A Simple, Efficient Method for Realistic Animation of Clouds

1
A Simple, Efficient Method for Realistic
Animation of Clouds

• Yoshinori Dobashi Kazufumi Kaneda Hideo
  Yamashita
• Tsuyoshi Okita Tomoyuki Nishita
• Hiroshima City University Hiroshima
  University University of Tokyo

2
Contents

• Introduction and Motivation
• Simulation
• Rendering
• Results
• Conclusion

3
Introduction
4
Problem Overview

• Realistic modeling and animation of
  (cumulus-type) clouds
• Two sub-problems
• Simulation of cloud formation, extinction and
  advection by wind
• Rendering of the clouds, shadows and shafts of
  light

5
Previous Work - Simulation

• Two categories of simulation methods
• Physical process of fluid dynamics
• Very accurate
• Computationally expensive
• Heuristic approach (procedural modeling)
• Computationally inexpensive
• Easier to implement
• Parameters needed

6
Previous Work - Rendering

• Accounting for multiple scattering of light
• Computationally expensive
• Using 3-D textures for volume density
• Does not handle atmospheric effects such as
  shafts of light
• Rendering shafts of light using ray-tracing or a
  similar method
• Computationally expensive

7
Goals

• Simple and efficient simulation method
• Support of effects such as ...
• Cloud color by single scattering of light
• Shadows of clouds cast on the ground
• Shafts of light through clouds
• Hardware-accelerated rendering
• Visually convincing result

8
Simulation Basic Idea

• Cellular automaton with binary states

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Nagels Method

• Water vapor turns to water to form clouds
• Use Nagels method to simulate cloud formation
• Divide 3-D space evenly into 3-D cells
• Assign boolean variables to each cell
• cld indicates whether cell contain clouds
• hum indicates whether cell has enough water vapor
  to form clouds
• act indicates whether phase transition is ready
  to occur

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Nagels Method (contd)

• Cell properties in the current animation frame ti
  are used to compute the cell properties in the
  next frame ti1
• hum(x, y, z, ti1) hum(x, y, z, ti) Ù Øact(x,
  y, z, ti)
• cld(x, y, z, ti1) cld(x, y, z, ti) Ú act(x,
  y, z, ti)
• act(x, y, z, ti1) Øact(x, y, z, ti) Ù hum(x,
  y, z, ti) Ù act(x, y, z , ti)
• act is a boolean function and its value is
  calculated by the status of act in the
  surrounding cells.

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Cloud Extinction

• Extension to Nagels method
• cld(x, y, z, ti1) cld(x, y, z, ti) Ù IS(rnd gt
  pext(x, y, z, ti))
• hum(x, y, z, ti1) hum(x, y, z, ti) Ú IS(rnd lt
  phum(x, y, z, ti))
• act(x, y, z, ti1) act(x, y, z, ti) Ú IS(rnd lt
  pact(x, y, z, ti))
• rnd uniform random number
• pext probability of cloud extinction
• phum probability of vapor forming
• pact probability of phase transition occurence

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Advection by Wind

• Clouds move, blown by winds
• Wind velocity is different depending on the
  height from the ground
• cld(x, y, z, ti1) cld(x v(z), y, z, ti)
• hum(x, y, z, ti1) hum(x v(z), y, z, ti)
• act(x, y, z, ti1) act(x v(z), y, z, ti)
• v(z) wind velocity, piecewise linear function
• Assumption wind blows towards the direction of
  x-axis

13
Controlling Cloud Motion

• Ellipsoids simulate air parcels
• Vapor and phase transition probability
• higher at center / lower at edge
• Cloud extinction probability
• Lower at center / higher at edge
• Ellipsoids move in direction of wind
• Different kinds of clouds by controlling
  ellipsoid parameters (sizes and position)

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Fast Simulation using Bitfields

• Each cell state (cld, act, hum) can be stored in
  a single bit
• Low memory requirements
• Fast computation of simulation process
• Problem Random numbers
• Solution Precalculated look-up tables

15
Rendering Basic Idea

• Smoothing and volume rendering
• Splatting method for clouds
• Spherical shells for shafts of light

16
Continuous Density Distribution Calculation

• Simulation output is a binary distribution
• Continuous density distribution results from
  smoothing the binary distribution
• Cloud density of a cell is the weighted average
  of the surrounding cells
• Each cell contributes a density distribution over
  an effective radius (?Metaballs)
• Cloud density of an arbitrary point is therefore
  a weighted sum of a simple basis function

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Metaball Billboards

• Generate 2-D texture of metaballs

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Rendering - Step 1

• Set up parallel projection with sun at viewpoint
  and initialize framebuffer to 1.0
• Place billboards at centers of metaballs with
  their normals toward the sun
• Starting with billboard closest to the sun,
  project and blend billboards to framebuffer
• Read back value at projected billboard center to
  get attenuation ratio between sun and metaball

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Rendering Step 1 (contd)

• After all metaballs have been projected,
  framebuffer contains shadow texture

20
Rendering Step 2

• Render all world objects except clouds
• Place billboards at centers of metaballs with
  their normals toward the observer
• Project and blend billboards to framebuffer
  starting with those farthest from viewpoint

21
Rendering Step 2 (contd)
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Shafts of Light

• Render using spherical shells (made of polygons)
• Modify Rendering Step 2 to
• Calculate colors of vertices of shell polygons
  (atmospheric conditions)
• Repeat for all shells (back-to-front)
• Render shell k with additive blending function
  and shadow texture mapping
• Render billboards between shell k-1 and shell k

23
Shafts of Light (contd)
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Results
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Results (contd)
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Conclusion

• Advantages
• Simulation requires little computation
• Memory requirements are small
• Rendering is fast by making use of graphics
  hardware
• Shadows of clouds and shafts of light can also be
  rendered
• Possible improvements
• Effects of terrain under clouds
• Level of detail

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The End

• Questions?