English

应用科学学报 ›› 2011, Vol. 29 ›› Issue (6): 577-584.doi: 10.3969/j.issn.0255-8297.2011.06.005

• 信号与信息处理 • 上一篇    下一篇

综合重构与正交迭代位姿估计算法

郭军1;2， 董新民1， 王龙1   

  1. 1. 空军工程大学工程学院，西安710038
    2. 93716部队57分队，天津301716
  • 收稿日期:2010-12-26 修回日期:2011-05-07 出版日期:2011-11-30 发布日期:2011-11-27
  • 通信作者: 郭军，博士生，研究方向：飞行器非线性飞行控制、视觉导航，E-mail：gj_lockon@163.com；董新民，教授，博导，研究方向：飞行器控制理论与应用、视觉导航，E-mail：dongxinmin@139.com
  • 作者简介:郭军，博士生，研究方向：飞行器非线性飞行控制、视觉导航，E-mail：gj_lockon@163.com；董新民，教授，博导，研究方向： 飞行器控制理论与应用、视觉导航，E-mail：dongxinmin@139.com
  • 基金资助:

    航空科学基金(No.2008ZC01006)资助

Pose Estimation Based on Integrated Reconstruction and Orthogonal Iteration

GUO Jun1;2, DONG Xin-min1, WANG Long1   

  1. 1. Engineering Institute, Air Force Engineering University, Xi’an 710038, China
    2. 57 Detachment, 93716 Troops, Tianjin 301716, China
  • Received:2010-12-26 Revised:2011-05-07 Online:2011-11-30 Published:2011-11-27

PDF

1556

被引次数

2

摘要：

摘要： 多摄像机系统(multiple camera systems, MCS)在机器视觉领域成为研究热点. 针对MCS的位姿估计问题提出了一种新的综合重构与正交迭代算法，并引入广义摄像机模型来描述MCS以方便算法推导. 为充分利用MCS提供的冗余测量信息，将观测到的参考点进行分类，并构建了加权目标函数，综合了最优绝对定向解和正交迭代(orthogonal iteration, OI)算法的优点. 三维重构信息的引入不仅克服了OI算法的位姿模糊，而且提高了位姿估计的收敛速度和鲁棒性. 采用了自适应权值方法降低重构误差对最终估计的影响. 仿真结果验证了提出算法的有效性和优越性.

关键词: 机器视觉, 多摄像机系统, 位姿估计, 位姿模糊, 正交迭代, 自适应权值

Abstract:

Abstract: Multiple camera systems (MCS) have attracted increasing attention in machine vision. Regarding pose estimation of MCS, a novel integrated reconstruction and orthogonal iteration algorithm is proposed. A general camera model is introduced to formulate MCS to derive the algorithm. To make full use of  the redundant measurements of MCS, the observed reference points are classified, and a weighted objective function is constructed. Using the objective function, advantages of the optimal absolute orientation solution (OAOS) and the orthogonal iteration (OI) algorithm are combined. Introduction of 3D reconstructed information not only overcomes the pose ambiguity of OI but also improves convergence and robustness in pose estimation. The effects of reconstructed error on final estimation are reduced using an adaptive weighting method. Simulation results show effectiveness and superiority of the proposed algorithm.

Key words: machine vision, multiple camera systems, pose estimation, pose ambiguity, orthogonal iteration, adaptive weighting

中图分类号: