基于参数化的三维颅面配准

计算机应用 ›› 2014, Vol. 34 ›› Issue (12): 3589-3592.

基于参数化的三维颅面配准

乔学军¹,²,赵俊莉²,³,⁴,鲁健庆²,³,谢文魁³

1. 西安建筑科技大学理学院,西安 710055
2. 虚拟现实应用教育部工程研究中心，北京 100875
3. 北京师范大学信息科学与技术学院,北京100875
4. 青岛大学软件技术学院,山东青岛 266061

收稿日期:2014-06-27 修回日期:2014-09-16 发布日期:2014-12-31 出版日期:2014-12-01
通讯作者: 赵俊莉
作者简介:乔学军(1970-),男,陕西西安人,副教授,硕士,主要研究方向:计算机图形学；赵俊莉(1977-),女,山西新绛人,讲师,博士研究生,主要研究方向:虚拟现实与可视化；鲁健庆(1988-),男, 山东潍坊人,硕士研究生,主要研究方向:信号与信息处理；谢文魁(1987-),男,江西吉安人,硕士,主要研究方向:计算机图形学。
基金资助:
国家自然科学基金重点项目;中央高校基本科研业务费专项基金资助项目

3D craniofacial registration using parameterization

QIAO Xuejun¹,²,ZHAO Junli¹,³,⁴,LU Jianqing¹,³,XIE Wenkui³

1. Engineering Research Center of Virtual Reality and Applications Ministry of Education (MOE), Beijing 100875, China
2. School of Science, Xi'an University of Architecture and Technology, Xi'an Shaanxi 710055, China;
3. College of Information Science and Technology, Beijing Normal University, Beijing 100875, China;
4. College of Software and Technology, Qingdao University, Qingdao Shandong 266061, China;

Received:2014-06-27 Revised:2014-09-16 Online:2014-12-31 Published:2014-12-01
Contact: ZHAO Junli

摘要/Abstract

摘要：

针对颅面配准问题,提出通过对颅面进行参数化将其转换成二维参数域的对应问题。首先,根据人类的生理特征标定6个特征点,利用这些特征点将颅面转换到一个统一的坐标系以实现姿态和大小的统一；其次,以两个外眼角为约束对参考颅面进行最小二乘保角映射,计算出6个特征点的参数值；然后,以这六个生理特征点的参数值为约束,利用最小二乘保角映射将任一待配准模型映射到二维参数域；最后,根据二维参数域确定三维颅面上的对应点,从而实现三维数据配准。为了验证所提方法,以对应点为控制点,利用薄板样条(TPS)变换把参考颅面变形到目标颅面,以变形后两个模型上对应点之间的几何距离的平均为度量,将所提算法和基于主轴分析的迭代最近点(ICP)配准以及基于随机采样控制点的迭代TPS配准方法进行了比较,实验结果表明,所提算法的配准效果优于其他两种方法。

Abstract:

This paper transfered the problem of the 3D craniofacial registration into the one in 2D parameter domain by using surface parameterization. Firstly, six landmarks on the craniofacial surfaces were calibrated according to the physiological characteristics, and the pose and size of the craniofacial surfaces were normalized by projecting the craniofacial surfaces into a unified coordinate system which was determined by using the six landmarks. Secondly, Least Squares Conformal Mapping (LSCM) was performed for a reference craniofacial surface by pinning two outer corners of the eyes, by which the 2D parameters of the six landmarks were computed. Thirdly, any craniofacial surface could be mapped into a 2D domain using LSCM by pinning the six landmarks. Finally, the 3D point correspondences were obtained by mapping the 2D correspondences into the 3D surfaces. To validate the proposed method, the reference model was deformed into the target one by the Thin Plate Spline (TPS) transform with the corresponding vertices being control points, and the average distance between two corresponding point sets after deformation was computed. By the average distance, the proposed method was compared with the principal axes analysis based ICP (Iterative Closest Point) and the random sampling control points based iterative TPS registration methods. The comparison shows that the proposed approach is more accurate and effective.

中图分类号:

TP301.6

乔学军赵俊莉鲁健庆谢文魁. 基于参数化的三维颅面配准[J]. 计算机应用, 2014, 34(12): 3589-3592.

QIAO Xuejun ZHAO Junli LU Jianqing XIE Wenkui. 3D craniofacial registration using parameterization[J]. Journal of Computer Applications, 2014, 34(12): 3589-3592.

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