can arise if Cesium has some updates. Actually, recently Cesium change the return value of its API getProperty("longitude") and getProperty("latitude") from radians to degrees. I have to fix the code slightly as a result. So please contact us if you find the website doesn't work.
Currently we provide a small dataset in file data1.js. The format is like this:
data1={"lat":{"0":...}, "lng": ..., "hgt": ..., "yaw": ..., "pitch": ..., "roll": ..., "t": ...}
If you want to generate your own dataset, please make sure you follow this format.
Given an aerial image Ij, the aerial field of view fj is represented by the eight parameters acquired at the image capturing time, fj ≡ ⟨lat,lng,hgt,θy,θp,θr,α,R⟩, where lat and lng are the GPS coordinates (i.e., latitude and longitude) of the camera location, hgt is the camera height with respect to the ground, θy, θp, and θr are three rotation angles of the camera pose (θy is the yaw angle rotating around the vertical axis, θp is the pitch angle rotating around the lateral axis, θr is the roll angle rotating around the longitudinal axis), α is the camera visible angle, and R is the maximum visible distance.
Given a dataset F and a query region in 3D space Rq (e.g., a cubic region), the 3D spatial coverage measurement problem is formulated as calculating the geo-awareness percentage of F to the visual space located in Rq.
The GUI of the tool is like above.
You can switch to different datasets through the first menu bar. For interactive querying, the tool enables selecting one of the visible buildings as a geographical region (QR) to measure its spatial coverage in the 3D space. Once defining QR, the coverage is measured using the three coverage measurement models (VCM, ECM, and WCM) and the results are displayed in an information panel that is positioned in the upper-right corner of the window. You can change the parameters of the FOVs and models through the menu bars on the top.
Note that due to the randomness of our algorithm, the results may vary for the same case. But we choose the number of iterations high enough to guarantee that the error is about 1% in average. If necessary, we can increase this number to increase the accuracy.
Please refer to the paper for more detail.
If you used this code for your experiments or found it helpful, consider citing the following paper: