<aside> 💡 This is a personal review note. Most of the explanations come from textbooks or online resources, especially the classic vSLAM book: Basic Knowledge on Visual SLAM: From Theory to Practice. For further details, please refer to the References section at the end of this page. if you need more information, please leave a comment.

</aside>

Epipolar Geometry

<aside> 💡 The Epipolar constraint reduces the correspondence problem to a 1D search along an epipolar line.

</aside>

Basic Knowledge on Visual SLAM: From Theory to Practice

Basic Knowledge on Visual SLAM: From Theory to Practice

Two frames $I_1,I_2$. The motion from the $I_1$ to $I_2$ as $\bold{R}$,$\bold{t}$ and the centers of the two cameras as $O_1$,$O_2$. Consider we have a feature point $p_1$ in $I_1$ and it’s corresponds feature point $p_2$ in $I_2$ and the match is correct (no error). the $\overrightarrow{O_1p_1}$ and the $\overrightarrow{O_2p_2}$ will intersect at $P$ in the 3D space. we have Epipolar geometric relationship between them.

Epipolar geometry terms

Geometric relationship

Epipolar Constraint

Epipolar Constraint Derivation

Define the spatial position of $P$ in the first frame to be:

$$ \bold{P}=\begin{bmatrix} X &Y&Z\end{bmatrix}^T $$