Assuming that cameras satisfy pinhole model, we have the following geometry constraints from two perspective views.
Epipoles or epipolar points: e1​,e2​
Epipolar lines: l1​,l2​
Epipolar plane: the plane formed by optical centers O1​,O2​ and point P
Fundamental Matrix
Suppose that the transformation from frame O1​ to frame O2​ can be described by a rotation matrixR and a 3D translation vector t. Let P1​ denote the position of point P in frame O1​, and P2​ the position of point P in frame O2​. We then have the relation
P2​=RP1​+t​​ To derive the beautiful and concise epipolar constraint, which reflects the fact that O1​,O2​ and P are co-planar, we first left-multiply both sides of (1) by[t] to obtain
[t]P2​=[t]RP1​+[t]t​​ where[t] is the bracket notation (i.e. express cross product as a skew-symmetric matrix) of vector t. The term [t]t is always zero and can be crossed out. We then left-multiply both sides of (2) by P2​T to obtain
P2​T[t]P2​=P2​T[t]RP1​​​ The termP2​T[t]P2​ is always zero, because P2​ is perpendicular to[t]P2​ and the dot product of the two is always zero. Finally, we obtain the epipolar constraint
P2​T[t]RP1​=0​​ Let F=[t]R be the Fundamental Matrix, we can rewrite the epipolar constraint in a concise form
P2​TFP1​=0​​ The epipolar constraint in this form relates the coordinates of the same point in two references frames.
Essential Matrix
Recall the pinhole camera model, we can project point P onto the image planes in two views by
Taking the vector product with t, followed by the dot product with p2​ we obtain p2T​[t]×​Rp1​=0.
E=t∧R,F=K−TEK−1,x2T​Ex1​=p2T​Fp1​=0​ its normalized image coordinates (i.e. x1​=K−1p1​), and the