Concept

Essential matrix

Summary
In computer vision, the essential matrix is a 3 \times 3 matrix, \mathbf{E} that relates corresponding points in stereo images assuming that the cameras satisfy the pinhole camera model. Function More specifically, if \mathbf{y} and \mathbf{y}' are homogeneous in image 1 and 2, respectively, then : (\mathbf{y}')^\top , \mathbf{E} , \mathbf{y} = 0 if \mathbf{y} and \mathbf{y}' correspond to the same 3D point in the scene. The above relation which defines the essential matrix was published in 1981 by H. Christopher Longuet-Higgins, introducing the concept to the computer vision community. Richard Hartley and Andrew Zisserman's book reports that an analogous matrix appeared in photogrammetry long before that. Longuet-Higgins' paper includes an algorithm for estimating \mathbf{E} from a set of corresponding normalized image coordinates as well as an algorith
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