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In computer vision, the essential matrix is a matrix, , with some additional properties described below, which relates corresponding points in stereo images assuming that the cameras satisfy the pinhole camera model. ==Function== More specifically, if and are homogeneous ''normalized'' image coordinates in image 1 and 2, respectively, then : if and correspond to the same 3D point in the scene. The above relation which defines the essential matrix was published in 1981 by Longuet-Higgins, introducing the concept to the computer vision community. Hartley & Zisserman's book reports that an analogous matrix appeared in photogrammetry long before that. Longuet-Higgins' paper includes an algorithm for estimating from a set of corresponding normalized image coordinates as well as an algorithm for determining the relative position and orientation of the two cameras given that is known. Finally, it shows how the 3D coordinates of the image points can be determined with the aid of the essential matrix. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「essential matrix」の詳細全文を読む スポンサード リンク
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