3D Reconstruction Using Low Precision Scanner

The objective of this work is to use low precision laser sensor and create reasonably precise 3D reconstructions. The 3D reconstruction is executed by combining several point clouds obtained from different viewpoints. The proposed method was developed with three main steps: point cloud registration, error compensation and surface reconstruction. The ICP algorithm is improved to execute the point cloud registration: dynamic distance threshold, weighted distance, rigid body restriction and color information. It is shown that using this improved ICP, the number of point correspondences to evaluate the quadratic error converges to a value. The quadratic error can be determined independently of scene complexity. The point cloud errors are compensated using the consensus surface algorithm with signed distance. The surface is reconstructed using the marching cubes algorithm. Several results are shown to demonstrate the reliability of the proposed method.