High-Fidelity Light Field VR Playback Using NVIDIA GPUs Tim - - PowerPoint PPT Presentation

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High-Fidelity Light Field VR Playback Using NVIDIA GPUs Tim - - PowerPoint PPT Presentation

High-Fidelity Light Field VR Playback Using NVIDIA GPUs Tim Milliron, Vice President of Engineering Nikhil Karnad, Architect for Image-Based Rendering 1 An Introduction to Light Field 2 THE LIGHT FIELD HOW IT WORKS KEY BENEFITS Capture


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High-Fidelity Light Field VR Playback
 Using NVIDIA GPUs

Tim Milliron, Vice President of Engineering Nikhil Karnad, Architect for Image-Based Rendering

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An Introduction to Light Field

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CONFIDENTIAL

THE LIGHT FIELD

KEY BENEFITS

Every pixel contains color, brightness and depth properties (RGBZ)

Every scene becomes a 3D model vs. a flat 2D image

Each captured perspective encodes proper view-dependent illumination HOW IT WORKS

Capture the natural flow of every ray of light

Leverages either hundreds of individual cameras or millions of microscopic lenses

Requires tightly coupled hardware and software

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Light Field for VR

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THE LIGHT FIELD VOLUME

⨠ Capture ray data from every angle at all

locations entering a given volume at high frame rate

⨠ Generate virtual views


from any point within the volume,
 facing any direction,
 with any field of view.

⨠ Breakthrough sense of presence & realism

for live action VR

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THE LIGHT FIELD FOR VR - 6DOF

⨠ Parallax

– Ability to “see behind objects”

⨠ View Dependent Illumination

– Specular highlights, reflections, …


⨠ Truly Correct Stereo

– Any viewing orientation - even when the viewer’s head is sideways – Any inter-ocular distance - adjustable


  • n-the-fly
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Lytro Immerge

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LYTRO IMMERGE

Capture

  • Configurable multi-

camera system

Processing

  • Color matching
  • Depth estimation

Rendering

  • Rendering process to

generate final assets for efficient playback and compression

Playback

  • Light-field playback in

leading HMDs

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CONFIDENTIAL

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PRODUCTION-READY

⨠ Planar configuration comprised of


95 individual cameras

⨠ Nodal capture in 5 “wedges” ⨠ 475 cameras used to synthesize


a full 360 view

⨠ Generates a 1-meter-wide “Viewing Volume” ⨠ Designed for modern high-end production ⨠ Director & film-crew can be behind the camera ⨠ Works well in practical on-set conditions ⨠ Highest resolution camera on the market today -


up to 8k 360 resolution

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CREATING A 360 LIGHT FIELD VOLUME

Lytro Immerge 
 Planar Configuration
 captures the environment from one direction creating a “wedge”

CONFIDENTIAL

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Rotate to Capture “Wedges” 
 five rotations to film a
 full 360 view of the environment

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Light Field Merging
 reconstructs the data into a 360 Light Field volume, enabling 
 6DoF movement for viewers during playback

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What’s the catch?

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What’s the catch?

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100-1,000x data

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The Bad News

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The Good News

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The Good News

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Light Field Capture & Playback is (barely) within reach today…

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Lytro Immerge Rendering & Playback
 with NVIDIA GPUs

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Light Field rendering: Requirements

⨠ Need two views, one per eye ⨠ High quality throughout the 6-

DoF viewing volume

⨠ Close objects need to shift

relative to far ones

⨠ Fill in occlusions seamlessly ⨠ Illumination variation across

views should not be lost

⨠ Low latency, typically 90+ fps

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Light Field rendering: Requirements

Viewing volume

DoF: Degrees of freedom

⨠ Need two views, one per eye ⨠ High quality throughout the 6-

DoF viewing volume

⨠ Close objects need to shift

relative to far ones

⨠ Fill in occlusions seamlessly ⨠ Illumination variation across

views should not be lost

⨠ Low latency, typically 90+ fps

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Viewing volume

Light Field rendering: Requirements

DoF: Degrees of freedom

⨠ Need two views, one per eye ⨠ High quality throughout the 6-

DoF viewing volume

⨠ Close objects need to shift

relative to far ones

⨠ Fill in occlusions seamlessly ⨠ Illumination variation across

views should not be lost

⨠ Low latency, typically 90+ fps

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Viewing volume

Light Field rendering: Requirements

DoF: Degrees of freedom

⨠ Need two views, one per eye ⨠ High quality throughout the 6-

DoF viewing volume

⨠ Close objects need to shift

relative to far ones

⨠ Fill in occlusions seamlessly ⨠ Illumination variation across

views should not be lost

⨠ Low latency, typically 90+ fps

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Viewing volume

Light Field rendering: Requirements

⨠ Need two views, one per eye ⨠ High quality throughout the 6-

DoF viewing volume

⨠ Close objects need to shift

relative to far ones

⨠ Fill in occlusions seamlessly ⨠ Illumination variation across

views should not be lost

⨠ Low latency, typically 90+ fps

DoF: Degrees of freedom

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Viewing volume

⨠ Need two views, one per eye ⨠ High quality throughout the 6-

DoF viewing volume

⨠ Close objects need to shift

relative to far ones

⨠ Fill in occlusions seamlessly ⨠ Illumination variation across

views should not be lost

⨠ Low latency, typically 90+ fps

Light Field rendering: Requirements

DoF: Degrees of freedom

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Light Field rendering: Background

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Theoretical two-plane Light Field parametrization

⨠ Each wedge is a planar camera array ⨠ Captured rays sample the plenoptic

function – Light slab [Levoy and Hanrahan, 1996] – Lumigraph [Gortler et al., 1996] – Digital Light Field Photography [Ng, 2006] – Light Field Camera Design [Wei et al., 2015]

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Light Field rendering: Background

⨠ Each wedge is a planar camera array ⨠ Captured rays sample the plenoptic

function – Light slab [Levoy and Hanrahan, 1996] – Lumigraph [Gortler et al., 1996] – Digital Light Field Photography [Ng, 2006] – Light Field Camera Design [Wei et al., 2015]

Lytro Light Field camera 2012 Lytro ILLUM 2014

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Lytro Immerge rendering: Practice

⨠ LOTS of captured rays!

– Hundreds of cameras – Video capture rate – Tens of billions of rays per sec

⨠ Per-ray payload multiplies

data size

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Subset of the Light Field captured for Hallelujah

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Lytro Immerge rendering: Practice

⨠ We use NVIDIA GPUs to crunch

these massive datasets

⨠ Assuming we could sift through

lots of rays per second during HMD render…

⨠ Upload to GPU would still be a

bottleneck – Bandwidth requirement of hundreds of GB/s

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Image courtesy NVIDIA http://images.nvidia.com/pascal/img/titanx/titanx-design.png HMD: Head-mounted display

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Lytro Immerge rendering: Acceleration

⨠ Goal

– Unburden the GPU from having to consider the entire dataset

⨠ Solution

– A proprietary acceleration structure that caches rays

Camera center

  • f perspective

Eye center

  • f perspective (in HMD)

HMD: Head-mounted display

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Lytro Immerge playback: Example

Left-eye and right-eye views rendered to the HMD

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Limited field of view capture across two wedges

HMD: Head-mounted display

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Lytro Immerge playback: Pipeline

⨠ Load: Cache allows order-of-magnitude improvement

– Under 10 GB/s

⨠ Decode: Proprietary compression technique for further bandwidth

reduction – Both CPU and GPU used

⨠ Shaders: Compute and graphics ⨠ OpenGL and DirectX implementations

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Lytro Immerge playback: Performance

⨠ Require 90 fps or higher, i.e., 11 ms or faster ⨠ Careful balance between compute and graphics ⨠ Average GPU render times for Hallelujah

– 980 Ti : 10.3 ms – Titan X Maxwell : 9.2 ms – Titan X Pascal : 6.5 ms

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Acknowledgements

⨠ Representing the work of the entire LYTRO IMMERGE team ⨠ Shoutouts specifically for this section of the talk

– Kurt Akeley, Trevor Carothers, Zeyar Htet, Derek Pang, Mike Ma, Alex Song, Cathy Ashenbremer

⨠ Contact information

– Nikhil Karnad <nkarnad@lytro.com> – Tim Milliron @timmilliron

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CONFIDENTIAL

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CONFIDENTIAL

QUESTIONS & ANSWERS

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High-Fidelity Light Field VR Playback
 Using NVIDIA GPUs

Tim Milliron, Vice President of Engineering Nikhil Karnad, Architect for Image-Based Rendering

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