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- W1998751019 abstract "During the last two decades a lot of researches have been done on the estimation of fundamental matrix, which represents the epipolar geometry between two uncalibrated perspective images. In this paper, a new linear and iterative method is proposed for estimating the fundamental matrix. It preserves the noise model of the observed image points, e.g. a Gaussian noise distribution. When the noise in the measurement of the image points is small, the accuracy of this method is comparable to that of the nonlinear Newton-type optimizers, however, it is much more efficient both because of its linearity and because of its faster convergency." @default.
- W1998751019 created "2016-06-24" @default.
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- W1998751019 date "2003-01-01" @default.
- W1998751019 modified "2023-09-27" @default.
- W1998751019 title "A linear iterative least-squares method for estimating the fundamental matrix" @default.
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- W1998751019 doi "https://doi.org/10.1109/isspa.2003.1224629" @default.
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