Iterative Depth Warping

Sungkil Lee, Younguk Kim, Elmar Eisemann

Research output: Contribution to journalArticleScientificpeer-review

15 Citations (Scopus)
175 Downloads (Pure)


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.
Original languageEnglish
Article number177
JournalACM Transactions on Graphics
Issue number5
Publication statusPublished - 2018

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