Camera Calibration Toolbox

The Camera Calibration Toolbox is a specialized computational tool in computer vision used to determine camera intrinsic and extrinsic parameters. This type of tool typically employs a two-stage calibration workflow: first computing initial parameters through linear methods, followed by precise adjustments via nonlinear optimization.

The initial stage utilizes linear methods (such as the Direct Linear Transform algorithm) to rapidly solve for fundamental camera matrix parameters including focal length and principal point coordinates. While these initial estimates may lack precision, they provide crucial starting values for subsequent optimization. In implementation, this typically involves solving homogeneous equations using singular value decomposition (SVD) on point correspondences between 3D world coordinates and 2D image points.

The second stage employs nonlinear optimization algorithms (like Levenberg-Marquardt) to jointly refine all parameters. This phase accounts for nonlinear factors including radial distortion and tangential distortion by minimizing reprojection errors to achieve optimal solutions. Distortion coefficients are precisely computed during this stage, effectively correcting barrel distortion or pincushion distortion phenomena in images. The optimization objective function typically involves iteratively minimizing the Euclidean distance between observed image points and reprojected 3D points.

This two-stage calibration methodology ensures computational efficiency while achieving high-precision calibration results, making it a widely adopted solution in both industrial and academic applications. Modern calibration toolboxes often include auxiliary features such as automatic checkerboard detection, result visualization interfaces, and accuracy validation metrics to streamline the calibration workflow.