Rendering Mirage Team 3 Seo Hansol, Lim Mingi CS482 Fall 2018 - - PowerPoint PPT Presentation

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Rendering Mirage Team 3 Seo Hansol, Lim Mingi CS482 Fall 2018 - - PowerPoint PPT Presentation

Nov 12, 2022 38 likes •502 views

Rendering Mirage Team 3 Seo Hansol, Lim Mingi CS482 Fall 2018 Midterm Presentation 1 Contents Introduction Background Previous Works Our Ideas 2 Introduction 3 Mirage inferior mirage superior mirage By Conjecture

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Rendering Mirage

Team 3 Seo Hansol, Lim Mingi CS482 Fall 2018 Midterm Presentation

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Contents

  • Introduction
  • Background
  • Previous Works
  • Our Ideas

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Introduction

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Mirage

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inferior mirage superior mirage

By Conjecture Corporation By Shawn Stockman-Malone

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Mirage

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inferior mirage

Both by Ludovica Lorenzelli

superior mirage

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Our Goal

We want to render realistic, artistic mirages.

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By Shawn Stockman-Malone From [ABW14]

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Background

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Mirage Image: The Physics

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By Ludovica Lorenzelli

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Mirage Image: The Physics

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High T → Low ρ → High v → Low n Low T → High ρ → Low v → High n

By Ludovica Lorenzelli

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Mirage Image: The Physics

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High T → Low ρ → High v → Low n Low T → High ρ → Low v → High n

By Ludovica Lorenzelli

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Mirage Image: The Physics

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By Ludovica Lorenzelli

High T → Low ρ → High v → Low n Low T → High ρ → Low v → High n

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Mirage Image: The Physics

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inferior mirage superior mirage

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Previous Works

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Previous Works

  • Modeling refractive index of atmosphere
  • Rendering through refractive index model
  • Artistic editing by user

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Refractive Index Modeling Of Atmosphere

  • Simulation of atmospheric phenomena [GSM*06]
  • Atmospheric Profile Manager (APM)
  • Simplified model of temperature, refractive index similar

to real atmosphere

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Refractive Index Modeling Of Atmosphere

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From [GSM*06] From [GSM*06] From slides of [Choi 17]

Background Inversion Layer Hot Spot Standardized De-standardization

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Rendering Through Refractive Index Model

  • Refractive radiative transfer equation [ABW14]
  • Applies Hamiltonian optics to the rendering equation

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Image from [ABW14]

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Artistic Editing

  • Interactive reflection editing [ROT*09]
  • User controllable reflection, defying physics
  • Intuitive UI

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Image from [ROT*09]

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Artistic Editing

  • State of the art in artistic editing of appearance, lighting

and material [SPN*14]

  • User controlled lighting, BRDF, etc.
  • Goal based interaction; user defines goal, system solves.

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Images from [ABW14]

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Previous Approaches To Mirage Rendering

  • Visual simulation of heat shimmering and mirage

[ZHF*07]

  • Build refractive index from object heat map, renders with

ray marching

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Image from [ZHF*07]

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Artistic Editing For Mirage Image

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Artistic Editing For Mirage Image [Choi 2017]

[Demo video]

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Overview

  • Source-to-Destination Point Pair

○ The user specifies constraints, defined as a set of

  • riginal position (source) + mirage image

position (destination)

  • Perform physically correct light path calculation
  • Use parametric optimization to calculate

○ With an appropriate refractive index distribution model for the optimization

23 This slide is copied from slides of [Choi 17]

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Source-to-Destination Point Pair

24 This slide is copied from slides of [Choi 17]

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Source-to-Destination Point Pair

25 This slide is copied from slides of [Choi 17]

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Source-to-Destination Point Pair

26 This slide is copied from slides of [Choi 17]

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Adapt APM[GSM*06] as a spatial encoding

Refractive Index Distribution Model

27 This slide is copied from slides of [Choi 17]

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Refractive Index Distribution Model

28 This slide is copied from slides of [Choi 17]

Plot of APM vs. New Formulation

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New formulation suggested for the refractive index distribution: Logistic Approximation

Refractive Index Distribution Model

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Spatial Encoding and Optimization

  • Let the m-dimensional spatial encoding of n(x)

be L

  • And let the parameter vector for L be

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Spatial Encoding and Optimization

  • Distance Function

○ Define distance per point pair, as the shortest distance between the Source Point and the light path

31 This slide is copied from slides of [Choi 17]

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Spatial Encoding and Optimization

  • Distance Function

○ For i-th pair, spatial encoding L, and parameter vector k

32 This slide is copied from slides of [Choi 17]

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Spatial Encoding and Optimization

  • Cost Function

○ For i-th pair, spatial encoding L, and parameter vector k ○ solve by Regression

33 This slide is copied from slides of [Choi 17]

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Rendering method

  • Ray-marching algorithm

34 Image from https://computergraphics.stackexchange.com/questions/161/what-is-ray-marching-is-sphere-tracing-the-

same-thing

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Rendering method

  • Ray-marching algorithm

35 [ABW14]

https://github.com/yoonlab/refracti ve-index- editor/blob/master/shaders/compo site.frag

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Limitations

  • This system is focused on creating static scenes

○ This formulation does not consider the spatial location of the hot spot and the inversion layer ○ When you move the camera, you’ll see a different scene than you intended

  • No illumination model
  • Poor, unintuitive UI

⇒ Unrealistic mirage scenes

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Our Ideas

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Areal Hot Spot

  • Hot spot is no longer depends on only height
  • Hot spot has xy-position and size, defined by user
  • Optimize additional parameters using the existing
  • ptimizer
  • By changing the formula to take into account the area
  • f the hot spot, we can see a more realistic scene

even if we move the camera

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Areal Hot Spot

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Hot Spot

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Atmospheric Noise

  • Temperature variance is not smooth in real
  • Air turbulences result in noises in real image
  • We can add some noises to the scene for more realistic

image ○ Temperature noise to model ○ Geometric noise to ray

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Local Illumination Model: Phong Illumination

  • Phong Illumination
  • Complex global illumination is overkill in large outdoor

scene with bright sunlight

  • Phong illumination is simple and plausible enough

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Texture Filtering

  • Mip-mapping
  • Anisotropic filtering
  • Ray differential

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Better UI

  • Point positioning
  • Camera positioning
  • More interactive point addition and rendering; user

should be able to see result of point addition more frequently

  • Point importance

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Better UI: Point Importance

  • User defines optimization rate (intensity) for each point
  • Optimizer has larger margins for less important points

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0.2 0.6 0.2

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Members & Roles

  • Seo Hansol : Setting up the environment, Presentation,

Coding

  • Lim Mingi : Presentation, Coding

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Q & A

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