Abstract

Depth inaccuracy greatly affects the quality of free-viewpoint image synthesis. A theoretical framework for a simplified view interpo- lation setup to quantitatively analyze the effect of depth inaccuracy and provide a principled optimization scheme based on the mean squared er- ror metric is proposed. The theory clarifies that if the probabilistic dis- tribution of disparity errors is available, optimal view interpolation that outperforms conventional linear interpolation can be achieved. It is also revealed that under specific conditions, the optimal interpolation con- verges to linear interpolation. Furthermore, appropriate band-limitation combined with linear interpolation is also discussed, leading to an easy algorithm that achieves near-optimal quality. Experimental results using real scenes are also presented to confirm this theory.