On New View Synthesis Using Multiview Stereo

We show that application of modern multiview stereo techniques to the newview synthesis (NVS) problem introduces a number of non-trivial complexities. By simultaneously solving for the colour and depth of the new-view pixels we can eliminate the visual artefacts that conventional NVS-via-stereo suffers. The global occlusion reasoning which has led to considerable improvements in recent stereo algorithms can easily be included in the new algorithm, using a recently improved graph-cut-based optimizer for general multi-label conditional random fields (CRFs). However, the CRF priors that are important to success in stereo cannot be easily applied if the reconstruction is to be computed in the reference frame of the novel view. We address this problem by extending recent work on the fast optimization of texture priors in NVS to model the image edge structure, yielding a synthesis of the two approaches which yields good results on difficult image sequences.