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Fundamental Matrix Computationing the fundamental matrix between two images, one can analyze the 3D structure of the scene, which we discuss in Chaps. . and .. This chapter describes the principle and typical computational procedures for accurately computing the fundamental matrix by considering the statistical properties of the

Militia

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3D Reconstruction from Two Views need to know the camera matrices that specify the positions, orientations, and internal parameters, such as focal lengths, of the two cameras. We estimate them from the fundamental matrix computed from the two images; this process is called self-calibration. We first express the fundamental matrix

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Homography Computationhy from point correspondences over two images is one of the most fundamental processes of computer vision. This is because, among other things, the 3D positions of the planar surface we are viewing and the two cameras that took the images can be computed from the computed homography. Such applicatio

合唱队

Planar Triangulationurface by assuming knowledge of the camera matrices of the two cameras. This process is called planar triangulation. We first show that the homography between the two images is determined from the equation of the plane and the camera matrices. The principle of planar triangulation is to correct the