Abstract
The problem of Euclidean 3D reconstruction is closely related to the calibration of the camera. It is well known that self-calibration methods only provide an approximate solution to camera parameters and their accuracy is undermined by the correspondence problem. However, we demonstrate through this article, that recovering the Euclidean 3D structure of a scene can be achieved in an accurate manner without resorting to a highly precise estimate of the intrinsic parameters. Mainly, we describe a three-step procedure in which we jointly use the simplified form of the Kruppa's equations, a normalization of pixel coordinates and the Eight-Point algorithm to recover the three-dimensional structure with high accuracy even in the presence of noise.
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