Interactive Sampling and Rendering for Complex and Procedural Geometry

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Presentation transcript:

Interactive Sampling and Rendering for Complex and Procedural Geometry Marc Stamminger, George Drettakis REVES/iMAGIS Sophia-Antipolis

motivation tree created by AMAP 150,000 triangles 8 fps (Linux PC with GeForce Quadro)

motivation rendered with points at 60 fps reduced quality 7 times faster

motivation level of detail 100 trees 270,000 points 20 fps

previous work 1985 Levoy/Whitted "The Use of Points as a Display Primitive" 1998 Grossman/Dally "Point Sample Rendering" 2000 Rusinkiewicz/Levoy "The Q-Splat" 2000 Pfister/Zwicker/van Baar/Gross "Surfels"

very recent work Wand/Fischer/Peter/Meyer/auf der Heide/Strasser "The Randomized z-Buffer Algorithm"

point rendering pipeline scene description vrml file mgf file … procedural model point set (3D-coordinates, normal, material) screen point rendering point generation

point generation (orthographic) views filtered triangle mesh hierarchy random points

point rendering in software in hardware filtering texturing hole filling in hardware as points as polygonal disks

our approach fast / on the fly point generation for procedural objects terrains complex dynamic objects point rendering with OpenGL’s GL_POINT very fast (up to 10 million points per second) OpenGL does lighting

results points are well suited for procedural geometry

results points are well suited for procedural geometry terrains

results points are well suited for procedural geometry terrains complex geometry

results points are well suited for procedural geometry terrains complex geometry combinations

complex polygonal geometry generate list of randomly distributed samples for every frame: compute n, render the first n 100,000 10,000 1,000

complex polygonal geometry easy speed / quality trade off frame rate control 100,000 10,000 1,000

modified complex geometry simple modifications on the fly 30 fps

displaced geometry 25,000 points 25,000 points

displaced geometry 25,000 points 100,000 points

adaptive sampling

undersampling factor < 1 > 1

undersampling factor

video sqrt(5) sampling

adaptive point generation

sqrt(5) sampling (2/5,1/5)

sqrt(5) sampling

sqrt(5) sampling

sqrt(5) sampling

sqrt(5) sampling

sqrt(5) sampling

sqrt(5) sampling rotated, nested grids special attention to boundaries grid distance decreases by 1/sqrt(5) rotation angle  27o special attention to boundaries

procedural modifiers

terrains

terrains

terrain parameterization parameterize by (d,u) d u terrain d u screen

terrain parameterization looking straight ahead looking up looking down

terrain algorithm sqrt(5) sampling scheme undersampling factor parameterization distortions perspective distortions displacement

terrain occlusion culling regular sampling occlusion culling, with adaptive sampling

video results

conclusion points are very powerful, when details become smaller than a pixel simple and efficient level of detail simple manipulation easily parallelizable big potential for further improvements

link more at: http://www-sop.inria.fr/reves

with a Marie-Curie fellowship acknowledgements thanks to the European Union for funding me with a Marie-Curie fellowship