Iterative Depth Warping
S. Lee (Sungkyunkwan University)
Younguk Kim (Sungkyunkwan University)
E. Eisemann (TU Delft - Computer Graphics and Visualisation)
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Abstract
This article presents an iterative backward-warping technique and its applications. It predictively synthesizes depth buffers for novel views. Our solution is based on a fixed-point iteration that converges quickly in practice. Unlike the previous techniques, our solution is a pure backward warping without using bidirectional sources. To efficiently seed the iterative process, we also propose a tight bounding method for motion vectors. Non-convergent depth holes are inpainted via deep depth buffers. Our solution works well with arbitrarily distributed motion vectors under moderate motions. Many scenarios can benefit from our depth warping. As an application, we propose a highly scalable image-based occlusion-culling technique, achieving a significant speed-up compared to the state of the art. We also demonstrate the benefit of our solution in multi-view soft-shadow generation.