Five-point relative orientation method based on forward intersection constraints

Abstract

The invention discloses a five-point relative orientation method based on forward intersection constraints. The method comprises the steps: firstly, shooting two images, with different visual angles, of an object to be measured, wherein the two images respectively comprise five points; secondly, constructing a coplanarity equation of the five pairs of points; thirdly, constructing a five-point relative orientation function based on the forward intersection constraints; fourthly, constructing an iterative equation of relative orientation elements, deriving and solving an unconstrained optimization objective function for the five-point relative orientation problem by constructing a homologous image point coplanar condition function containing the forward intersection constraints and orthogonality constraints, and solving the five relative orientation elements through the least-squares generalized inverse algorithm. Compared with an existing five-point algorithm, it can be guaranteed that the five pairs of homologous rays respectively intersect without removing error solutions. In addition, the method is high in solving precision and good in robustness and has practical value.

Description

technical field [0001] The invention relates to the technical field of optical imaging measurement, in particular to a five-point relative orientation method based on forward intersection constraints. Background technique [0002] Camera calibration is one of the hot issues in the research field of optical imaging measurement (such as machine vision, video measurement and digital close-range photogrammetry), and is the basis for realizing high-precision optical imaging measurement. Currently, camera calibration methods can be divided into three categories: [0003] 1) The traditional camera calibration method calculates the internal and external parameters of the camera by establishing the correspondence between the known three-dimensional coordinate points and their image points on the precision-processed calibration block. The advantage of this method is that it can obtain higher precision, but it is not suitable for online calibration and occasions where calibration bloc...

AI Technical Summary

Problems solved by technology

Therefore, it is difficult to ensure the success of the essential matrix solution only relying on the coplanar conditional equations of five pixels with the same name:

[0013] 1) The existing "five-point algorithm" adopts polynomial solving technology, so there are multiple solutions instead of a single solution, and there is a problem of eliminating misunderstandings;

[0014] 2) The coplanarity of five image points with the same name cannot ensure that the five pairs of rays with the same name intersect in pairs, resulting in the failure of the essential matrix solution and the relative orientation failure

[0015] Five-point relative orientation is a classic problem in machine vision, video measurement, and digital close-range photogrammetry. The traditional five-point algorithm uses polynomial solution technology, resulting in heterogeneity of understanding

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