基于深度扫描仪的高辨识度三维人体模型重建方法

3D 照相打印馆人像的打印质量取决于3D 扫描获得的三维人体模型的辨识度。然 而，由于现有3D 人体扫描仪价格昂贵、操作复杂等原因，使得3D 人像打印成本高、耗时长和 打印精度较低。针对这些缺点提出一种基于深度扫描仪重建高辨识度三维人体模型方法。利用 多组深度扫描仪分工协作、优势互补，分别获取高辨识度的人体面部五官点云数据，上半身与 全身表面轮廓点云数据。然后，通过引入特征点和改进的最近点迭代法将采集到的三组点云数 据进行对齐、替换、拼接，将拼接后的无拓扑关系的点云数据进行曲面重构即可获得高辨识度 的三维人体模型。该方法的扫描时间较短，以较低的成本构建了具有高辨识度的三维人像模型。

High Identification 3D Human Body Model Reconstruction MethodBased on the Depth Scanner

The printing quality of 3D portrait in 3D printing photographic house, depend on the 3D scan of the three dimensional human body model identification. However, the traditional 3D body scanner is expensive, complicated manipulation and other reasons, 3D portraits of high printing costs, time-consuming and less accurate printing. In view of these shortcomings a method is proposed based on the deep scanner reconstruct the high degree of recognition three-dimensional human body model. The method combines with the advantages of three groups of different types of the depth scanner, collaboration, respectively to obtain high precision characters facial features and hair detail point cloud data, upper body and the body surface contour point cloud data. Then, the captured three sets of point cloud data will be aligned, replaced, registered by introducing feature points and iterated closest point. The registered of non-topological relations of point cloud data for surface reconstruction can get high precision of 3D human body model. The method of scanning time is shorter, at a relatively low cost to build the 3D portrait with high identification model.