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<p><b>Abstract</b>—In this paper, we describe an efficient method to impose the constraints existing between the collineations between images which can be computed from a sequence of views of a planar structure. These constraints are usually not taken into account by multiview techniques in order not to increase the computational complexity of the algorithms. However, imposing the constraints is very useful since it allows a reduction of geometric errors in the reprojected features and provides a consistent set of collineations which can be used for several applications such as mosaicing, reconstruction, and self-calibration. In order to show the validity of our approach, this paper focus on self-calibration from unknown planar structures proposing a method exploiting the consistent set of collineations. Our method can deal with an arbitrary number of views and an arbitrary number of planes and varying camera internal parameters. However, for simplicity, this papers will only discuss the case with one plane in several views. The results obtained with synthetic and real data are very accurate and stable even when using only few images.</p>
Self-calibration, multiple views, planes, collineation, nonlinear constraints.

E. Malis and R. Cipolla, "Camera Self-Calibration from Unknown Planar Structures Enforcing the Multiview Constraints between Collineations," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 24, no. , pp. 1268-1272, 2002.
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