基于体数据变形的自适应移动立方体算法的研究

 移动立方体（Marching Cubes）算法是一种经典的三维重建方法，但是对采样稀疏的体数据进行重建时，不能满足所需的精确度要求。提出了一种基于体数据变形的自适应移动立方体算法。该算法通过自适应地改变体素顶点的位置，使得体素包含更多的图像信息从而使体素内的三角面片更加逼近等值面；同时，采用了区域增长策略对体数据进行分割从而避免了对整个体素空间的运算；对算法的并行优化提升了算法的三维重建效率。实验证明使用该算法对稀疏体数据进行三维重建，提高了重建的精确度，并且保证了重建的实时性与交互性。

The Research of Extending Marching Cubes with Adaptive Methods Based on Volume Warping

Marching Cubes (MC) algorithm is a typical representative for surface reconstruction method.However there are still some shortcomings about the represent accuracy of the isosurface which extracted from sparse volume. An adaptive algorithm of Marching Cubes based on volume warping is given. The proposed algorithm uses an iterative process to adaptively displaces the vertices of the cubes. After each iteration, the cubes obtain more accurate representations of the isosurface, and the difference between the implicit and the explicit representations is reduced. Region growing strategy is used to segment volume which avoid the calculation for all vertices. And parallel approach is used to optimize the proposed algorithm which promote algorithm-s efficiency. The experiment results show that this algorithm enhance the accuracy and ensure the instantaneity and interactivity of 3D reconstruction for sparse volume.