Binocular Stereo Vision Three-Dimensional Reconstruction Algorithm Based on ICP and SFM

Currently, the commonly used multi-angle fusion three-dimensional (3D) reconstruction algorithm mainly includes the iterative closest point (ICP) algorithm and the structure from motion (SFM) algorithm. Aiming at the shortcomings of the above algorithms, we propose a multi-angle fusion 3D reconstruction algorithm with binocular stereo based on ICP and SFM. Firstly, the n groups of photos arc taken around the target with binocular cameras by using the SFM algorithm. Then, we manually select the matching feature points of target in each group of binocular images, and calculate the 3D coordinate of matching feature points to generate the n groups of 3D point cloud. Subsequently, the rotation matrix and translation vector within the n groups of 3D point cloud arc calculated and optimized by ICP algorithm. Finally, the n groups of 3D point arc fused, and the 3D geometry of target is recovered by Delaunay triangle. The experimental results show that, the proposed algorithm takes advantages of the binocular cameras, overcomes the disadvantages of ICP and SFM algorithm, and has good vision effect for 3D reconstruction of target.