Some tools to facilitate trajectory prediction

See also trap

1. Camera calibration

Find the camera intrinsics and lens distortion matrixes. This helps to remove curvature from the image, and points map to a linear space.

02. Test Calibration and draw points

Apply the now obtained camera matrix to undistort a snapshot. Check if it looks good.

Now we can obtain coordinates to map for the homography. Draw points on the floor (I used chalk) and measure their distances. I then used SolveSpace to go from their distances to positions in a plane.

Then with a camera snapshot of these points, click with the cursor in the source image to draw mark these points in the image.

This is saved to points.json. If this is right, rename it to img_points.json for the homography.

2. Homography

Having the camera intrinsics, the perspective of the camera can be undone by mapping points to a 'top down' space. This way, the distances between points is in accordance to their distance IRL.

This file reads camera intrinsics & distortion matrixes, img_points.json (obtained step 2) and the corresponding irl_points.json. Which I created based on coordinates obtained with SolveSpace.