Introduction State of the art Our method Results and Conclusions Master Thesis Real-time Realistic Rain Rendering Carles Creus Advisor: Gustavo Patow Facultat d’Inform` atica de Barcelona July 8, 2010
Introduction State of the art Our method Results and Conclusions Introduction 1 Motivation Rain phenomena State of the art 2 Approaches Summary Our method 3 Proposal Preprocess Real-time Results and Conclusions 4 Tests Conclusions
Introduction State of the art Our method Results and Conclusions Motivation Weather is used to transmit specific moods Filming becomes expensive and laborious Synthetic methods simplify the task Our focus: rain rendering Difficulties Huge variety of phenomena Complex physical evolutions, optical properties Overwhelming amount of small details
Introduction State of the art Our method Results and Conclusions Rain phenomena - Raindrops
Introduction State of the art Our method Results and Conclusions Rain phenomena - Puddles, splashes, coronas and ripples
Introduction State of the art Our method Results and Conclusions Rain phenomena - Other
Introduction State of the art Our method Results and Conclusions State of the art Each method simulates a specific subset of phenomena Simplifications on optical properties and physics Traditionally, framerate chosen over realism
Introduction State of the art Our method Results and Conclusions Garg - 2006 Objectives 1 Complex lighting patterns for close-up shots: Create a photorealistic model to render rain streaks using: → light direction → view direction → raindrop shape Create a database of precomputed rain streak renders 2 Add rain streaks to videos
Introduction State of the art Our method Results and Conclusions Garg - Model Base Oscillation model developed in atmospheric sciences: Assumes that the equilibrium shape is spherical The shape is expressed as a combination of harmonics But it does not specify the parameters for the oscillation → Capture real images and compare with synthetic renders
Introduction State of the art Our method Results and Conclusions Garg - Real captures Setup Drops released from 15m r 0 = 2mm Light 1m away HDR camera 3m away 10 repetitions
Introduction State of the art Our method Results and Conclusions Garg - Comparison
Introduction State of the art Our method Results and Conclusions Rousseau - 2006
Introduction State of the art Our method Results and Conclusions Tariq - 2007
Introduction State of the art Our method Results and Conclusions Tatarchuk - 2006
Introduction State of the art Our method Results and Conclusions Centelles - 2009
Introduction State of the art Our method Results and Conclusions Summary Reflection, Refraction Participating media Ground collision Moving camera Raindrops Real-time Lightning Dripping Splashes Ripples Wind Garg ✗ ✓ ✓ ✓ ✗ ✗ ✗ ✗ ✗ ✗ ✗ Wang ✓ ✓ ✗ ✓ ✗ ✗ ✗ ✗ ✗ ✗ ✗ Rousseau ✓ ✓ ✗ ✓ ✗ ✗ ✓ ✗ ✗ ✗ ✗ Tariq ✓ ✓ ✗ ✓ ✓ ✗ ✗ ✓ ✗ ✗ ✗ Centelles ✓ ✓ ✗ ✓ ✗ ✗ ✗ ✓ ✗ ✗ ✗ Tatarchuk ✓ ✓ ✓ ✗ ✓ ✓ ✓ ✓ ✓ ✓ ✓ Our method ✓ ✓ ✓ ✓ ✗ ✗ ✗ ✗ ✓ ✗ ✗
Introduction State of the art Our method Results and Conclusions Summary Open issues ✗ Comprehensive algorithms have poor user interaction ✗ Restricted artistic direction ✗ Each phenomena decoupled from the rest ✗ Seldom interaction with the scene
Introduction State of the art Our method Results and Conclusions Proposal Objectives Real-time rendering of raindrops Realistic raindrop illumination Interaction with the scene: splashes no indoor rain Arbitrary rain placement and density
Introduction State of the art Our method Results and Conclusions Overview
Introduction State of the art Our method Results and Conclusions Overview
Introduction State of the art Our method Results and Conclusions Preprocess - Atlas
Introduction State of the art Our method Results and Conclusions Preprocess - Atlas 450 images 2880 x 3606 12 mipmap levels
Introduction State of the art Our method Results and Conclusions Preprocess - Atlas 5 images 32 x 3606 12 mipmap levels
Introduction State of the art Our method Results and Conclusions Preprocess - Splash animation 21 frames 48 x 32 6 mipmap levels
Introduction State of the art Our method Results and Conclusions Preprocess - Particle generation Rain space scheme
Introduction State of the art Our method Results and Conclusions Preprocess - Particle generation Rain space scheme - Optimization
Introduction State of the art Our method Results and Conclusions Preprocess - Particle generation Particle packets Worldwide Tree: Quad-tree Kd-tree Grid
Introduction State of the art Our method Results and Conclusions Preprocess - Particle generation Particle packets Worldwide Tree: Quad-tree Kd-tree Grid
Introduction State of the art Our method Results and Conclusions Preprocess - Particle generation Particle packets Worldwide Tree: Quad-tree Kd-tree Grid
Introduction State of the art Our method Results and Conclusions Preprocess - Particle generation Particle packets Worldwide Tree: Quad-tree Kd-tree Grid
Introduction State of the art Our method Results and Conclusions Preprocess - Particle generation Particle packets Worldwide Tree: Quad-tree Kd-tree Grid
Introduction State of the art Our method Results and Conclusions Real-time - CPU - Time animation Fall animated with a global parameter in [0 , 1). Updated with: ∆ time height local / velocity fall
Introduction State of the art Our method Results and Conclusions Real-time - CPU - Local space movement Height correction
Introduction State of the art Our method Results and Conclusions Real-time - CPU - Packet handling
Introduction State of the art Our method Results and Conclusions Real-time - GPU - Vertex shader Placement Particle state
Introduction State of the art Our method Results and Conclusions Real-time - GPU - Geometry shader Billboard expansion Drops: lighting parameters Splash: animation frame
Introduction State of the art Our method Results and Conclusions Real-time - GPU - Fragment shader Texture fetch Shadowing Shading
Introduction State of the art Our method Results and Conclusions Test settings City model (by www.Daz3D.com) 780K polygons 140 textures (color + alpha mask + bump map) Rain 400 x 400 meters, 230 meters high 375M particles 3606 x 2880 and 32 x 2880 mipmapped atlases ( x 10) 21 animation frames of 48 x 32 Computer TM 2 Duo at 3 GHz � Core Intel R � GeForce R � GTX 280 with 1GB of memory NVIDIA R Screen size of 1280 x 720
Introduction State of the art Our method Results and Conclusions Results
Introduction State of the art Our method Results and Conclusions Results
Introduction State of the art Our method Results and Conclusions Results
Introduction State of the art Our method Results and Conclusions Performance Local space analysis
Introduction State of the art Our method Results and Conclusions Performance Radius analysis
Introduction State of the art Our method Results and Conclusions Performance Packet size analysis
Introduction State of the art Our method Results and Conclusions Performance Light amount analysis
Introduction State of the art Our method Results and Conclusions Conclusions ✓ Realistic raindrop highlights ✓ Lighting considering shadows ✓ Easy rain configuration: rain space density map ✓ Scene interaction: no indoor rain splashes ✓ Good performance: Particle packets handled with few and fast operations Per-particle operations only in GPU
Introduction State of the art Our method Results and Conclusions Limitations ✗ Drop blending needs a depth buffer → no semi-transparent geometry → no volumetric data ✗ Tighter bounds on simulation volume hindered by present organization ✗ Huge impact on performance due to light sources ✗ Unrealistic and repetitive splashes
Introduction State of the art Our method Results and Conclusions End Thanks! Questions?
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