Three-Dimensional Reconstruction of Points and Lines with Unknown Correspondence across Images

被引:0
作者
Y.-Q. Cheng
X.G. Wang
R.T. Collins
E.M. Riseman
A.R. Hanson
机构
[1] Carnegie Mellon University,Robotics Institute, NSH
[2] University of Massachusetts,Department of Computer Science
来源
International Journal of Computer Vision | 2001年 / 45卷
关键词
feature correspondence matching; point/line affinity measure; weighted bipartite graph matching; maximum network flow;
D O I
暂无
中图分类号
学科分类号
摘要
Three-dimensional reconstruction from a set of images is an important and difficult problem in computer vision. In this paper, we address the problem of determining image feature correspondences while simultaneously reconstructing the corresponding 3D features, given the camera poses of disparate monocular views. First, two new affinity measures are presented that capture the degree to which candidate features from different images consistently represent the projection of the same 3D point or 3D line. An affinity measure for point features in two different views is defined with respect to their distance from a hypothetical projected 3D pseudo-intersection point. Similarly, an affinity measure for 2D image line segments across three views is defined with respect to a 3D pseudo-intersection line. These affinity measures provide a foundation for determining unknown correspondences using weighted bipartite graphs representing candidate point and line matches across different images. As a result of this graph representation, a standard graph-theoretic algorithm can provide an optimal, simultaneous matching and triangulation of points across two views, and lines across three views. Experimental results on synthetic and real data demonstrate the effectiveness of the approach.
引用
收藏
页码:129 / 156
页数:27
相关论文
共 64 条
[1]  
Boldt M.(1989)Token-based extraction of straight lines IEEE Trans. SMC 19 1581-1594
[2]  
Weiss R.(1986)Extracting straight lines IEEE Trans. PAMI 8 425-455
[3]  
Riseman E.M.(1989)Analysis of preflowpush algorithms for maximum network flow SIAM J. Comput. 18 1057-1086
[4]  
Burns J.B.(1998)The ASCENDER system automated site modeling from multiple aerial images Computer Vision and Image Understanding 72 143-162
[5]  
Hanson A.R.(1995)A system for automated site model acquisition Integrating Photogrammetric Techniques with Scene Analysis and Machine Vision II 7617 244-254
[6]  
Riseman E.M.(1972)Theoretical improvements in algorithmic efficiency for network flowproblems J. Assoc. Comput. Math. 19 248-264
[7]  
Cheriyan J.(1988)A new approach to the maximum-flow problem J. Assoc. Comput. Mach. 35 921-940
[8]  
Maheshwari S.N.(1992)Matching and motion estimation of three-dimensional point and line sets using eigenstructure without correspondences Pattern Recognition 25 271-286
[9]  
Collins R.T.(1989)Correspondence of 2-D projections by bipartite matching Pattern Recognition Letter 9 361-366
[10]  
Cheng Y.Q.(1988)Geometrically constrained multiphoto matching Photogrammetric Engineering and Remote Sensing 54 633-641