Simultaneous Self-Calibration of a Projector and a Camera Using Structured Light

Abstract

We propose a method for geometric calibration of an active vision system, composed of a projector and a camera, using structured light projection. Unlike existing methods of self-calibration for projector-camera systems, our method estimates the intrinsic parameters of both the projector and the camera as well as extrinsic parameters except a global scale without any calibration apparatus such as a checker-pattern board. Our method is based on the decomposition of a radial fundamental matrix into intrinsic and extrinsic parameters. Dense and accurate correspondences are obtained utilizing structured light patterns consisting of Gray code and phase-shifting sinusoidal code. To alleviate the sensitivity issue in estimating and decomposing the radial fundamental matrix, we propose an optimization approach that guarantees the possible solution using a prior for the principal points. We demonstrate the stability of our method using several examples and evaluate the system quantitatively and qualitatively.