“Immersive Light Field Video with a Layered Mesh Representation” by Broxton, Flynn, Overbeck, Erickson, Hedman, et al. …

  • ©Michael Broxton, John Flynn, Ryan S. Overbeck, Daniel Erickson, Peter Hedman, Matthew DuVall, Jason Dourgarian, Matt Whalen, Jay Busch, and Paul E. Debevec




    Immersive Light Field Video with a Layered Mesh Representation

Session/Category Title: Systems and Software



    We present a system for capturing, reconstructing, compressing, and rendering high quality immersive light field video. We accomplish this by leveraging the recently introduced DeepView view interpolation algorithm, replacing its underlying multi-plane image (MPI) scene representation with a collection of spherical shells that are better suited for representing panoramic light field content. We further process this data to reduce the large number of shell layers to a small, fixed number of RGBA+depth layers without significant loss in visual quality. The resulting RGB, alpha, and depth channels in these layers are then compressed using conventional texture atlasing and video compression techniques. The final compressed representation is lightweight and can be rendered on mobile VR/AR platforms or in a web browser. We demonstrate light field video results using data from the 16-camera rig of [Pozo et al. 2019] as well as a new low-cost hemispherical array made from 46 synchronized action sports cameras. From this data we produce 6 degree of freedom volumetric videos with a wide 70 cm viewing baseline, 10 pixels per degree angular resolution, and a wide field of view, at 30 frames per second video frame rates. Advancing over previous work, we show that our system is able to reproduce challenging content such as view-dependent reflections, semi-transparent surfaces, and near-field objects as close as 34 cm to the surface of the camera rig.

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