Self-recalibration of a structured light system via plane-based homography
Self-recalibration of the relative pose in a vision system plays a very important role in many applications and much research has been conducted on this issue over the years. However, most existing methods require information of some points in general three-dimensional positions for the calibration, which is hard to be met in many practical applications. In this paper, we present a new method for the self-recalibration of a structured light system by a single image in the presence of a planar surface in the scene. Assuming that the intrinsic parameters of the camera and the projector are known from initial calibration, we show that their relative position and orientation can be determined automatically from four projection correspondences between an image and a projection plane. In this method, analytical solutions are obtained from second order equations with a single variable and the optimization process is very fast. Another advantage is the enhanced robustness in implementation via the use of over constrained systems. Computer simulations and real data experiments are carried out to validate our method.
self-recalibration structured light system plane-based homography relative pose eigenvalue decomposition cheirality constraint