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Robust and accurate online pose estimation algorithm via efficient three-dimensional collinearity model
Fan BJ(范保杰); Du YK(杜英魁); Cong Y(丛杨)
作者部门机器人学研究室
关键词Iterative Methods Pose Estimation Online Pose Estimation Algorithm Three-dimensional Collinearity Model Noncoplanar Point Configuration Coplanar Point Configuration Principle Depth Relative Depth Iterative Point Camera Coordinate System Three-dimensional Point Set 3d Mode Point Set
发表期刊IET COMPUTER VISION
ISSN1751-9632
2013
卷号7期号:5页码:382-393
收录类别SCI ; EI
EI收录号20134516947730
WOS记录号WOS:000326175300010
产权排序2
资助机构This work has been funded by the Natural Science Foundation of China (grant no. 61203270) and 2012 State Key Laboratory of Robotics Open Project.
摘要In this study, the authors propose a robust and high accurate pose estimation algorithm to solve the perspective-N-point problem in real time. This algorithm does away with the distinction between coplanar and non-coplanar point configurations, and provides a unified formulation for the configurations. Based on the inverse projection ray, an efficient collinearity model in object-space is proposed as the cost function. The principle depth and the relative depth of reference points are introduced to remove the residual error of the cost function and to improve the robustness and the accuracy of the authors pose estimation method. The authors solve the pose information and the depth of the points iteratively by minimising the cost function, and then reconstruct their coordinates in camera coordinate system. In the following, the optimal absolute orientation solution gives the relative pose information between the estimated three-dimensional (3D) point set and the 3D mode point set. This procedure with the above two steps is repeated until the result converges. The experimental results on simulated and real data show that the superior performance of the proposed algorithm: its accuracy is higher than the state-of-the-art algorithms, and has best anti-noise property and least deviation by the influence of outlier among the tested algorithms.
语种英语
WOS标题词Science & Technology ; Technology
WOS类目Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
关键词[WOS]OBJECT POSE ; PERSPECTIVE ; IMAGES ; LINES
WOS研究方向Computer Science ; Engineering
引用统计
文献类型期刊论文
条目标识符http://ir.sia.cn/handle/173321/14048
专题机器人学研究室
通讯作者Fan BJ(范保杰)
作者单位1.College of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210046, China
2.State Key Laboratory of Robotics, Shenyang Institute Automation, Chinese Academy of Sciences, Shenyang 110016, China
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GB/T 7714
Fan BJ,Du YK,Cong Y. Robust and accurate online pose estimation algorithm via efficient three-dimensional collinearity model[J]. IET COMPUTER VISION,2013,7(5):382-393.
APA Fan BJ,Du YK,&Cong Y.(2013).Robust and accurate online pose estimation algorithm via efficient three-dimensional collinearity model.IET COMPUTER VISION,7(5),382-393.
MLA Fan BJ,et al."Robust and accurate online pose estimation algorithm via efficient three-dimensional collinearity model".IET COMPUTER VISION 7.5(2013):382-393.
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