如何将从基本矩阵获得的相机姿态(转换矩阵)转换为世界坐标系 [英] How to convert camera pose (Translation matrix) obtained from the essential matrix to world coordinate system

问题描述

我从基本矩阵中提取了旋转和平移矩阵.翻译向量具有尺度模糊性.因此，我无法定义其真实"值.

I have extracted Rotation and Translation matrices from the essential matrix. The translation vector has a scale ambiguity. Therefore, I couldn't define its "true" values.

我的步骤如下:

F=estimateF(matches1,matches2,'RANSAC')
E=K2'*F*K1
[U S V]=svd(E)
s=(S(1,1)+S(2,2))/2
S=diag([s s 0])
E_new=U*S*V'
[U S V]=svd(E_new);
R1=U*W*V'
R2=U*W'*V';
t1=U(:,3);
t2=-t1

我的问题是如何以毫米为单位定义第二个摄像头相对于第一个摄像头的平移.

My problem is how to define the translation of the second camera from the first one in mm.

推荐答案

除非您知道将点与现实世界联系起来的更多信息，否则不可能恢复绝对比例.

Unless you know some more information that ties your points to the real world, it's not possible to recover the absolute scale.

例如，如果匹配您知道其尺寸以毫米为单位的校准棋盘的正方形的角，那么您将能够知道以mm为单位的摄像机彼此之间的距离.

For example, if the matches where corners of squares of a calibration chessboard of which you know the size in mm, then you would be able to know how far cameras are from each other in mm.

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