Camera calibration using spheres: a semi-definite programming approach

Vision algorithms utilizing camera networks with a common field of view are becoming increasingly feasible and important. Calibration of such camera networks is a challenging and cumbersome task. The current approaches for calibration using planes or a known 3D target may not be feasible as these objects may not be simultaneously visible in all the cameras. In this paper, we present a new algorithm to calibrate cameras using occluding contours of spheres. In general, an occluding contour of a sphere projects to an ellipse in the image. Our algorithm uses the projection of the occluding contours of three spheres and solves for the intrinsic parameters and the locations of the spheres. The problem is formulated in the dual space and the parameters are solved for optimally and efficiently using semidefinite programming. The technique is flexible, accurate and easy to use. In addition, since the contour of a sphere is simultaneously visible in all the cameras, our approach can greatly simplify calibration of multiple cameras with a common field of view. Experimental results from computer simulated data and real world data, both for a single camera and multiple cameras, are presented.