[1]李静,杨宜民,蔡述庭.多视图的三维景物中平表面重建[J].智能系统学报,2014,9(04):454-460.[doi:10.3969/j.issn.1673-4785.201309029]
 LI Jing,YANG Yimin,CAI Shuting.3-D scene plane reconstruction based on multiple views[J].CAAI Transactions on Intelligent Systems,2014,9(04):454-460.[doi:10.3969/j.issn.1673-4785.201309029]
点击复制

多视图的三维景物中平表面重建(/HTML)
分享到:

《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第9卷
期数:
2014年04期
页码:
454-460
栏目:
出版日期:
2014-08-25

文章信息/Info

Title:
3-D scene plane reconstruction based on multiple views
作者:
李静1 杨宜民2 蔡述庭2
1. 洛阳师范学院 信息技术学院, 河南 洛阳 471022;
2. 广东工业大学 自动化学院, 广东 广州 510090
Author(s):
LI Jing1 YANG Yimin2 CAI Shuting2
1. Academy of Information Technology, Luoyang Normal University, Luoyang 471022, China;
2. School of Automation, Guangdong University of Technology, Guangzhou 510090, China
关键词:
三维景物中平表面重建单应矩阵约束条件智能算法遗传算法
Keywords:
3-D scene planereconstructionhomographyconstraint conditionintelligent algorithmgenetic algorithm
分类号:
TP391.41
DOI:
10.3969/j.issn.1673-4785.201309029
摘要:
针对使用传统的三维景物重建方法用于三维景物中平表面重建而出现的精度低等问题, 提出了2种基于多视图的三维景物中平表面重建模型:最小化反投影误差的平表面重建模型和最小化转移误差的平表面重建模型。第1种模型利用反投影线应与空间平面相交且交于一点, 从而将误差转移到空间平面上进行最小化反投影误差;第2种模型利用二维空间平面与二维图像平面之间的单应转移关系, 从而将误差转移到空间平面上最小化转移误差。这2种模型都采用遗传算法进行优化求解, 从而获得平表面重建结果。实际上, 2种平表面重建方法的基本原理相同, 只是计算复杂度不同。实验结果表明, 2种平表面重建方法的精度基本一致, 而平表面重建的精度大大提高。
Abstract:
With consideration to the problems including low accuracy of the 3-D scene plane reconstruction by using the traditional 3-D reconstruction method, two kinds of 3-D scene plane reconstruction models based on multiple views are presented. One is the model of a scene plane reconstruction based on minimizing the reverse projection error. The other is the model of a scene plane reconstruction based on minimizing the transfer error. The first model uses the knowledge that the reverse projection lines should not only intersect with a scene plane but should also meet at one point in a scene plane, so as to minimize the reverse projection error in the scene plane. The second model uses the transfer relationship between the image plane and the scene plane, so as to minimize the transfer error in the scene plane. Finally, the optimized value is computed by the genetic algorithm. The basic principles of the two methods are the same, and the difference between them is in regard to the computational complexity. The experimental results show that the accuracy of the two methods is almost the same and the accuracy of the 3-D scene plane reconstruction is improved greatly.

参考文献/References:

[1] LINDSTROM P. Triangulation made easy[C]//Proceedings of IEEE Conference Computer Vision Pattern Recognition. San Fransico, USA, 2010: 1554-1561.
[2] TOSSAVAINEN T. Approximate and SQP two view triangulation[C]//Proceedings of 10th Asian Conference Computer Vision. Queenstown, New Zealand, 2010, 3: 1303-1316.
[3] HARTLEY R, ZISSERMAN A. Multiple view geometry in computer vision[M]. Cambridge: Cambridge University Press, 2003: 54-57.
[4] ZACH C, SORMAN M, KARNER K. High-performance multi-view reconstruction[C]//Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission. Chapel Hill, North Carolina, USA, 2006: 113-120.
[5] CHUM O, PAJDLA T, STURM P. The geometric error for homographies[J]. Computer Vision and Image Understanding, 2002, 97(1): 86-102.
[6] KANATANI K, NIITSUMA H. Optimal two-view planar scene triangulation[J]. IPSJ Transactions on Computer Vision and Applications, 2011, 3: 67-79.
[7] OLSSON C, ERIKSSON A. Triangulating a plane[C]//Proceedings of Scandinavian Conference on Image Analysis. Berlin Heidelberg, Germany, 2011: 13-23.
[8] KE Q, KANADA T. Quasiconvex optimization for robust geometric reconstruction[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007, 29(10): 1834-1847.
[9] AGARWAL S, SNAVELY N, SEITZ S M. Fast algorithms for L-infinity problems in multiview geometry[C]//Proceeding of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Anchorage, Alaska, USA, 2008: 24-26.
[10] HARTLEY R, KAHL F, OLSSON C, et al. Verifying globle minima for L sub>2 minimization problems in multiple view geometry[J]. International Journal of Computer Vision, 2013: 288-304.
[11] KAHL F, HARTLEY R. Multiple-view geometry under the L-infinity norm[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008, 30(9): 1603-1617.
[12] LEE H, SEO Y, LEE S W. Removing outliers by minimizing the sum of infeasibilities[J]. Image and Vision Computing, 2010, 28: 881-889.

备注/Memo

备注/Memo:
收稿日期:2013-09-29。
基金项目:国家自然科学基金青年基金资助项目(61201392);广东省自然科学基金资助项目(S2011010004006)
作者简介:杨宜民,男,1945年生,教授,博士生导师,主要研究方向为机器视觉、多机器人技术、人工智能等;蔡述庭,男,1979年生,副教授,博士,主要研究方向为分布式视频编码、人工智能等。
通讯作者:李静,女,1983年生,博士研究生,主要研究方向为计算机视觉、多视图几何、三维重建。E-mail:litangjing61@163.com
更新日期/Last Update: 1900-01-01