Subspace Deformation Research Articles

Parametric Skeletons with Reduced Soft‐Tissue Deformations

AbstractWe present a method to augment parametric skeletal models with subspace soft‐tissue deformations. We combine the benefits of data‐driven skeletal models, i.e. accurate replication of contact‐free static deformations, with the benefits of pure physics‐based models, i.e. skin and skeletal reaction to contact and inertial motion with two‐way coupling. We succeed to do so in a highly efficient manner, thanks to a careful choice of reduced model for the subspace deformation. With our method, it is easy to design expressive reduced models with efficient yet accurate force computations, without the need for training deformation examples. We demonstrate the application of our method to parametric models of human bodies, SMPL, and hands, MANO, with interactive simulations of contact with nonlinear soft‐tissue deformation and skeletal response.>

Positioning human body models for crashworthiness using model order reduction

A new technique to accelerate the positioning of human body models (HBMs) by means of a dimensionality reduction of a database of precomputed simulations is presented. First, a set of important subspace deformation modes which are used to approximate the model’s movements observed in the training simulations are computed. In the second step, a convex optimization problem is solved in order to obtain an optimal position of the human body model as described by the user. We apply the proposed method to a new reclined seating position of the Total Human Model for Safety (THUMS, v5).

A mobile device tool to assist the ECG interpretation based on a realistic 3D virtual heart simulation

Computational tools can be developed to help the interpretation of the ECG and the beating heart. In some cases, such tools are implemented in mobile devices and applied to “mobile learning” (m-learning) activities. In the present work, we show a mobile device tool that emulates the beating heart according to ECG data. The tool has been implemented using skeletal subspace deformation to control the movement of a 3D heart model in real time. It is possible to manipulate the heart model and visualize its inner anatomy. The results of the simulation show that the tool allows online adjustments on the virtual heart according to actual ECG data set by the user or by ECG data files (normal rhythm or arrhythmias). The comparison between clinical data and the results of the simulation validated the cardiac beating simulation. The user experience was evaluated by students of biomedical engineering using a Likert scale. The students evaluated their experience with the tool positively. The results, as a whole, show that the tool may represent a newly accessible resource to help support m-learning in the context of interpreting ECG data. Also, the tool seems to be applicable in a teaching/learning environment where undergraduates are studying either the ECG or the cardiac anatomy or function.

Anatomographic Volumetric Skin-Musculoskeletal Model and Its Kinematic Deformation With Surface-Based SSD

Conventional musculoskeletal models mainly consist of bones modeled by rigid linkages, and muscles, tendons, and ligaments modeled by ideal wires. The lack of volumetric modeling of muscle makes a representation of interaction between muscles and natural muscle pathway difficult. This difficulty results in a physiologically inappropriate estimation of a muscle momentum arm that is critical for a muscle activity estimation. In this letter, we develop a volumetric skin-musculoskeletal model based on an anatomographic human shape database to improve an estimation of a muscle momentum arm. A volumetric deformation of surface skin and muscle is realized by an extended skeleton subspace deformation (SSD, the linear blend skinning algorithm) that considers a surface profile of bone with low computational cost. This extended SSD considers a sub-bone that is projected to the bone surface polygon so that the skin and muscle deformation is significantly affected by the bone surface profile. The surface-based SSD realized the natural skin deformation avoiding a penetration between skin and bones during trunk rotation that results in a physiologically appropriate estimation of a muscle momentum arm. The volumetric skin-musculoskeletal model and the surface-based SSD estimates the momentum arm of vastus lateralis with 14.1% maximum error from a literature values, though there is 44.8% maximum error with the wire musculoskeletal model. This model would accurize a muscle activity estimation that leads to a more correct understanding of human motion control/generation mechanisms.

A unified approach for subspace simulation of deformable bodies in multiple domains

Multi-domain subspace simulation can efficiently and conveniently simulate the deformation of a large deformable body, by constraining the deformation of each domain into a different subspace. The key challenge in implementing this method is how to handle the coupling among multiple deformable domains, so that the overall effect is free of gap or locking issues. In this paper, we present a new domain decomposition framework that connects two disjoint domains through coupling elements. Under this framework, we present a unified simulation system that solves subspace deformations and rigid motions of all of the domains by a single linear solve. Since the coupling elements are part of the deformable body, their elastic properties are the same as the rest of the body and our system does not need stiffness parameter tuning. To quickly evaluate the reduced elastic forces and their Jacobian matrices caused by the coupling elements, we further develop two cubature optimization schemes using uniform and non-uniform cubature weights. Our experiment shows that the whole system can efficiently handle large and complex scenes, many of which cannot be easily simulated by previous techniques without limitations.

Boundary-Aware Multidomain Subspace Deformation

In this paper, we propose a novel framework for multidomain subspace deformation using node-wise corotational elasticity. With the proper construction of subspaces based on the knowledge of the boundary deformation, we can use the Lagrange multiplier technique to impose coupling constraints at the boundary without overconstraining. In our deformation algorithm, the number of constraint equations to couple two neighboring domains is not related to the number of the nodes on the boundary but is the same as the number of the selected boundary deformation modes. The crack artifact is not present in our simulation result, and the domain decomposition with loops can be easily handled. Experimental results show that the single-core implementation of our algorithm can achieve real-time performance in simulating deformable objects with around quarter million tetrahedral elements.

Example‐based inverse kinematics using cage

ABSTRACTThis paper presents a cage‐based inverse kinematics (CageIK) that enables interactive posing of character models in a wide range of mesh representations using handle points. By providing a set of cage geometries as examples, CageIK optimizes deformations of the cage according to handle movements and reconstructs the model using a subspace deformation method based on Green Coordinates. CageIK therefore not only poses the model naturally but also preserves details even when leaving the example space. Furthermore, by blending deformations based on bounded biharmonic weights, CageIK can edit the pose of the model locally. Because example cages can be generated from existing models, we can reuse animation assets that were already created by artists or simulations, which avoids repeating the time‐consuming process of creating examples. We show that CageIK can edit a wide variety of models, including multicomponent meshes, polygon soups, and quadrilateral meshes. Copyright © 2012 John Wiley & Sons, Ltd.

Sparse meshless models of complex deformable solids

A new method to simulate deformable objects with heterogeneous material properties and complex geometries is presented. Given a volumetric map of the material properties and an arbitrary number of control nodes, a distribution of the nodes is computed automatically, as well as the associated shape functions. Reference frames attached to the nodes are used to apply skeleton subspace deformation across the volume of the objects. A continuum mechanics formulation is derived from the displacements and the material properties. We introduce novel material-aware shape functions in place of the traditional radial basis functions used in meshless frameworks. In contrast with previous approaches, these allow coarse deformation functions to efficiently resolve non-uniform stiffnesses. Complex models can thus be simulated at high frame rates using a small number of control nodes.

Subspace self-collision culling

We show how to greatly accelerate self-collision detection (SCD) for reduced deformable models. Given a triangle mesh and a set of deformation modes, our method precomputes Subspace Self-Collision Culling (SSCC) certificates which, if satisfied, prove the absence of self-collisions for large parts of the model. At runtime, bounding volume hierarchies augmented with our certificates can aggressively cull overlap tests and reduce hierarchy updates. Our method supports both discrete and continuous SCD, can handle complex geometry, and makes no assumptions about geometric smoothness or normal bounds. It is particularly effective for simulations with modest subspace deformations, where it can often verify the absence of self-collisions in constant time. Our certificates enable low amortized costs, in time and across many objects in multi-body dynamics simulations. Finally, SSCC is effective enough to support self-collision tests at audio rates, which we demonstrate by producing the first sound simulations of clattering objects.

Efficient reconstruction of nonrigid shape and motion from real-time 3D scanner data

We present a new technique for reconstructing a single shape and its nonrigid motion from 3D scanning data. Our algorithm takes a set of time-varying unstructured sample points that capture partial views of a deforming object as input and reconstructs a single shape and a deformation field that fit the data. This representation yields dense correspondences for the whole sequence, as well as a completed 3D shape in every frame. In addition, the algorithm automatically removes spatial and temporal noise artifacts and outliers from the raw input data. Unlike previous methods, the algorithm does not require any shape template but computes a fitting shape automatically from the input data. Our reconstruction framework is based upon a novel topology-aware adaptive subspace deformation technique that allows handling long sequences with complex geometry efficiently. The algorithm accesses data in multiple sequential passes, so that long sequences can be streamed from hard disk, not being limited by main memory. We apply the technique to several benchmark datasets, significantly increasing the complexity of the data that can be handled efficiently in comparison to previous work.

Optimizing cubature for efficient integration of subspace deformations

We propose an efficient scheme for evaluating nonlinear subspace forces (and Jacobians) associated with subspace deformations. The core problem we address is efficient integration of the subspace force density over the 3D spatial domain. Similar to Gaussian quadrature schemes that efficiently integrate functions that lie in particular polynomial subspaces, we propose cubature schemes (multi-dimensional quadrature) optimized for efficient integration of force densities associated with particular subspace deformations, particular materials, and particular geometric domains. We support generic subspace deformation kinematics, and nonlinear hyperelastic materials. For an r-dimensional deformation subspace with O(r) cubature points, our method is able to evaluate subspace forces at O(r(2)) cost. We also describe composite cubature rules for runtime error estimation. Results are provided for various subspace deformation models, several hyperelastic materials (St.Venant-Kirchhoff, Mooney-Rivlin, Arruda-Boyce), and multimodal (graphics, haptics, sound) applications. We show dramatically better efficiency than traditional Monte Carlo integration. CR CATEGORIES: I.6.8 [Simulation and Modeling]: Types of Simulation-Animation, I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling-Physically based modeling G.1.4 [Mathematics of Computing]: Numerical Analysis-Quadrature and Numerical Differentiation.

Gradient domain editing of deforming mesh sequences

Many graphics applications, including computer games and 3D animated films, make heavy use of deforming mesh sequences. In this paper, we generalize gradient domain editing to deforming mesh sequences. Our framework is keyframe based. Given sparse and irregularly distributed constraints at unevenly spaced keyframes, our solution first adjusts the meshes at the keyframes to satisfy these constraints, and then smoothly propagate the constraints and deformations at keyframes to the whole sequence to generate new deforming mesh sequence. To achieve convenient keyframe editing, we have developed an efficient alternating least-squares method. It harnesses the power of subspace deformation and two-pass linear methods to achieve high-quality deformations. We have also developed an effective algorithm to define boundary conditions for all frames using handle trajectory editing. Our deforming mesh editing framework has been successfully applied to a number of editing scenarios with increasing complexity, including footprint editing, path editing, temporal filtering, handle-based deformation mixing, and spacetime morphing.

Gradient domain editing of deforming mesh sequences

Many graphics applications, including computer games and 3D animated films, make heavy use of deforming mesh sequences. In this paper, we generalize gradient domain editing to deforming mesh sequences. Our framework is keyframe based. Given sparse and irregularly distributed constraints at unevenly spaced keyframes, our solution first adjusts the meshes at the keyframes to satisfy these constraints, and then smoothly propagate the constraints and deformations at keyframes to the whole sequence to generate new deforming mesh sequence. To achieve convenient keyframe editing, we have developed an efficient alternating least-squares method. It harnesses the power of subspace deformation and two-pass linear methods to achieve high-quality deformations. We have also developed an effective algorithm to define boundary conditions for all frames using handle trajectory editing. Our deforming mesh editing framework has been successfully applied to a number of editing scenarios with increasing complexity, including footprint editing, path editing, temporal filtering, handle-based deformation mixing, and spacetime morphing.

Animation space

Skeletal subspace deformation (SSD), a simple method of character animation used in many applications, has several shortcomings; the best-known being that joints tend to collapse when bent. We present animation space , a generalization of SSD that greatly reduces these effects and effectively eliminates them for joints that do not have an unusually large range of motion.While other, more expensive generalizations exist, ours is unique in expressing the animation process as a simple linear transformation of the input coordinates. We show that linearity can be used to derive a measure of average distance (across the space of poses), and apply this to improving parametrizations.Linearity also makes it possible to fit a model to a set of examples using least-squares methods. The extra generality in animation space allows for a good fit to realistic data, and overfitting can be controlled to allow fitted models to generalize to new poses. Despite the extra vertex attributes, it is possible to render these animation-space models in hardware with no loss of performance relative to SSD.

Real‐Time Weighted Pose‐Space Deformation on the GPU

Abstract WPSD (Weighted Pose Space Deformation) is an example based skinning method for articulated body animation. The per‐vertex computation required in WPSD can be parallelized in a SIMD (Single Instruction Multiple Data) manner and implemented on a GPU. While such vertex‐parallel computation is often done on the GPU vertex processors, further parallelism can potentially be obtained by using the fragment processors. In this paper, we develop a parallel deformation method using the GPU fragment processors. Joint weights for each vertex are automatically calculated from sample poses, thereby reducing manual effort and enhancing the quality of WPSD as well as SSD (Skeletal Subspace Deformation). We show sufficient speed‐up of SSD, PSD (Pose Space Deformation) and WPSD to make them suitable for real‐time applications.Categories and Subject Descriptors (according to ACM CCS): I.3.1 [Computer Graphics]: Hardware Architecture‐Parallel processing, I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling‐Curve, surface, solid and object modeling, I.3.7 [Computer Graphics]: Three‐Dimensional Graphics and Realism‐Animation.

Subspace gradient domain mesh deformation

In this paper we present a general framework for performing constrained mesh deformation tasks with gradient domain techniques. We present a gradient domain technique that works well with a wide variety of linear and nonlinear constraints. The constraints we introduce include the nonlinear volume constraint for volume preservation, the nonlinear skeleton constraint for maintaining the rigidity of limb segments of articulated figures, and the projection constraint for easy manipulation of the mesh without having to frequently switch between multiple viewpoints. To handle nonlinear constraints, we cast mesh deformation as a nonlinear energy minimization problem and solve the problem using an iterative algorithm. The main challenges in solving this nonlinear problem are the slow convergence and numerical instability of the iterative solver. To address these issues, we develop a subspace technique that builds a coarse control mesh around the original mesh and projects the deformation energy and constraints onto the control mesh vertices using the mean value interpolation. The energy minimization is then carried out in the subspace formed by the control mesh vertices. Running in this subspace, our energy minimization solver is both fast and stable and it provides interactive responses. We demonstrate our deformation constraints and subspace deformation technique with a variety of constrained deformation examples.