Procedural Generation of Multi-Biome Landscapes...Motivation •Huge landscapes as combination of different biomes •Populating the terrain with objects Introduction Previous Work

AutoBiomes

Roland Fischer, Philipp Dittmann, René Weller, Gabriel Zachmann

University of Bremen, Germany

[email protected]

CGI, 20-23 October 2020, Geneva

Procedural Generation of Multi-Biome Landscapes

mailto:[email protected]

The Good Dinosaur [Disney/Pixar]

Motivation

Introduction Previous Work Overview Details Results Conclusion 1

Ghost Recon: Wildlands [Ubisoft]The Good Dinosaur [Disney/Pixar]

Motivation


Ghost Recon: Wildlands [Ubisoft]The Good Dinosaur [Disney/Pixar]

Motivation


VaMEx-VTB [University of Bremen]

Motivation

• Huge landscapes as combination of different biomes


Minecraft

Motivation


• Populating the terrain with objects


Minecraft

Motivation



• Manual creation is not an option


Minecraft

Motivation




• Procedural terrain generation (PTG)


Minecraft

Motivation




• Procedural terrain generation (PTG)

• Much researched, still open challenges


Realism Speed

Usability

Flexibility

Minecraft

Related Work

• Main PTG approaches:

• Synthetic, e.g. noise

• Fast, unintuitive, hard to get realistic results [Thorimbert18]


[Thorimbert18]

Related Work




• Physics-based, e.g. erosion, fluid simulation

• Complex, realistic results, slow [Stam03, Jákó11, Ihmsen14]


[Thorimbert18]

[Jákó11]

Related Work






• Example-based, e.g. image synthesis, DEMs, neural networks

• Realistic, good usability, inflexible [Zhou07, Beckham17, Wulff-Jensen18]


[Thorimbert18]

[Jákó11]

[Zhou07]

Related Work






• Example-based, e.g. image synthesis, DEMs, neural networks

• Realistic, good usability, inflexible [Zhou07, Beckham17, Wulff-Jensen18]

• Also valid for commercial tools (e.g. World Creator, World Machine, Terragen)


[Thorimbert18]

[Jákó11]

[Zhou07]

Our Contributions

• Novel PTG system combining advantages of 3 approaches


Our Contributions


• Effective generation of vast, plausible-looking terrains


Our Contributions



• Multi-biome landscapes


Our Contributions




• Dense, complex asset distribution


Our Contributions





• Easy-to-use, iterative workflow


Our Contributions





• Easy-to-use, iterative workflow

• Unreal Engine 4 integration


Our PTG Pipeline


Rough Base-Terrain

Climate Simulation

Biome-based Terrain

Refinement

Asset Placement

Terrain + Asset

Distribution

User

Parameters

Our PTG Pipeline


Rough Base-Terrain

Climate Simulation

Biome-based Terrain

Refinement

Asset Placement

Terrain + Asset

Distribution

User

Parameters

Noise

Our PTG Pipeline


Rough Base-Terrain

Climate Simulation

Biome-based Terrain

Refinement

Asset Placement

Terrain + Asset

Distribution

User

Parameters

Temperature Wind Biomes

Noise

Precipitation

Our PTG Pipeline


Rough Base-Terrain

Climate Simulation

Biome-based Terrain

Refinement

Asset Placement

Terrain + Asset

Distribution

User

Parameters


Noise DEMs

Precipitation

Our PTG Pipeline


Rough Base-Terrain

Climate Simulation

Biome-based Terrain

Refinement

Asset Placement

Terrain + Asset

Distribution

User

Parameters


Noise Local-to-Global

DEMs

Precipitation

Our PTG Pipeline


Rough Base-Terrain

Climate Simulation

Biome-based Terrain

Refinement

Asset Placement

Terrain + Asset

Distribution

User

Parameters



DEMs

Precipitation

Synthetic

Our PTG Pipeline


Rough Base-Terrain

Climate Simulation

Biome-based Terrain

Refinement

Asset Placement

Terrain + Asset

Distribution

User

Parameters



DEMs

Precipitation

Synthetic Physics-based

Our PTG Pipeline


Rough Base-Terrain

Climate Simulation

Biome-based Terrain

Refinement

Asset Placement

Terrain + Asset

Distribution

User

Parameters



DEMs

Precipitation

Synthetic Physics-based Example-based

Our PTG Pipeline


Rough Base-Terrain

Climate Simulation

Biome-based Terrain

Refinement

Asset Placement

Terrain + Asset

Distribution

User

Parameters



DEMs

Precipitation

Synthetic Physics-based Example-based Mainly Synthetic

Our PTG Pipeline


Rough Base-Terrain

Climate Simulation

Biome-based Terrain

Refinement

Asset Placement

Terrain + Asset

Distribution

User

Parameters



DEMs

Precipitation

Our PTG Pipeline


• Each step is customizable and repeatable

Rough Base-Terrain

Climate Simulation

Biome-based Terrain

Refinement

Asset Placement

Terrain + Asset

Distribution

User

Parameters



DEMs

Precipitation

Our PTG Pipeline



Rough Base-Terrain

Climate Simulation

Biome-based Terrain

Refinement

Asset Placement

Terrain + Asset

Distribution

User

Parameters



DEMs

Precipitation

Our PTG Pipeline



• Direct proxy visualization for quick workflow

Rough Base-Terrain

Climate Simulation

Biome-based Terrain

Refinement

Asset Placement

Terrain + Asset

Distribution

User

Parameters



DEMs

Precipitation

Our PTG Pipeline



• Direct proxy visualization for quick workflow

Rough Base-Terrain

Climate Simulation

Biome-based Terrain

Refinement

Asset Placement

Terrain + Asset

Distribution

User

Parameters



DEMs

Precipitation

Base Terrain Generation

Introduction Previous Work Overview Details Results Conclusion

• Multiple octaves of simplex noise

6




• Lots of parameters for flexibility, fast to compute, scalable

• Other noise combinations possible

6






• Only serves as rough starting terrain, refined later

• No tedious fine-tuning needed

6

Base terrain, water bodies in blue






• Only serves as rough starting terrain, refined later

• No tedious fine-tuning needed

• Easily extendable with sketch-basedediting techniques

6

Base terrain, water bodies in blue

• Two adjustable interpolation modes:

• Bi-linear interpolation

Climate Simulation - Temperature


Temperature, blue = cold, red = hot

-15 32

25 35



• Sine-based interpolation




-15 32

25 35



• Sine-based interpolation

• Adjustable altitude-based decline




-15 32

25 35

Climate Simulation - Wind


• Prevailing wind for moisture distribution

• Iterative, simplified semi-Lagrangian approach

8





• Only self advection and external forces

8






• User specified, persistent external forces on corners

8

0

1







• Iteratively averaging wind vectors with adjacent ones in forward direction

8

2








8

2








• Enables creation of smooth, believable prevailing wind currents

8

Wind vector field

Climate Simulation - Precipitation


• Iterative computation

9




• Water bodies/world borders as moisture sources

9





• Temperature-dependent evaporation

9






• Wind distributes moisture

9







• Dispersion and equalization

9

Grey indicates receiving moisture amount








9

Diffusion based on current moisture








9

Diffusion based on current moisture








9








9

Moisture, low = red, high = blue








• Temperature and moisture-dependent precipitation

9


Precipitation, low = red, high = blue








• Temperature and moisture-dependent precipitation

• Enables phenomena like rain shadows

9


Precipitation, low = red, high = blue

• Biomes classified by temperature and precipitation

Climate Simulation - Biomes



• Discretized Whittaker diagram as lookup table

• Fully customizable or replaceable



Temperature

Pre

cip

ita

tio

n


• Discretized Whittaker diagram as lookup table

• Fully customizable or replaceable



Biome map

Temperature

Pre

cip

ita

tio

n

Biome-Based Terrain Refinement


• Adds biome-specific structures

• DEMs as examples, inherently realistic

Biome map

DEMs





• DEMs, ℎ𝑑, blended with base terrain, ℎ𝑏

Biome map Base terrain Refined terrain

DEMs







DEMs

ℎ 𝑝 = 𝑤𝑏 ⋅ ℎ𝑏 𝑝 + 𝑤𝑑 ⋅ ℎ𝑑(𝑝)







DEMs








DEMs







• Natural biome transitions essential


DEMs








• Further noise-based border distortion


DEMs









• Weighted blending of adjacent DEMs, 𝑖, via 2D kernel


DEMs









• Weighted blending of adjacent DEMs, 𝑖, via 2D kernel

ℎ 𝑝 = 𝑤𝑏 ⋅ ℎ𝑏 𝑝 + 𝑤𝑑 ⋅

𝑖=1

𝑛

𝑤𝑖 ⋅ ℎ𝑑𝑖(𝑝)


DEMs

Procedural Asset Placement


• Iterative, rule-based local-to-global model




• Assets with bilateral placement rules





• Asset hierarchy, assigned to biomes






• Constrained-based placement via dart throwingSample Rnd.

PositionCheck

ConstraintsValid Pos.

n tries






• Constrained-based placement via dart throwing

• Enables emergent multi-object distributions

Sample Rnd.Position

CheckConstraints

Valid Pos.

n tries






• Constrained-based placement via dart throwing

• Enables emergent multi-object distributions

• All seasons with one placement

• Switching asset variants

Sample Rnd.Position

CheckConstraints

Valid Pos.

n tries

Result: Proxy View of Final Terrains


Represents 1600 𝑘𝑚2




Wind




Result: Asset Placement


~ 200,000 instances on final terrain

Result: Asset Placement


Shrubs exclusively in shadow of dense tree clusters Tight clusters of shrubs in open spaces between trees Dense, clumped shrubs around loosely grouped trees

Result: Asset Placement - Seasons


Result: Performance


Complexity:

𝑂 𝑁 ⋅ 𝑘 - N: # cells𝑘: # iterations

Pipeline Step Res. 1 Res. 2 Res. 3

Terrain Gen. 1024 2048 4096

Asset Placing 30 60 120

Rest 128 256 512

Result: Terrain Refinement Performance


Conclusion


• Successful combination of synthetic, physics-basedand example-based PTG

18

Conclusion



• Effective generation of vast, plausible-lookinglandscapes

18

Conclusion




• Varied landscapes as combination of biomes

18

Conclusion





• Procedural, complex rule-based asset placement

18

Conclusion






• Quick, easy-to-use iterative workflow

18

Conclusion






• Quick, easy-to-use iterative workflow

• Unreal Engine 4 integration

18

Future Work

• Consider geological properties and soil types


Future Work


• Add rivers/water bodies and erosion


Future Work



• Generate and combine DEMs using neural networks


Future Work




• Add sketch-based user control


Future Work




• Add sketch-based user control

• Improve efficiency, e.g. multi-threading


Thank you!

[email protected]

Questions?

mailto:[email protected]

Documents

Procedural Generation of Multi-Biome Landscapes...Motivation •Huge landscapes as combination of different biomes •Populating the terrain with objects Introduction Previous Work