Abstract
This paper studies the geometrical recovery of an incomplete observation matrix for converting existing 2D video sequences to 3D content. In situations when converting previously recorded monoscopic video to 3D, several entries of the observation matrix have not been observed and other entries have been perturbed by the influence of noise. In such cases, there is no simple solution for SVD factorization for shape from motion. In this paper, a new recovery algorithm is proposed for recovering missing feature points, by minimizing the influence of noise, using iteratively geometrical correlations between a 2D observation matrix and 3D shape. Results in practical situations demonstrated with synthetic and real video sequences verify the efficiency and flexibility of the proposed method.
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