Tomographic surface reconstruction from point cloud

作者：Nagai Yukie^*; Ohtake Yutaka; Suzuki Hiromasa

来源：Computers & Graphics-UK, 2015, 46: 55-63.

DOI：10.1016/j.cag.2014.09.034

• Surface reconstruction
• Point cloud
• Surface mesh
• Volume data
• Computed tomography

Inspired by computed tomography (Cr), this paper presents a novel surface reconstruction algorithm, tomographic surface reconstruction, to reconstruct a surface mesh from a point cloud equipped with oriented normals. In the process of scanning a real object using an X-ray CT system, it generates a sinogram consisting of projection images that are maps of X-ray transmission lengths, and then, a tomogram (Cr volume) is reconstructed from the sinogram. A hole-free surface mesh is then easily obtained by polygonizing an isosurface. To adopt this CT paradigm to surface reconstruction from a point cloud, only a scheme to generate a sinogram from a point cloud is required. The value of a sinogram for surface reconstruction can be defined as the sum of the distances between the intersecting points of a ray and the underlying surface, which are defined as the maxima of the point density. While ordinary Cr scanning uses projection directions which share a single rotation axis, tomographic surface reconstruction adopts randomly selected projection directions and successfully improved the reconstruction robustness. By applying an iterative CT reconstruction to the sinogram, the algorithm generates a tomogram whose boundary between the foreground and background approximates the surface of the object. The effectiveness for a point cloud with a lack of sampling and outliers is demonstrated from experimental results.

• 出版日期2015-2