High-resolution surface reconstruction based on multi-level implicit surface from multiple range images

In this paper, we propose a method for improving the resolution of a 3D shape reconstructed from multiple range images acquired from a moving target. In our approach, the alignment and surface estimation problems are solved in a simultaneous estimation framework based on multi-level implicit surface. We present results of experiments for evaluating the reconstruction accuracy with different point cloud densities and noise levels which shows that our method achieved good performance even when the input range images were low-resolution and sparse.