Relative Orientation Algorithm Based on Essential Matrix Factorization and its Application

In close range industrial photogrammetry, handheld cameras generally need to take a large number of photos from multiple angles and positions, making the relative poses between stations complex and unchanged. Therefore, this article proposes a relative orientation algorithm based on essential matrix factorization, which effectively solves the problem of relative orientation between camera stations. Firstly, based on the coplanar conditions in photogrammetry, the relationship between the essential matrix and the two types of parameters of relative orientation, namely the rotation matrix Euler angle and translation vector, is derived; Secondly, a method for calculating the essential matrix from the fundamental matrix is provided. Finally, the unique solutions of the rotation matrix and translation vector are obtained through singular value decomposition. The photogrammetric experiment on the large-sized surface of the box confirmed the effectiveness of the orientation algorithm proposed in this paper.