Related entropy-based Torr-M-Estimators basic matrix robust estimation method

A basic matrix and robust estimation technology, applied in computing, computer components, image data processing, etc., can solve problems such as low accuracy, poor results, long computing time, etc., to improve accuracy and robustness Effect

Active Publication Date: 2018-09-28
XI AN JIAOTONG UNIV
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Problems solved by technology

Based on this problem, people have done a lot of research. The solution methods are divided into three categories: linear method, iterative method and robust solution method. The linear solution method is fast, but when there are wrong matching points, the accuracy is very low. ; The iterative solution method has high precision, but it takes a long time to calculate compared with the linear soluti

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  • Related entropy-based Torr-M-Estimators basic matrix robust estimation method
  • Related entropy-based Torr-M-Estimators basic matrix robust estimation method
  • Related entropy-based Torr-M-Estimators basic matrix robust estimation method

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[0039] Details in each step of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0040] The present invention proposes a Torr-M-Estimators fundamental matrix robust estimation method based on correlation entropy, such as figure 1 As shown, it specifically includes the following steps:

[0041] Step 1: For input such as Figure 4 Two images from different perspectives of the same scene shown, Figure 4 -a is the image of the first perspective, Figure 4 -b is the image corresponding to the second viewing angle. The present invention extracts SIFT feature points as a feature point description operator, and the result is as follows Figure 5 as shown, Figure 5 -a, 5-b represent the SIFT feature points corresponding to the two perspectives. Using the RANSAC method for feature point matching, the results are as follows Figure 6 As shown, at this time, according to the geometric relationship, the corresponding relation...

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Abstract

The invention discloses a related entropy-based Torr-M-Estimators basic matrix robust estimation method. A Torr-M-Estimators algorithm performs weighting processing on a residual error of each matching pair to reduce the influence of an exterior point of the relatively large residual error on an estimation process of a basic matrix, and different weight functions have different optimization results; an information theory-based related entropy function has relatively great advantage in robustness and is more remarkably improved in precision and robustness; data normalization is performed by utilizing a Hartley method, an initial value of the basic matrix is obtained by a linear least square method, a related entropy is a Torr-M-Estimators weight function, a rank of the basic matrix is limited to be 2 by eigenvalue decomposition, and a loop stop condition is determined by a minimum iterative error and a maximum iterative frequency; and an experiment shows that the method has very high estimation precision and robustness and is an important improved method in the basic matrix solving step in the fields of three-dimensional reconstruction, motion estimation, matching tracking and the like.

Description

technical field [0001] The invention belongs to the field of multi-view geometry in computer vision, and is a research invention for solving the basic matrix of the mathematical expression of epipolar constraints in stereo vision, and specifically relates to a Torr-M-Estimators basic matrix robust estimation method based on correlation entropy. Background technique [0002] In the field of computer vision, multi-view geometry is an important basis for computers to express the three-dimensional world through two-dimensional images. figure 2 As shown, the corresponding point m' of the image point m on another image plane must be above its epipolar line e'. The epipolar geometric relationship can be expressed by a matrix of order 3 and rank 2, which is called the fundamental matrix, also known as the F matrix (Fundamental Matrix), and the mathematical expression of the epipolar geometric relationship is m' T Fm=0, where m', m is the matching pair of corresponding feature point...

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Application Information

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IPC IPC(8): G06T17/00G06T7/80G06K9/46
CPCG06T7/80G06T17/00G06T2207/10028G06V10/462
Inventor 张雪涛孙继发聂明显王飞郑南宁
Owner XI AN JIAOTONG UNIV
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