A new mesh reconstruction technique, called dividing virtual belt algorithm (DVBA), is proposed for approximating the surface from a set of wire-frame contours. DVBA decomposes the branching region into a set of virtual belts and virtual canyons. A tiling technique based on the divide-and-conquer strategy is also introduced to approximate the surface from the virtual belt, and the virtual canyons are covered by a conventional polygon triangulation technique. The experimental result shows that our method works well even though there are many complicated branches in the object.

This paper addresses a method for constructing surface representation of 3D structures from a sequence of cross-sectional images. Firstly, we propose cell-boundary representation, which is a generalization of PVP method proposed by Yun and Park, and develop an efficient surface construction algorithm from a cell-boundary. Cell-boundary consists of a set of boundary cells with their 1-voxel configurations, and can compactly describe binary volumetric data. Secondly, to produce external surface from the cell-boundary representation, we define 19 modeling primitives (MP) including volumetric, planar and linear groups. Surface polygons are created from those modeling primitives using a simple table look-up operation. Since a cell-boundary can be obtained using only topological information of neighboring voxels, there is no ambiguity in determining modeling primitives which may arise in PVP method. Since our algorithm has data locality and is very simple to implement, it is very appropriate for parallel processing.

In the past decade, significant effort has been made toward increasing the accuracy and robustness of three-dimensional scanning methods. In this paper, we present a new prototype vision system named 3D Model Studio, which has been built to reconstruct a complete 3D model in as less as a few minutes. New schemes for a probe calibration and a 3D data merging (axis consolidation) are employed. We also propose a new semi-automatic contour registration method to generate accurate contour model from 3D data points, along with a contour triangulation based surface reconstruction. Experimental result shows that our system works well for reconstructing a complete 3D surface model of a human body.

A new mesh reconstruction method, called the shrink-wrapped boundary face (SWBF) algorithm, is proposed for approximating a surface from a set of unorganized 3D points. SWBF overcomes the genus-0 spherical topology restriction of previous shrink-wrapping based mesh generation technique. Furthermore, SWBF is much faster since it requires only local nearest-point-search in the shrinking process. Our experimental results demonstrate that SWBF is very robust and efficient, and it is expected to become a general solution for reconstructing a mesh from an unorganized points cloud.

A new hierarchical isosurface reconstruction scheme from a set of tomographic cross sectional images is presented. From the input data, we construct a hierarchy of volume, called the volume pyramid, based on a 3D dilation filter. After extracting the base mesh from the volume at the coarsest level by the cell-boundary method, we iteratively fit the mesh to the isopoints representing the actual isosurface of the volume. The SWIS (Shrink-wrapped isosurface) algorithm is adopted in this process, and a mesh subdivision scheme is utilized to reconstruct fine detail of the isosurface. According to experiments, our method is proved to produce a hierarchical isosurface which can be utilized by various multiresolution algorithms such as interactive visualization and progressive transmission.