In this paper, we propose a patch-based technique for robust background initialization that exploits both spatial and temporal consistency of the static background. The proposed technique is able to cope with heavy clutter, i.e, foreground objects that stand still for a considerable portion of time. First, the sequence is subdivided in patches that are clustered along the time-line in order to narrow down the number of background candidates. Then, a tessellation is grown incrementally by selecting at each step the best continuation of the current background. The method rests on sound principles in all its stages and only few, intelligible parameters are needed. Experimental results show that the proposed algorithm is effective and compares favorably with existing techniques.

In this paper we present a method for novel view synthesis from two uncalibrated reference views. Snapshots of a scene are created as if they were taken from a different "virtual" viewpoint. The relative affine structure is used to describe the geometry of the scene and then to extrapolate and interpolate novel views. The contribution of this paper is an automatic method for specifying the virtual viewpoint in an uncalibrated setting, based on the interpolation and extrapolation of the epipolar geometry linking the reference views. Experimental results using synthetic and real images are shown.