In this paper, we consider the problem of projective reconstruction based on the factorization method. Unlike existing factorization based methods which minimize the SVD reprojection error, we propose to estimate the projective depths by minimizing the 2-D reprojection errors. An iterative algorithm is developed to minimize 2-D reprojection errors. This algorithm reconstructs the projective depths robustly and does not rely on any geometric knowledge, such as epipolar geometry. Simulation results using synthetic data are given to illustrate the performance of the algorithm. © Springer-Verlag Berlin Heidelberg 2002.
CITATION STYLE
Tang, W. K., & Hung, Y. S. (2002). A factorization-based method for projective reconstruction with minimization of 2-D reprojection errors. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2449 LNCS, pp. 387–394). Springer Verlag. https://doi.org/10.1007/3-540-45783-6_47
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