[1]谢晓燕,吴锦桥. 一种全自动三维点云配准及比例约束方法[J].计算机技术与发展,2015,25(03):63-66.
　XIE Xiao-yan,WU Jin-qiao. An Automatic Method of 3 D Point Cloud Registration and Dimension Adjustment[J].,2015,25(03):63-66.
点击复制

 一种全自动三维点云配准及比例约束方法()
分享到：

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
25
期数:
2015年03期
页码:
63-66
栏目:
智能、算法、系统工程
出版日期:
2015-03-10

文章信息/Info

Title:
 An Automatic Method of 3 D Point Cloud Registration and Dimension Adjustment
文章编号:
1673-629X（2015)03-0063-04
作者:
 谢晓燕; 吴锦桥
 西安邮电大学 计算机学院
Author(s):
 XIE Xiao-yan ; WU Jin-qiao
关键词:
 ; 点云; 点云配准; 比例约束; 三维重建
Keywords:
 ; point cloud ; point cloud registration;  scale adjustment ; 3D reconstruction
分类号:
TP399
文献标志码:
A
摘要:
 为了能够对初始相对位置不确定，且尺寸互不一致的多块三维点云进行配准，并对配准后的点云进行尺寸调整，提出了一种新的全自动点云配准及比例约束方法。利用三维重建过程中的相机参数信息，先匹配出特征同名点对，再解算旋转变换矩阵，最后依据摄影测量理论中的共线方程，采用空间后方交会方法求解出点云的真实尺寸。实验结果表明，所提方法能较好地实现初始位置不确定的多块点云之间的配准及三维尺寸调整；另外，相对于最近迭代点算法，新方法实现简单，能获得较好的配准精度。
Abstract:
 To register the multi-blocks of 3D point cloud which its initial relative position is uncertain and the dimension is different by each other and adjust their dimension,propose a fully new automatic method of 3D point cloud registration and dimension adjustment. First search the feature same-name point pairs by using the camera parameter information produced in the process of three-dimension re-construction,and then compute rotation matrix based on same-name point pairs. Finally,calculate the point cloud real dimension accord-ing to the theory of classical photogrammetry and space resection. Experimental results show that the method can accurately accomplish the registration and dimension adjustment of multi-block point cloud which its initial relative position is uncertain. In addition,the new method proposed can also be implemented easily and get good performance at the aspect of accuracy.

相似文献/References:

[1]赵越超 李忠科 王勇 吕培军.基于OpenGL的三维牙颌模型可视化研究[J].计算机技术与发展,2008,(01):119.
　ZHAO Yue-chao,LI Zhong-ke,WANG Yong,et al.Research of 3D Dental Visualization Based on OpenGL[J].,2008,(03):119.
[2]张琴 蔡勇.支持向量学习机在点云去噪中的应用[J].计算机技术与发展,2011,(06):85.
　ZHANG Qin,CAI Yong.Application of Support Vector Machine in Point Clouds Denoising[J].,2011,(03):85.
[3]周春艳 李勇 邹峥嵘.三维点云ICP算法改进研究[J].计算机技术与发展,2011,(08):75.
　ZHOU Chun-yan,LI Yong,ZOU Zheng-rong.Three-Dimensional Cloud ICP Algorithm Improvement[J].,2011,(03):75.
[4]张志宏,吴庆波,邵立松,等.基于飞腾平台TOE协议栈的设计与实现[J].计算机技术与发展,2014,24(07):1.
　ZHANG Zhi-hong,WU Qing-bo,SHAO Li-song,et al. Design and Implementation of TCP/IP Offload Engine Protocol Stack Based on FT Platform[J].,2014,24(03):1.
[5]梁文快,李毅. 改进的基因表达算法对航班优化排序问题研究[J].计算机技术与发展,2014,24(07):5.
　LIANG Wen-kuai,LI Yi. Research on Optimization of Flight Scheduling Problem Based on Improved Gene Expression Algorithm[J].,2014,24(03):5.
[6]黄静,王枫,谢志新,等. EAST文档管理系统的设计与实现[J].计算机技术与发展,2014,24(07):13.
　HUANG Jing,WANG Feng,XIE Zhi-xin,et al. Design and Implementation of EAST Document Management System[J].,2014,24(03):13.
[7]侯善江[],张代远[][][]. 基于样条权函数神经网络P2P流量识别方法[J].计算机技术与发展,2014,24(07):21.
　HOU Shan-jiang[],ZHANG Dai-yuan[][][]. P2P Traffic Identification Based on Spline Weight Function Neural Network[J].,2014,24(03):21.
[8]李璨,耿国华,李康,等. 一种基于三维模型的文物碎片线图生成方法[J].计算机技术与发展,2014,24(07):25.
　LI Can,GENG Guo-hua,LI Kang,et al. A Method of Obtaining Cultural Debris’ s Line Chart Based on Three-dimensional Model[J].,2014,24(03):25.
[9]翁鹤,皮德常. 混沌RBF神经网络异常检测算法[J].计算机技术与发展,2014,24(07):29.
　WENG He,PI De-chang. Chaotic RBF Neural Network Anomaly Detection Algorithm[J].,2014,24(03):29.
[10]刘茜[],荆晓远[],李文倩[],等. 基于流形学习的正交稀疏保留投影[J].计算机技术与发展,2014,24(07):34.
　LIU Qian[],JING Xiao-yuan[,LI Wen-qian[],et al. Orthogonal Sparsity Preserving Projections Based on Manifold Learning[J].,2014,24(03):34.

更新日期/Last Update: 2015-04-30