Method for three-dimensional reconstruction of dynamic stereo vision based on line structured light using global optimization

Abstract

To overcome the limitation of the measurement range of static stereo vision, a three-dimensional (3-D) reconstruction method of dynamic stereo vision based on line structured light for metal surface is presented in this paper. The dynamic stereo vision is mainly composed of binocular cameras and a laser line generator, and moves along a horizontal guide rail. The intrinsic parameters of the cameras and the rotation and translation of the right camera relative to the left camera are previously obtained by Zhang’s method. To obtain the 3-D coordinates of the line structured light fringe in each position, the sub-pixel coordinates of the fringe center are extracted by Steger algorithm, and a joint calibration method between single camera and a laser line generator is proposed. The joint calibration method calculates the plane equation of the line structured light by using multiple checkerboard images with projected structured light line. To unify the 3-D coordinates of structured light fringe in each position to the reference coordinate system, the rotation and translation of the camera in each position relative to the reference position (called absolute pose) should be solved. The direct linear transformation method is firstly used to calculate the rough relative pose between adjacent frames, and principle of re-projection error minimization in object space is used to obtain the refined relative pose. Instead of using step-by-step transfer method, the absolute pose of the camera in each position is eventually calculated by using global optimization algorithm after the relative pose between all adjacent frames are obtained. Computer simulation and abundant experimental data validate the effectiveness of proposed method. The proposed 3-D reconstruction method using global optimization is respectively compared with step-by-step transfer method based on pixel re-projection error minimization and re-projection error minimization in object space. The experimental results reflect that our method is superior to step-by-step transfer method, and the 3-D reconstruction accuracy is improved by 28.05 % after global optimization.