In this paper, we present a simple method for animating natural phenomena such as erosion, sedime... more In this paper, we present a simple method for animating natural phenomena such as erosion, sedimentation, and acidic corrosion. We discretize the appropriate physical or chemical equations using finite differences, and we use the results to modify the shape of a solid body. We remove mass from an object by treating its surface as a level set and advecting it
Eurographics Symposium on Rendering/Eurographics Workshop on Rendering Techniques, 2007
We present a technique for synthesizing spatially and temporally varying textures on continuous f... more We present a technique for synthesizing spatially and temporally varying textures on continuous flows using image or video input, guided by the physical characteristics of the fluid stream itself. This approach enables the generation of realistic textures on the fluid that correspond to the local flow behavior, creating the appearance of complex surface effects, such as foam and small bubbles. Our technique requires only a simple specification of texture behavior, and automatically generates and tracks the features and texture over time in a temporally coherent manner. Based on this framework, we also introduce a technique to perform feature-guided video synthesis. We demonstrate our algorithm on several simulated and recorded natural phenomena, including splashing water and lava flows. We also show how our methodology can be extended beyond realistic appearance synthesis to more general scenarios, such as temperature-guided synthesis of complex surface phenomena in a liquid during boiling.
We present a technique for coupling simulated fluid phenomena that interact with real dynamic sce... more We present a technique for coupling simulated fluid phenomena that interact with real dynamic scenes captured as a binocular video sequence. We first process the binocular video sequence to obtain a complete 3D reconstruction of the scene, including velocity information. We use stereo for the visible parts of 3D geometry and surface completion to fill the missing regions. We then perform fluid simulation within a 3D domain that contains the object, enabling one-way coupling from the video to the fluid. In order to maintain temporal consistency of the reconstructed scene and the animated fluid across frames, we develop a geometry tracking algorithm that combines optic flow and depth information with a novel technique for "velocity completion". The velocity completion technique uses local rigidity constraints to hypothesize a motion field for the entire 3D shape, which is then used to propagate and filter the reconstructed shape over time. This approach not only generates smoothly varying geometry across time, but also simultaneously provides the necessary boundary conditions for one-way coupling between the dynamic geometry and the simulated fluid. Finally, we employ a GPU based scheme for rendering the synthetic fluid in the real video, taking refraction and scene texture into account.
The matrix used to help solve the Heat eqauaion with the LOD method, p. 46. I The moment of inert... more The matrix used to help solve the Heat eqauaion with the LOD method, p. 46. I The moment of inertia of a rigid body in world coordinates, p. 62. I The number of gird cells in the x-dimension of the computational domain, p. 19. J The number of gird cells in the y-dimension of the computational domain, p. 19. K The number of gird cells in the z-dimension of the computational domain, p. 19. k The thermal diffusion constant that controls how fast heat moves through a material, p. 46. M The mass of a rigid body is its density times its volume, p. 62. M The number of cells in the area of interest around the φ = 0, also called the active-set or narrow band, p. 86. xi n The outward normal on a surface, p. 60. n φ The outward normal of the level set, p. 83. p The pressure is a force per unit area, p. 16. R The solid domain, p. ix. r A vector pointing from the center of mass to a point on the rigid body, p. 58. R The force inside a rigid body that keeps it deformation free, p. 63. S A source term including relative density and collision terms, p. 62. S A signature function of φ used in reinitialization, like the sign fuction but with 0 = 0, p. 85. t The scalar temperature field, p. 46. t The traction force, p. 60. u The velocity in meters per second. The discrete version is a vector field, p. 16. u The x-component of the velocity, u, p. 18. u A vector that contains the x-component of the velocities for each cell face in the MAC grid that has fluid on both sides, p. 43. u temp The intermediate velocity used with operator splitting, p. 42. u A divergence free and energy conserving velocity that is not yet constrained to rigid body motion, p. vi. u R The energy conserving, deformation free rigid body velocity, p. 63. u n The velocity at the beginning of a time step, p. vi. u n+1 The final velocity at the end of a time step, p. vi. u * The divergence free velocity, without accounting for rigid body energy and motion, p. vi. u t The time derivative of velocity, p. 16. u The best guess velocity, before enforcing incompressibility, p. 27. u The x-component of the best guess velocity,ũ, p. 28. v The y-component of the velocity, u, p. 18. v The translational velocity of a rigid body at the center of mass, p. 58. v The rigid body velocity obtained by integrating over the rigid body's domain, p. 64. v The y-component of the best guess velocity,ũ, p. 28.
Recent efforts to visually capture the phenomena of boiling have proposed monolithic approaches t... more Recent efforts to visually capture the phenomena of boiling have proposed monolithic approaches that extend the basic techniques underlying existing fluid solvers. In this work, we show that if we instead treat boiling as a sep- arate computational module to be loosely coupled to an existing solver, a very easy to implement, highly efficient algorithm can be designed that produces
We present a novel technique for the animation of turbulent fluids by coupling a procedural turbu... more We present a novel technique for the animation of turbulent fluids by coupling a procedural turbulence model with a numerical fluid solver to introduce subgrid-scale flow detail. From the large-scale flow simulated by the solver, we model the production and behavior of turbulent energy using a physically motivated energy model. This energy distribution is used to synthesize an incompressible turbulent velocity field, whose features show plausible temporal behavior through a novel Lagrangian approach for advected noise. The synthesized turbulent flow has a dynamical effect on the large-scale flow, and produces visually plausible detailed features on both gaseous and free-surface liquid flows. Our method is an order of magnitude faster than full numerical simulation of equivalent resolution, and requires no manual direction.
Physically based deformable models have been widely embraced by the Computer Graphics community. ... more Physically based deformable models have been widely embraced by the Computer Graphics community. Many problems outlined in a previous survey by Gibson and Mirtich [GM97] have been addressed, thereby making these models interesting and useful for both offline and real-time applications, such as motion pictures and video games. In this paper, we present the most significant contributions of the past decade, which produce such impressive and perceivably realistic animations and simulations: finite element/difference/volume methods, mass-spring systems, meshfree methods, coupled particle systems and reduced deformable models based on modal analysis. For completeness, we also make a connection to the simulation of other continua, such as fluids, gases and melting objects. Since time integration is inherent to all simulated phenomena, the general notion of time discretization is treated separately, while specifics are left to the respective models. Finally, we discuss areas of application, such as elastoplastic deformation and fracture, cloth and hair animation, virtual surgery simulation, interactive entertainment and fluid/smoke animation, and also suggest areas for future research.
In this paper, we present a simple method for animating natural phenomena such as erosion, sedime... more In this paper, we present a simple method for animating natural phenomena such as erosion, sedimentation, and acidic corrosion. We discretize the appropriate physical or chemical equations using finite differences, and we use the results to modify the shape of a solid body. We remove mass from an object by treating its surface as a level set and advecting it
Eurographics Symposium on Rendering/Eurographics Workshop on Rendering Techniques, 2007
We present a technique for synthesizing spatially and temporally varying textures on continuous f... more We present a technique for synthesizing spatially and temporally varying textures on continuous flows using image or video input, guided by the physical characteristics of the fluid stream itself. This approach enables the generation of realistic textures on the fluid that correspond to the local flow behavior, creating the appearance of complex surface effects, such as foam and small bubbles. Our technique requires only a simple specification of texture behavior, and automatically generates and tracks the features and texture over time in a temporally coherent manner. Based on this framework, we also introduce a technique to perform feature-guided video synthesis. We demonstrate our algorithm on several simulated and recorded natural phenomena, including splashing water and lava flows. We also show how our methodology can be extended beyond realistic appearance synthesis to more general scenarios, such as temperature-guided synthesis of complex surface phenomena in a liquid during boiling.
We present a technique for coupling simulated fluid phenomena that interact with real dynamic sce... more We present a technique for coupling simulated fluid phenomena that interact with real dynamic scenes captured as a binocular video sequence. We first process the binocular video sequence to obtain a complete 3D reconstruction of the scene, including velocity information. We use stereo for the visible parts of 3D geometry and surface completion to fill the missing regions. We then perform fluid simulation within a 3D domain that contains the object, enabling one-way coupling from the video to the fluid. In order to maintain temporal consistency of the reconstructed scene and the animated fluid across frames, we develop a geometry tracking algorithm that combines optic flow and depth information with a novel technique for "velocity completion". The velocity completion technique uses local rigidity constraints to hypothesize a motion field for the entire 3D shape, which is then used to propagate and filter the reconstructed shape over time. This approach not only generates smoothly varying geometry across time, but also simultaneously provides the necessary boundary conditions for one-way coupling between the dynamic geometry and the simulated fluid. Finally, we employ a GPU based scheme for rendering the synthetic fluid in the real video, taking refraction and scene texture into account.
The matrix used to help solve the Heat eqauaion with the LOD method, p. 46. I The moment of inert... more The matrix used to help solve the Heat eqauaion with the LOD method, p. 46. I The moment of inertia of a rigid body in world coordinates, p. 62. I The number of gird cells in the x-dimension of the computational domain, p. 19. J The number of gird cells in the y-dimension of the computational domain, p. 19. K The number of gird cells in the z-dimension of the computational domain, p. 19. k The thermal diffusion constant that controls how fast heat moves through a material, p. 46. M The mass of a rigid body is its density times its volume, p. 62. M The number of cells in the area of interest around the φ = 0, also called the active-set or narrow band, p. 86. xi n The outward normal on a surface, p. 60. n φ The outward normal of the level set, p. 83. p The pressure is a force per unit area, p. 16. R The solid domain, p. ix. r A vector pointing from the center of mass to a point on the rigid body, p. 58. R The force inside a rigid body that keeps it deformation free, p. 63. S A source term including relative density and collision terms, p. 62. S A signature function of φ used in reinitialization, like the sign fuction but with 0 = 0, p. 85. t The scalar temperature field, p. 46. t The traction force, p. 60. u The velocity in meters per second. The discrete version is a vector field, p. 16. u The x-component of the velocity, u, p. 18. u A vector that contains the x-component of the velocities for each cell face in the MAC grid that has fluid on both sides, p. 43. u temp The intermediate velocity used with operator splitting, p. 42. u A divergence free and energy conserving velocity that is not yet constrained to rigid body motion, p. vi. u R The energy conserving, deformation free rigid body velocity, p. 63. u n The velocity at the beginning of a time step, p. vi. u n+1 The final velocity at the end of a time step, p. vi. u * The divergence free velocity, without accounting for rigid body energy and motion, p. vi. u t The time derivative of velocity, p. 16. u The best guess velocity, before enforcing incompressibility, p. 27. u The x-component of the best guess velocity,ũ, p. 28. v The y-component of the velocity, u, p. 18. v The translational velocity of a rigid body at the center of mass, p. 58. v The rigid body velocity obtained by integrating over the rigid body's domain, p. 64. v The y-component of the best guess velocity,ũ, p. 28.
Recent efforts to visually capture the phenomena of boiling have proposed monolithic approaches t... more Recent efforts to visually capture the phenomena of boiling have proposed monolithic approaches that extend the basic techniques underlying existing fluid solvers. In this work, we show that if we instead treat boiling as a sep- arate computational module to be loosely coupled to an existing solver, a very easy to implement, highly efficient algorithm can be designed that produces
We present a novel technique for the animation of turbulent fluids by coupling a procedural turbu... more We present a novel technique for the animation of turbulent fluids by coupling a procedural turbulence model with a numerical fluid solver to introduce subgrid-scale flow detail. From the large-scale flow simulated by the solver, we model the production and behavior of turbulent energy using a physically motivated energy model. This energy distribution is used to synthesize an incompressible turbulent velocity field, whose features show plausible temporal behavior through a novel Lagrangian approach for advected noise. The synthesized turbulent flow has a dynamical effect on the large-scale flow, and produces visually plausible detailed features on both gaseous and free-surface liquid flows. Our method is an order of magnitude faster than full numerical simulation of equivalent resolution, and requires no manual direction.
Physically based deformable models have been widely embraced by the Computer Graphics community. ... more Physically based deformable models have been widely embraced by the Computer Graphics community. Many problems outlined in a previous survey by Gibson and Mirtich [GM97] have been addressed, thereby making these models interesting and useful for both offline and real-time applications, such as motion pictures and video games. In this paper, we present the most significant contributions of the past decade, which produce such impressive and perceivably realistic animations and simulations: finite element/difference/volume methods, mass-spring systems, meshfree methods, coupled particle systems and reduced deformable models based on modal analysis. For completeness, we also make a connection to the simulation of other continua, such as fluids, gases and melting objects. Since time integration is inherent to all simulated phenomena, the general notion of time discretization is treated separately, while specifics are left to the respective models. Finally, we discuss areas of application, such as elastoplastic deformation and fracture, cloth and hair animation, virtual surgery simulation, interactive entertainment and fluid/smoke animation, and also suggest areas for future research.
Uploads
Papers by Mark Carlson