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Method of registration for 3D face point cloud data

机译:3D面部点云数据的注册方法

摘要

This paper analyzes the techniques that can be used to perform point cloud data registration for a human face. We found that there is a limitation in full scale viewing on the input data taken from 3D camera which is only represented the front face of a man as the point of view of a camera. This has caused a hole on the surface that is not filled with the point cloud data. This research is done by mapping the retrieved point cloud to the surface of the face template of the human head. By using Coherent Point Drift (CPD) algorithm which is one of the non-rigid registration techniques, the analysis has been done and it shows that the mapping of points for a three-dimensional (3D) face is not done properly where there are some surfaces work well and certain points spread into the wrong area. Consequently, it has resulted in registration failure occurrences due to the concentration of the points which is focusing on the face only.
机译:本文分析了可用于执行人脸点云数据注册的技术。我们发现,从3D相机获取的输入数据的全尺寸查看存在局限性,该输入数据仅代表人的正面作为相机的视点。这导致在表面上没有填充点云数据的孔。这项研究是通过将检索到的点云映射到人脸的面部模板表面来完成的。通过使用非刚性配准技术之一的相干点漂移(CPD)算法,已进行了分析,结果表明,在存在某些缺陷的情况下,三维(3D)面的点映射没有正确完成表面工作良好,某些点散布到错误的区域。结果,由于仅集中在面部上的点的集中而导致出现配准失败。

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