“Computer Modelling of Fallen Snow” by Paul Fearing

1. “Computer Modelling of Fallen Snow”by Paul Fearing Presented by Luv Kohli COMP238 October 29, 2002

2. The Problem • Want to generate realistic “snowy worlds” • Need to determine: • how much snow falls on a scene • where this snow accumulates

3. Previous work • Premoze, et al. • Mostly concerned with far away landscapes • Uses digital elevation model enhanced with aerial photo • Much larger scale

4. Basic Algorithm (Fearing) • Two stages • Snow accumulation stage • How much snow accumulates per surface • Snow stability stage • Resolves unstable snow surfaces

5. Snow accumulation stage • Attempt to simulate “flake flutter” • Shoot snow particles from “launch sites” towards sky • Like ray tracing, but not straight lines • Piecewise linear path towards sky

6. Flake flutter Circles of varying radius Random points on circles Flake path

7. Snow accumulation stage • 10-15 flakes from each launch site shot upwards • until blocked – ‘hit’ • or until sky reached – ‘miss’ • Gives an idea of launch site’s occlusion from sky • Snow accumulation is used to add snow as 3D surfaces above model

8. Importance ordering • Each launch site given a priority based on several factors • Completeness • Area • Neighborhoods • etc.

9. Occlusion boundaries

10. Launch site meshing • Sites represented as triangles generated from original base scene models • Initially at least one site per upward-facing triangle • Sites can be merged or refined

11. Sky buckets • Snowfall should be fairly equal across sky • Sky divided into grid of equal-area buckets • Flake’s representative area spread across one or more buckets on a ‘miss’

12. Sky buckets

13. Flake dusting • Thin ‘dusting’ of snow difficult to represent as 3D objects • Semi-transparent procedural noise textured polygons used instead • Dusting polygons placed slightly in front of 3D surface

14. Flake dusting

15. Snow stability stage • Redistribute accumulated snow into stable configuration • Use angle of repose • Measure of static friction of a pile of granular material

16. Angle of repose (AOR) • 90º for fresh snow • 15º for slush • Can model probability of stability around AOR

17. Stability test • Compute angle between snow surface on site s and neighbors ni lower than s • If angle too steep to support snow, perform obstacle test between s and ni • Shift snow from s to ni if not blocked • Repeat until no unstable neighbors or s is empty

18. Obstacle test • avalanche blocked by scene object • avalanche blocked by snow on object • avalanche partially blocked by snow on object

19. Stability termination • Simulation runs out of time • All launch sites are stable • Only a small amount of snow moved during last pass • Most unstable snow resolved during first few passes

20. Rain, flour, wind • Rain can be simulated by setting AOR = 0º and not allowing any flake flutter • Feasible for other materials, like flour • Framework in place for basic wind effects

21. Rain

22. Recent work • “Modeling the Accumulation of Wind-Driven Snow” – Bryan E. Feldman and James F. O’Brien

24. References • Fearing, P. 2000. Computer modelling of fallen snow. In Proceedings of ACM SIGGRAPH 2000, 37-46. • Feldman, B. E., O’Brien, J. F. 2002. Modeling the accumulation of wind-driven snow. ACM SIGGRAPH 2002 Technical Sketch.