In this work, we use points, lines, and the linear extremal contours of cylinders to estimate the position and orientation of the camera in the world coordinate system. Other line-based p ose estimation methods use the correspondences between 3D lines in space and 2D image lines, although the model and its observation are nite line segments. We present a noise model describing the probabilistic relationship between 3D lines and cylinders and their noisy observations. The noise model takes the

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... te nature of the observation into account. Position and orientation of cameras are estimated using a maximum-likelihood approach. Covariance matrices, con dence limits, and standard translation and rotation errors are estimated by singular value decomposition of the Jacobian matrix. The method p r ovides clear indications on the reliability of each of the estimated p arameters, and enables the user to add appropriate information, in terms of feature correspondence, to improve the accuracy if necessary. Simulation results are used t o c ompare this method with some of the previously published ones. The algorithm is currently being used o n r eal data for the update of 3D CAD models of industrial environments.