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山东大学学报(理学版)

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一种新型的本质矩阵解析分解算法

吴春富1,唐庆顺1,谢煌生1,周风余2*   

  1. 1.龙岩学院物理与机电学院, 福建 龙岩 364012; 2.山东大学控制科学与工程学院, 山东 济南 250061
  • 收稿日期:2014-01-03 出版日期:2014-03-20 发布日期:2014-05-29
  • 通讯作者: 周风余(1969- ),男,教授,博士生导师,博士,研究方向为智能机器人、智能控制方法等. E-mail:zhoufengyu@sdu.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(61375084)

A novel analytical essential matrix decomposition algorithm#br#

WU Chun-fu1, TANG Qing-shun1, XIE Huang-sheng1, ZHOU Feng-yu2*   

  1. 1. School of Physics and Mechanical and Electrical, Longyan College, Longyan 364012, Fujian, China;
    2. School of Control Science and Engineering, Shandong University, Jinan 250061, Shandong, China
  • Received:2014-01-03 Online:2014-03-20 Published:2014-05-29

摘要: 为了由本质矩阵分解出两摄像机的相对位姿,提出了一种新型的本质矩阵解析分解算法。首先,利用本质矩阵秩2的属性求出两摄像机间的平移量;然后,利用求解旋转矩阵方程组的方法求出两摄像机间的旋转量;最后,利用直接求取空间3D点成像深度的方法快速从四组分解结果中确定出满足空间3D点可见性约束的惟一正确解。实验结果表明,本文提出的分解算法不仅避免了对本质矩阵进行复杂耗时的奇异值分解运算,而且分解出的四组解析解具有直观且明确的几何意义,同时因为完全避免了景物结构的3D重建,大大简化了惟一解确定过程,降低了惟一解确定难度。

关键词: 本质矩阵分解, 相对定向, 多视图几何

Abstract:  For purpose of acquiring the pose and position information of two cameras from essential matrix decomposition efficiently, a novel analytical essential matrix decomposition method is proposed. Firstly, by taking essential matrix’s rank 2 property into account, the position information of the two cameras corresponding to two views respectively is acquired. Secondly, the pose information is obtained through solving rotation matrix equations. Finally, in order to distinguish the unique solution that satisfies the reference-point visibility constraint quickly, the 3D point’s imaging depths are obtained directly. The experimental results show that, the proposed method not only avoids the time consuming singular value decomposition operation, but also acquires four analytical solutions that have intuitive and explicit geometric meanings, meanwhile because of the avoidance of the scene structure’s 3D reconstruction, the process of unique solution determination is simplified greatly.

Key words: relative orientation, essential matrix decomposition, multiple view geometry

[1] 杨元慧,李国栋,吴春富,王小龙. 单目视觉SLAM车载摄像机快速位姿估计及景物重构[J]. 山东大学学报(理学版), 2016, 51(12): 116-124.
[2] 唐庆顺, 吴春富, 李国栋, 王小龙, 周风余. 移动机器人车载摄像机位姿的高精度快速求解[J]. 山东大学学报(理学版), 2015, 50(03): 32-39.
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