Working with ROS camera calibration
Like all sensors, cameras also need to be calibrated so that we can correct the distortions in the camera's images due to its internal parameters, as well as for finding the world coordinates from the camera coordinates.
The primary parameters that cause image distortions are radial distortions and tangential distortions. Using the camera calibration algorithm, we can model these parameters and also calculate the real-world coordinates from the camera coordinates by computing the camera calibration matrix, which contains the focal distance and the principal points.
Camera calibration can be done using a classic black-white chessboard, symmetrical circle pattern, or asymmetrical circle pattern. According to each pattern, we can use different equations to get the calibration parameters. Using certain calibration tools, we can detect these patterns, and each detected pattern is taken as a new equation. When the calibration tool detects enough...