Browsing by Author "Kim, Tae-Yong"

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    Cloth and Skin Deformation with a Triangle Mesh Based Convolutional Neural Network
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Chentanez, Nuttapong; Macklin, Miles; Müller, Matthias; Jeschke, Stefan; Kim, Tae-Yong; Bender, Jan and Popa, Tiberiu
    We introduce a triangle mesh based convolutional neural network. The proposed network structure can be used for problems where input and/or output are defined on a manifold triangle mesh with or without boundary. We demonstrate its applications in cloth upsampling, adding back details to Principal Component Analysis (PCA) compressed cloth, regressing clothing deformation from character poses, and regressing hand skin deformation from bones' joint angles. The data used for training in this work are generated from high resolution extended position based dynamics (XPBD) physics simulations with small time steps and high iteration counts and from an offline FEM simulator, but it can come from other sources. The inference time of our prototype implementation, depending on the mesh resolution and the network size, can provide between 4 to 134 times faster than a GPU based simulator. The inference also only needs to be done for meshes currently visible by the camera.
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    Detailed Rigid Body Simulation with Extended Position Based Dynamics
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Müller, Matthias; Macklin, Miles; Chentanez, Nuttapong; Jeschke, Stefan; Kim, Tae-Yong; Bender, Jan and Popa, Tiberiu
    We present a rigid body simulation method that can resolve small temporal and spatial details by using a quasi explicit integration scheme that is unconditionally stable. Traditional rigid body simulators linearize constraints because they operate on the velocity level or solve the equations of motion implicitly thereby freezing the constraint directions for multiple iterations. Our method always works with the most recent constraint directions. This allows us to trace high speed motion of objects colliding against curved geometry, to reduce the number of constraints, to increase the robustness of the simulation, and to simplify the formulation of the solver. In this paper we provide all the details to implement a fully fledged rigid body solver that handles contacts, a variety of joint types and the interaction with soft objects.
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    Primal/Dual Descent Methods for Dynamics
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Macklin, Miles; Erleben, Kenny; Müller, Matthias; Chentanez, Nuttapong; Jeschke, Stefan; Kim, Tae-Yong; Bender, Jan and Popa, Tiberiu
    We examine the relationship between primal, or force-based, and dual, or constraint-based formulations of dynamics. Variational frameworks such as Projective Dynamics have proved popular for deformable simulation, however they have not been adopted for contact-rich scenarios such as rigid body simulation. We propose a new preconditioned frictional contact solver that is compatible with existing primal optimization methods, and competitive with complementarity-based approaches. Our relaxed primal model generates improved contact force distributions when compared to dual methods, and has the advantage of being differentiable, making it well-suited for trajectory optimization. We derive both primal and dual methods from a common variational point of view, and present a comprehensive numerical analysis of both methods with respect to conditioning. We demonstrate our method on scenarios including rigid body contact, deformable simulation, and robotic manipulation.