3D coordinate transform model of optical images fusing vector distance information

For reducing the error of affine transform while matching the three-dimensional targets in optical images, the model of optical images matching was extended to three dimension using distance information of high characteristics in optical images (vector distance information), the three-dimensional (3D) coordinate transform was proposed. Theoretical analysis shows that when the optical imaging model was simplified to pinhole imaging model, the error of 3D coordinate transform didn’t exist, while avoiding the nonlinear problem. The amount of calculation of 3D coordinate transform was analyzed using least squares estimation and RANSAC estimation as examples; the amount of calculation of 3D coordinate transform is only four times of affine transform, twice when using RANSAC estimates. The simulation analysis of matching tracking algorithm based on SIFT feature points using 3D coordinate transform was taken by the visual simulation software VegaPrime and MATLAB, and the advantages of 3D coordinate transform has been verified.