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On the Estimation of the Fundamental Matrix: A Convex Approach to Constrained Least-Squares
[chapter]
2000
Lecture Notes in Computer Science
In this paper we consider the problem of estimating the fundamental matrix from point correspondences. It is well known that the most accurate estimates of this matrix are obtained by criteria minimizing geometric errors when the data are a ected by noise. It is also well known that these criteria amount to solving non-convex optimization problems and, hence, their solution is a ected by the optimization starting point. Generally, the starting point is chosen as the fundamental matrix estimated
doi:10.1007/3-540-45054-8_16
fatcat:qm6ya56kvnb33mjqv5pxa6esgu