Selection of reference views for image-based representation

Recently, much attention has been devoted to image-based scene representations. They allow one to construct an arbitrary view of a 3D scene by the interpolation (transfer) from a sparse set of real 2D (reference) images, rather than by rendering an explicit 3D model. While many authors address mainly the purely geometrical aspect of the task, we focus on the problem of how to select the optimal set of reference views. Selection of reference views from a dense set of real primary views is posed as a selection and fitting of parametric models. The selected set must minimize a weighted sum of the number of reference views and the total fit error. We propose two different algorithms for solving this optimization problem. The experimental results on synthetic and real data indicate the feasibility of the approach for 1-DOF camera movement. We discuss the possibility to extend one of the algorithms for more general case.