Working with ROS camera calibration
Like all sensors, cameras also need calibration for correcting the distortions in the camera images due to the camera's internal parameters, and 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 principle points.
Camera calibration can be done using a classic black-white chessboard, symmetrical circle pattern, or an asymmetrical circle pattern. According to each different pattern, we use different equations to get the calibration parameters. Using the calibration tools, we detect the patterns, and each detected pattern is taken as a new equation. When the calibration tool gets enough detected patterns it can compute...
