Optical EngineeringMany composite correlation filter designs have been proposed for solving a wide variety of target detection and pattern recognition problems. Due to the large number of available designs, however, it is often unclear how to select the best design for a pa
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We present a camera calibration technique to determine the focal length and the extrinsic parameters of a camera merely by using one perspective view of two coplanar circles with arbitrary radii and topological configuration. We believe our effort is valuable, in that the position of a camera and its focal length are frequently adjusted in many vision applications. In contrast to the iterative optimization technique in previous work, whose convergence relies heavily on proper initialization, we propose a closed-form solution on the basis of simple matrix operations, which turns out to be computationally efficient. It can also be used to initialize existing algorithms for higher accuracy and speed. Our method is based on the projective equation of a circle, first presented here, which naturally encodes the intrinsic and extrinsic camera parameters and the degenerate conic envelope spanned by the image of circular points. Extensive experiments with both synthetic data and real images verify the efficiency and robustness of our technique.