84 research outputs found
MatryODShka: Real-time 6DoF Video View Synthesis using Multi-Sphere Images
We introduce a method to convert stereo 360{\deg} (omnidirectional stereo)
imagery into a layered, multi-sphere image representation for six
degree-of-freedom (6DoF) rendering. Stereo 360{\deg} imagery can be captured
from multi-camera systems for virtual reality (VR), but lacks motion parallax
and correct-in-all-directions disparity cues. Together, these can quickly lead
to VR sickness when viewing content. One solution is to try and generate a
format suitable for 6DoF rendering, such as by estimating depth. However, this
raises questions as to how to handle disoccluded regions in dynamic scenes. Our
approach is to simultaneously learn depth and disocclusions via a multi-sphere
image representation, which can be rendered with correct 6DoF disparity and
motion parallax in VR. This significantly improves comfort for the viewer, and
can be inferred and rendered in real time on modern GPU hardware. Together,
these move towards making VR video a more comfortable immersive medium.Comment: 25 pages, 13 figures, Published at European Conference on Computer
Vision (ECCV 2020), Project Page: http://visual.cs.brown.edu/matryodshk
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