计算机应用 ›› 2005, Vol. 25 ›› Issue (12): 2845-2848.

• 图形图像处理 • 上一篇    下一篇

一个基本矩阵的鲁棒估计算法

郭继东1,向辉2   

  1. 1.山东经济学院信息管理学院； 2.山东大学计算机科学与技术系
  • 收稿日期:1900-01-01 修回日期:1900-01-01 发布日期:2005-12-01 出版日期:2005-12-01

Robust method for estimating the fundamental matrix

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  1. 1.Department of Information Management,Shandong Economic University,Jinan Shandong 250014,China;2.School of Computer Science and Technology,Shandong University,Jinan Shandong 250013,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2005-12-01 Published:2005-12-01

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摘要： 通过分析基本矩阵的鲁棒估计方法的特点，提出了三点改进：在RANSAC（RANdom SAmpling Consensus）方法中采用了极小化再投影误差判别数据点的类别；给出再投影误差的一阶近似算法；由求出的基本矩阵和局内点数据采用LM算法对结果过一步求精，给出更好的基本矩阵估计值，使得再投影误差进一步减小，避免结果趋于局部极值。合成数据和真实图像实验均证明了该方法的有效性和可靠性。

关键词: 基本矩阵, 再投影误差, LM算法, RANSAC方法

Abstract: After analyzing the characteristics of methods for computing fundamental matrix,a method was presented for robustly estimating fundamental matrix with three improvement.The data set was discriminated into inliers or outliers by minimizing reprojection error.The computation of one order approximation for reprojection error was given.To avoid local minimum,LM algorithm was adopted in last steps of RANSAC(RANdom SAmpling Consensus) algorithm.A very good estimation of fundamental matrix was obtained and the reprojection error was smaller.Experiment results on synthetic and real images demonstrated that the new algorithm is valid and robust.

Key words: fundamental matrix, reprojection error, LM algorithm, RANSAC(RANdom SAmpling Consensus) algorithm

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