Surface reconstruction via efficient and accurate registration of multiview range scans

To address the surface reconstruction issue, this paper proposes an efficient and accurate approach for registration of multiview range scans. It has a good objective function designed, where all multiview registration parameters are involved. To solve this function, the coarse-to-fine approach is proposed, where each range scan should be sequentially registered to a coarse surface model, which is reconstructed by other scans with initial multiview alignment. By applying the trimmed iterative closest point algorithm, it can sequentially obtain good multiview registration results for each scan, which can then be immediately utilized to refine the coarse surface model for registration of other scans. To acquire accurate surface model, several rounds of update should be applied to all range scans involved in the multiview registration. With the increase of update round, it can finally obtain the accurate surface model. Experimental results on public data sets illustrate its superiority over previous approaches.