EVASION Environnements Virtuels pour l’Animation et la Synthèse d’Images d’Objets Naturels...
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Transcript of EVASION Environnements Virtuels pour l’Animation et la Synthèse d’Images d’Objets Naturels...
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!