3D Reconstruction of Array Virtual Camera

In this study, an imaging system combining cameras and rotating Risley prisms is proposed to address the difficulty of considering the field of view and spatial resolution in a target scene's three-dimensional (3D) reconstruction. The imaging system can form a virtual camera array under different Risley prism rotation angles, adjust the array virtual cameras' imaging position using rail movement, and realize a subregional multiview image acquisition in a large field of view. A calibration approach of the array virtual camera's internal and external parameters using a geometrical transformation relationship is proposed, and the subregional 3D point cloud acquisition approach based on the triangulation principle is established, employing the camera projection model and the double-prism refraction model. A prelocalization approach for overlapping regions of multiview pictures is presented on this basis, and a coarse-to-precise subregional point cloud alignment fusion is obtained by integrating the iterative closest neighbor algorithm. The experimental results reveal that the proposed imaging system can achieve largescale and high-resolution 3D target reconstruction and can ensure a 3D reconstruction accuracy due to the coarse-to-precise point cloud alignment approach while enhancing processing efficiency.