Globally Optimal 2D-3D Registration from Points or Lines Without Correspondences

被引:32
作者
Brown, Mark [1 ]
Windridge, David [1 ,2 ]
Guillemaut, Jean-Yves [1 ]
机构
[1] Univ Surrey, CVSSP, Guildford GU2 7XH, Surrey, England
[2] Middlesex Univ, Sch Sci & Technol, London NW4 4BT, England
来源
2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV) | 2015年
关键词
POSE;
D O I
10.1109/ICCV.2015.244
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We present a novel approach to 2D-3D registration from points or lines without correspondences. While there exist established solutions in the case where correspondences are known, there are many situations where it is not possible to reliably extract such correspondences across modalities, thus requiring the use of a correspondence-free registration algorithm. Existing correspondence-free methods rely on local search strategies and consequently have no guarantee of finding the optimal solution. In contrast, we present the first globally optimal approach to 2D-3D registration without correspondences, achieved by a Branch-and-Bound algorithm. Furthermore, a deterministic annealing procedure is proposed to speed up the nested branch-and-bound algorithm used. The theoretical and practical advantages this brings are demonstrated on a range of synthetic and real data where it is observed that the proposed approach is significantly more robust to high proportions of outliers compared to existing approaches.
引用
收藏
页码:2111 / 2119
页数:9
相关论文
共 30 条
[1]  
[Anonymous], 2009, International Journal Computer Vision
[2]   Linear pose estimation from points or lines [J].
Ansar, A ;
Daniilidis, K .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2003, 25 (05) :578-589
[3]   A Branch-and-Bound Approach to Correspondence and Grouping Problems [J].
Bazin, Jean-Charles ;
Li, Hongdong ;
Kweon, In So ;
Demonceaux, Cedric ;
Vasseur, Pascal ;
Ikeuchi, Katsushi .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2013, 35 (07) :1565-1576
[4]   OPTIMAL GEOMETRIC MODEL-MATCHING UNDER FULL 3D PERSPECTIVE [J].
BEVERIDGE, JR ;
RISEMAN, EM .
COMPUTER VISION AND IMAGE UNDERSTANDING, 1995, 61 (03) :351-364
[5]  
Bhat K. K. Srikrishna, 2014, 2014 2nd International Conference on 3D Vision (3DV). Proceedings, P155, DOI 10.1109/3DV.2014.27
[6]   Implementation techniques for geometric branch-and-bound matching methods [J].
Breuel, TM .
COMPUTER VISION AND IMAGE UNDERSTANDING, 2003, 90 (03) :258-294
[7]  
Brown M., 2014, P INT C COMP VIS THE
[8]  
Buch A. G., 2013, LECT NOTES COMPUTER, V54-65
[9]   STRUCTURAL MATCHING IN COMPUTER VISION USING PROBABILISTIC RELAXATION [J].
CHRISTMAS, WJ ;
KITTLER, J ;
PETROU, M .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1995, 17 (08) :749-764
[10]  
David P, 2005, IEEE I CONF COMP VIS, P1581