Re-projective Pose Estimation of a Planar Prototype

We present an approach for robust pose estimation of a planar prototype. In fact, there are many applications in computer graphics in which camera pose tracking from planar targets is necessary. Unlike many other approaches our method minimizes the Euclidean error to re-projected image points. There is a number of recent pose estimation methods, but all of these algorithms suffer from pose ambiguities. If we know the positions of some points on the plane we can describe the 3D position of the planar prototype as a solution of an optimization problem over two parameters. Based on this formulation we develop a new algorithm for pose estimation of a planar prototype. Its robustness is illustrated by simulations and experiments with real images.