A Statistical Model for Disocclusions in Depthbased Novel View Synthesis The occurrence of missing regions in output images is a critical issue when rendering a scene from novel vantage points using depthbased view synthesis. These regions typically have to be filled using inpainting algorithms, which are slow and might yield unconvincing results. Understanding the likelihood of the occurrence of these missing regions can help us design better, applicationspecific data representations and camera systems by knowing which vantage points should be captured and stored to minimize disocclusion holes in the synthesized novel views. In this paper, we propose a statistical model that predicts the likelihood of missing data in synthesized images as a function of the viewpoint translation. Scenedependent model parameters are efficiently estimated using simple shift and scaling transformations on the source depth images without needing view synthesis.

A Novel Algebaric Variety Based Model for High Quality FreeViewpoint View Synthesis on a Krylov Subspace This paper presents a new depthimagebased rendering algorithm for freeviewpoint 3DTV applications. The cracks, holes, ghost countors caused by visibility, disocclusion, resampling problems associated with 3D warping lead to serious rendering artifacts in synthesized virtual views. This challenging problem of hole filling is formulated as an algebraic matrix completion problem on a higher dimensional space of monomial features described by a novel variety model. The highlevel idea of this work is to exploit the linear or nonlinear structures of the data and interpolate missing values by solving algebraic varieties associated with Hankel matrices as a member of Krylov subspace. The proposed model effectively handles artifacts appear in widebaseline spatial view interpolation and arbitrary camera movements. Our model has a low runtime and results excel with stateoftheart methods in quantitative and qualitative evaluation.