A Fusion Algorithm of Relative Orientation for Close Range Industrial Photogrammetry

In order to satisfy the multiple-baselines and large-dip-angles close range photogrammetry applied in industry, a fusion algorithm of relative orientation is presented. In this algorithm, the initial values of the relative orientation parameters are established by the decomposition of the essential matrix, and then the precise solution of the parameters are calculated by a nonlinear optimization. First, the relationship between the essential matrix and the orientation parameters is derived by the determinant from the coplanarity condition, and then the rotation matrix and translation vector between two images are calculated by singular value decomposition (SVD) of the essential matrix, including the removal of the pseudo solutions. Second, according to the coplanarity condition equation, the cost function of relative orientation parameters for non-linear optimization is build. Finally, the result in comparison experiment indicates that the fusion algorithm has acquired better stabilization and high precision.