Central catadioptric cameras have been extensively adopted in robotics and surveillance due to their extensive field of view.To attain precise 3D information in these applications,it is important to calibrate the catadioptric cameras accurately.The existing calibration techniques either require prior knowledge of the mirror types,or highly depend on a conic estimation procedure,which might be ruined if there are only small portions of the conic visible on calibration images.In this paper,we design a novel planar pattern with concurrent lines as a calibration rig,which is more robust in conic estimation since the relationship among lines is taken into account.Based on the line properties,we propose a rough-to-fine approach suitable for the new planar pattern to calibrate central catadioptric cameras.This method divides the nonlinear optimization calibration problem into several linear sub-problems that are much more robust against noise.Our calibration method can estimate intrinsic parameters and the mirror parameter simultaneously and accurately,without a priori knowledge of the mirror type.The performance is demonstrated by both simulation and a real hyperbolic catadioptric imaging system.
Omnidirectional imaging sensors have been used in more and more applications when a very large field of view is required.In this paper,we investigate the unwrapping,epipolar geometry and stereo rectification issues for omnidirectional vision when the particular mirror model and the camera parameters are unknown in priori.First,the omnidirectional camera is calibrated under the Taylor model,and the parameters related to this model are obtained.In order to make the classical computer vision algorithms of conventional perspective cameras applicable,the ring omnidirectional image is unwrapped into two kinds of panoramas:cylinder and cuboid.Then the epipolar geometry of arbitrary camera configuration is analyzed and the essential matrix is deduced with its properties being indicated for ring images.After that,a simple stereo rectification method based on the essential matrix and the conformal mapping is proposed.Simulations and real data experimental results illustrate that our methods are effective for the omnidirectional camera under the constraint of a single view point.
