EOL

This post is an application of the EOL calibration described in the EOL calibration article. Detect Image Corners Detecting the corners of the fisheye images on its original image is challenging due to its severe distortion. So we resort to detecting the corners on the BEV image and then project the corners back onto the original image to further refine the corners. Set initial extrinsics (referring to installation parameters (angles and positions) or parameters from joint calibration with LiDAR), construct a 20m×20m grid with resolution of 0.01m in the ego coordinate system’s ground plane (z=0), and generate a BEV projected image; ...

In this post, we will discuss the end-of-line (EOL) camera calibration, especially for camera bird’s-eye view (BEV) extrinsic calibration. Suggested Pipeline Do single camera intrinsic calibration Measure each corner in the world coordinate Refine the corners’ coordinates according to board constraints (plane, parallel, equally spaced) Find the plane equation in the world coordinate Initialize each camera’s extrinsic parameters by solving the perspective-n-point (PnP) problem Estimate the 3D coordinates by the intersection of the image ray and board plane ...