Direct linear transformation (DLT) calibration uses correspondences between world points and camera image points to estimate camera parameters. In particular, DLT calibration exploits the fact thethat the perspective pinhole camera model defines a set of similarity relations that can be solved via the [[direct linear transformation]] algorithm.<ref name=faugeras1993>O. Faugeras. Three-dimensional Computer Vision. MIT Press. (1993). [http://www.amazon.com/Three-Dimensional-Computer-Vision-Artificial-Intelligence/dp/0262061589 ISBN 978-0262061582].</ref> To employ this approach, one requires accurate coordinates of a non-degenerate set of points in 3D space. A common way to achieve this is to construct a camera calibration rig (example below) built from three mutually perpendicular chessboards. Since the corners of each square are equidistant, it is straightforward to compute the 3D coordinates of each corner given the width of each square. The advantage of DLT calibration is its simplicity; arbitrary cameras can be calibrated by solving a single [[System of linear equations#Homogeneous systems|homogeneous linear system]]. However, the practical use of DLT calibration is limited by the necessity of a 3D calibration rig and the fact that extremely accurate 3D coordinates are required to avoid [[Numerical stability|numerical instability]].<ref name=forsyth2002/>
