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EVASION Environnements Virtuels pour l’Animation et la Synthèse d’Images d’Objets Naturels Virtual Environments for Modeling, Animating and Rendering Natural Scenes. INRIA Rhône-Alpes Équipe du laboratoire GRAVIR/IMAG Future équipe du LJK (CNRS, INPG, INRIA, UJF). Who are we?. - PowerPoint PPT Presentation
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EVASION
Environnements Virtuels pour l’Animation et la
Synthèse d’Images d’Objets Naturels
Virtual Environments for
Modeling, Animating and Rendering Natural Scenes
INRIA Rhône-Alpes Équipe du laboratoire GRAVIR/IMAG
Future équipe du LJK (CNRS, INPG, INRIA, UJF)
Who are we?
The team
– 6 faculties • 2 full profs : GP Bonneau (UJF), MP Cani (INPG): Scientific leader • 2 assistant profs : F Faure (UJF), F. Hetroy (INPG, sept 2004)• 2 CR1 researchers : F. Neyret (CNRS), L. Revéret (INRIA)
– 4 post-doc, engineer or designer
– 12 PhD students (8 with MENRT grants)
History
– Created in January 2003, after the scission of iMAGIS
– Basis: Computer Graphics (modeling, animation, rendering)
Scientific focus Modeling & Visualizing Nature
• Fascinating problem (vegetable, mineral, animal worlds)
• Still unsolved to a large extent
• Many industrial applications (from realism to real-time)– 3D feature films, Special effects, Video games– Virtual prototyping & Pedagogical Simulators (environment, geology, energy, aeronautics, surgery, cosmetics)
Modeling & Visualizing Nature Main challenges
• Extreme complexity – Number of elements, shape, aspect, motion and deformation
• Re-using models from other sciences is not always possible – Virtual clouds? Fluid dynamics & meteorology study other scales– Hair animation? FEM + collisions not applicable for 100 000 strands
Use existing knowledge: Collaborate with other disciplines Combine efficiency and realism?
Specific methodology + New fundamental tools
Scientific basisMethodology for handling complexity
1. Characterize the observed sub-phenomena
2. Represent them by coupled sub-models– Of different nature : physical model, geometry, texture, ...
– Applied at different scales
3. Dynamically adapt the sub-models to the needs– By changing their local space and time resolution
– By switching from one model to another
4. Validate based on human perception
Methodology for handling complexityExample: meadow blowing in the wind
1. Wind : pattern + action
2. Receever : precomputed dynamics
3. Grass geometry : 3 levels of detail
… [I3D’01,Computer Animation’03]
Contributions1. New fundamental tools
• Geometry– New shape representations
– Interactive deformations
• Animation– Motion control from video analysis
– Physically-based simulation
• Visualization of massive data-sets– Multiresolution analysis & adaptive rendering
• Realistic rendering– Textures, shaders, point-based rendering
New fundamental toolsExample: Constant volume space deformations
• Foldover-free space deformation• Rings of constant volume « swirls »
Applications• Modeling virtual clay• Animating fluids
[Pacific Graphics’04, SCA’05]
Contributions2. Application to specific natural scenes
• Mineral world– Animation of lava-flows, sea, streams
– Simulation of water, smoke, clouds
• Vegetable world– Real-time rendering of forest
– Animating meadows (grass, trees)
• Animal world– Wild animals animated from video
– Virtual humans: hair, skin, muscles, clothes
– Real-time organs for surgery simulators
Application to specific natural scenesExample: Simulation of Natural Hair
• New Lagrangian deformable model: Super-helices– Predicts the shape of static hair – Efficient and stable simulation of hair dynamics
• Identification of hair interaction parameters• Bridging the gap between wisps & continuum
Interdisciplinary work (cosmetics, mechanics)Industrial partnership (L’Oréal) [EG’05 short, SIGGRAPH’06]
Application to specific natural scenesExample: Simulation of Natural Hair
3. Software development SOFA with CIMIT/Harvard, INRIA, ETHZ, CWU
An Open Framework for Medical Simulation• Multi-institution, international effort • Aim: component sharing / exchange / comparison
Kernel (release Dec 06)
– Communication & interfaces
Modules – FEM, Mass & springs, Particles– Rendering algorithms, – Collision detection & response
Scientific Collaborations
International– Joint team with DGP, University of Toronto (2004-2006) – 6 Eurodoc grants: 6 month visit of PhD students to
U. of Washington, Davis, Berkeley, Calgary, Montreal – European Network of Excellence: Aim@shape(other joint papers with UBC, ETHZ, U. of Tuebingen, UC Davis)
National – Co-advised PhDs: SIAMES, MOVI, APACHE, LMC, TIMC– DEREVE 2 with LIRIS & ICA, MIDAS with TIMC, ICP– ARCs with ALCOVE, EPIDAURE, ISA, Geometrica
with Other Disciplines
2003-2005: Collaborations with the fields of– Mechanics (CEMAGREF, LEGI, L3S)– Medicine (IRCAD, TIMC)– Cognitive Sciences (U. of Geneva)– Cosmetics (l’Oreal research labs)
2005-2009: Interdisciplinary research clusters – “Environnement” & “Santé” (Rhône-Alpes Region)
2006-2009: Multidiciplinary ANR Projects– Biomechanics & Neurosciences (project Kameleon) – Botanics (project NatSim) NatSim
Kamelelon
Industrial grants & transfer
Public projects with technology transfer– European project Odysseous
– RIAM Virtual Actors & RNTL PARI with Galilea
– RIAM projects Vertigo & Prodige with Bionatics and Thales
Direct grants from the industry– L’Oreal (contract 2004-2006)
– CEA / CESTA (PhD grant 2004-2006)
– EDF (PhD grant 2005-2007)
Results & Visibility
• Publications (20 journal, 48 conf, 6 chapters…)
• Editors: GMOD, IEEE TVCG• Conference co-chairs
– EG-IEEE Visualisation’2003, IEEE Shape Modeling & Applications’05
• Paper co-chairs – EUROGRAPHICS’04, ACM-EG Symp. on Computer Animation’06
• PC members– SIGGRAPH, Eurographics, Pacific Graphics
– IEEE Vis, SMI, SCA, CASA, NPAR, etc
Grand challenge ?Specify and control a full, animated natural scene
Creation of digital content, in a difficult case– High number of similar, but different details– Allow user-input / fit specific distributions– Control motion while maintaining realism– Animate and render efficiently
Reasons for tackling it?– Real-size tests & interactions between different phenomena– Interactive exploration (GPU, GRimage PC grid)– Validation through the science of human perception
Objectives for the next 4 years
1. Creation of Natural Scenes• Exploit real images, data, sketching• Combine user control with procedural details
2. Animating Nature: multi-disciplinary projects• Promote interactive virtual scenes as a support for
experimenting and validating hypotheses• Model natural phenomena never achieved in CG
3. Efficient Visualization of very large scenes• Interactive exploration of hybrid data-masses• Fast, realistic rendering of natural scenes
Conclusion
• Computer Graphics group – Competences: modeling, animation, visualization, rendering
– Focus: Virtual natural scenes and phenomena
• Strategic aspects within French research – Combining simulation, visualization and virtual reality
– Processing huge data-sets
– Applications to Environmental simulations
– Applications to Biology/Health-careEVASION
EVASION
Thank you!