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We study geometrical properties between 2-D image plane and 3-D error space under affine reconstruction. The purpose of our system is to contribute to more accurate 3-D reconstruction by analyzing geometrically 2-D to 3-D relationship. In situation for no missing feature points and no noise in the 2-D observation matrix, the accurate solution is known to be provided by Singular Value Decomposition. However, several feature points of the matrix have not been observed because of occlusions and low image resolution, and so on. In this case, there is no simple solution. To obtain accurate 3-D reconstruction by recovering missing feature points, we propose the analytic approach which can handle the error orientation and distance of missing feature points by the geometrical properties.

Geometrical properties between 2-D image plane and 3-D error space