In this paper we study pose estimation for non-central cameras, using planes. The method proposed uses non-minimal data. Using the homography matrix to represent the transformation between the world and camera coordinate systems, we describe a non-iterative algorithm for pose estimation. In addition, we propose a parameter optimization to refine the pose estimate. We evaluate the proposed solutions against the state-of-the-art method in terms of both robustness to noise and computation time. From the experiments, we conclude that the proposed method is more accurate against noise. We also conclude that the numerical results obtained with this method improve with increasing number of data points. In terms of processing speed both versions of the algorithm presented are faster than the state-of-the-art algorithm.