Shape Deformation Technique Research Articles

Multi-Resolution Real-Time Deep Pose-Space Deformation

We present a hard-real-time multi-resolution mesh shape deformation technique for skeleton-driven soft-body characters. Producing mesh deformations at multiple levels of detail is very important in many applications in computer graphics. Our work targets applications where the multi-resolution shapes must be generated at fast speeds ("hard-real-time", e.g., a few milliseconds at most and preferably under 1 millisecond), as commonly needed in computer games, virtual reality and Metaverse applications. We assume that the character mesh is driven by a skeleton, and that high-quality character shapes are available in a set of training poses originating from a high-quality (slow) rig such as volumetric FEM simulation. Our method combines multi-resolution analysis, mesh partition of unity, and neural networks, to learn the pre-skinning shape deformations in an arbitrary character pose. Combined with linear blend skinning, this makes it possible to reconstruct the training shapes, as well as interpolate and extrapolate them. Crucially, we simultaneously achieve this at hard real-time rates and at multiple mesh resolution levels. Our technique makes it possible to trade deformation quality for memory and computation speed, to accommodate the strict requirements of modern real-time systems. Furthermore, we propose memory layout and code improvements to boost computation speeds. Previous methods for realtime approximations of quality shape deformations did not focus on hard real-time, or did not investigate the multi-resolution aspect of the problem. Compared to a "naive" approach of separately processing each hierarchical level of detail, our method offers a substantial memory reduction as well as computational speedups. It also makes it possible to construct the shape progressively level by level and interrupt the computation at any time, enabling graceful degradation of the deformation detail. We demonstrate our technique on several examples, including a stylized human character, human hands, and an inverse-kinematics-driven quadruped animal.

The Design of Cavity Resonators and Microwave Filters Applying Shape Deformation Techniques

This article introduces shape deformation as a new approach to the computer-aided design (CAD) of high-frequency components. We show that geometry deformation opens up new design possibilities and offers additional degrees of freedom in the 3-D modeling of microwave structures. Such design flexibility is highly desirable if the full potential of additive manufacturing (AM) is to be exploited in the fabrication of RF and microwave devices. The use of deformation techniques in the design of high-frequency components allows the attainment of improved electrical parameters, such as high-quality factors for cavity resonators and wide higher-order mode separation. In this work, shape deformation with radial basis functions (RBFs) is integrated with an electromagnetic field simulator based on the 3-D finite-element method (FEM), allowing the semiautomated optimization of microwave components, such as cavity resonators and filters. The proposed strategy is used for the design of high <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Q$</tex-math> </inline-formula> -factor cavity resonators, cavity bandpass filters with improved spurious mode separation, and a compact twisted waveguide filter. Three designs of waveguide cavity filters with complex geometry are experimentally verified using 3-D-printed prototypes fabricated with selective laser melting (SLM) technology.

Aerodynamic Optimization of Transonic Rotor Using Radial Basis Function Based Deformation and Data-Driven Differential Evolution Optimizer

The complicated flow conditions and massive design parameters bring two main difficulties to the aerodynamic optimization of axial compressors: expensive evaluations and numerous optimization variables. To address these challenges, this paper establishes a novel fast aerodynamic optimization platform for axial compressors, consisting of a radial basic function (RBF)-based blade parameterization method, a data-driven differential evolution optimizer, and a computational fluid dynamic (CFD) solver. As a versatile interpolation method, RBF is used as the shape parameterization and deformation technique to reduce optimization variables. Aiming to acquire competitive solutions in limited steps, a data-driven evolution optimizer is developed, named the pre-screen surrogate model assistant differential evolution (pre-SADE) optimizer. Different from most surrogate model-assisted evolutionary algorithms, surrogate models in pre-SADE are used to screen the samples, rather than directly estimate them, in each generation to reduce expensive evaluations. The polynomial regression model, Kriging model, and RBF model are integrated in the surrogate model to improve the accuracy. To further save optimization time, the optimizer also integrates parallel task management programs. The aerodynamic optimization of a transonic rotor (NASA Rotor 37) is performed as the validation of the platform. A differential evolution (DE) optimizer and another surrogate model-assisted algorithm, committee-based active learning for surrogate model assisted particle swarm optimization (CAL-SAPSO), are introduced for the comparison runs. After optimization, the adiabatic efficiency, total pressure ratio, and surge margin are, respectively, increased by 1.47%, 1.0%, and 0.79% compared to the initial rotor. In the same limited steps, pre-SADE gets a 0.57% and 0.51% higher rotor adiabatic efficiency than DE and CAL-SAPSO, respectively. With the help of parallel techniques, pre-SADE and DE save half the optimization time compared to CAL-SAPSO. The results verify the effectiveness and the rapidity of the fast aerodynamic optimization platform.

CFD-based optimization of a displacement trimaran hull for improving its calm water and wavy condition resistance

This paper presents a multi-objective shape optimization approach for improving the bow region of a trimaran ship hull. A CFD-based design study is conducted to reduce the total resistance of trimaran ship hull in calm water and wavy condition. Accordingly, a practical multi-objective optimization platform is established and developed for ship hull modification. In addition, the hullform of a displacement trimaran ship with inverted bow is modified as a case study. Six objective functions are utilized in the present study by considering the weighted sum optimization method. Reduction of total resistance at two cruise and sprint speeds in calm water, reduction of resistance in two different wave conditions, and two cruise and sprint speeds are the six objectives of the study. Two aspects of ship hydrodynamics, resistance, and seakeeping are the disciplines that are considered through the proposed optimization process. Ship hull parametrization is performed by Arbitrary Shape Deformation (ASD) technique that defines the input variables for optimization process. The geometry reconstruction step connects to CFD solver in order to calculate the response of the optimization cycle. An innovative Simcenter SHERPA algorithm is employed to optimize the design objectives. The optimization results show a 3.14% reduction in the aggregated objective function. Generated waves around the hulls of the optimized trimaran have constructive interaction and diminish each other in calm water. A forefoot angle and sharper nose are created at bow region of the optimized hullform. Moreover, the comparison between baseline and optimized trimaran hull confirms the validity of the proposed optimization design strategy.

Detail-Preserving Shape Unfolding.

Canonical extrinsic representations for non-rigid shapes with different poses are preferable in many computer graphics applications, such as shape correspondence and retrieval. The main reason for this is that they give a pose invariant signature for those jobs, which significantly decreases the difficulty caused by various poses. Existing methods based on multidimentional scaling (MDS) always result in significant geometric distortions. In this paper, we present a novel shape unfolding algorithm, which deforms any given 3D shape into a canonical pose that is invariant to non-rigid transformations. The proposed method can effectively preserve the local structure of a given 3D model with the regularization of local rigid transform energy based on the shape deformation technique, and largely reduce geometric distortion. Our algorithm is quite simple and only needs to solve two linear systems during alternate iteration processes. The computational efficiency of our method can be improved with parallel computation and the robustness is guaranteed with a cascade strategy. Experimental results demonstrate the enhanced efficacy of our algorithm compared with the state-of-the-art methods on 3D shape unfolding.

Automated CFD-based optimization of inverted bow shape of a trimaran ship: Proposing an applicable and efficient optimization platform

This paper investigates the improvement of bow region of a trimaran ship hull, proposing a CFD-based automated approach to reduce total resistance. Two main goals are pursued; to create and develop a useful optimization platform for ship hull modification, and then investigate the influence of different inverted bow on hydrodynamic performance of trimaran ship. A wave-piercing bow trimaran hull is the baseline design. Ship bow is redesigned by Arbitrary Shape Deformation (ASD) technique that defines the input variables for optimization process. The objective function is the drag force and this study is conducted at cruise speed. To accomplish this task, two optimization methods are sequentially applied. A Latin Hypercube Sampling tool distributes design points and an RBF based surrogated model is constructed to investigate system behavior. Final optimum design in Design of Experiment (DOE) study is introduced to direct optimization SHERPA algorithm. Integration of CFD solver, geometric parametrization, and optimizer tool is managed by HEEDS MDO package with a multi-connection approach. Optimization results show successful optimization along with 10.2% resistance reduction. Comparison between initial and optimized hull demonstrates that the proposed optimization platform can be used for ship hull optimization in industrial application with significantly reduced computational time and effort.

An investigation into fishing boat optimisation using a hybrid algorithm

The optimisation of high-speed fishing boats is different from the optimisation of other displacement type vessels as, for high-speed fishing boats, the wave-making resistance decreases while the splashed resistance increases sharply. To reduce fuel consumption and operating costs in the current economic climate, this paper presents a fishing boat optimisation approach using a Computational Fluid Dynamics (CFD) technique. The RANS-VoF solver was utilised to calculate total resistance, sinkage and trim for a fishing boat in calm water. The Arbitrary Shape Deformation (ASD) technique was used to smoothly alter the geometry. A hybrid algorithm was presented to solve the complicated nonlinear optimisation problem. Herein, a Design of Experiments (DoE) method was applied to find an optimal global region and a mathematical programme was employed to determine an optimal global solution. Under the same displacement with the original hull, two optimisation loops were built with different design variables. After completion of the optimisation, two optimal hull forms were obtained. The optimisation results show that the optimisation loop presented in this study can be used to design a suitable fishing boat in the reduction of the total resistance in calm water.

Spectral Affine‐Kernel Embeddings

AbstractIn this paper, we propose a controllable embedding method for high‐ and low‐dimensional geometry processing through sparse matrix eigenanalysis. Our approach is equally suitable to perform non‐linear dimensionality reduction on big data, or to offer non‐linear shape editing of 3D meshes and pointsets. At the core of our approach is the construction of a multi‐Laplacian quadratic form that is assembled from local operators whose kernels only contain locally‐affine functions. Minimizing this quadratic form provides an embedding that best preserves all relative coordinates of points within their local neighborhoods. We demonstrate the improvements that our approach brings over existing nonlinear dimensionality reduction methods on a number of datasets, and formulate the first eigen‐based as‐rigid‐as‐possible shape deformation technique by applying our affine‐kernel embedding approach to 3D data augmented with user‐imposed constraints on select vertices.

Research on bulbous bow optimization based on the improved PSO algorithm

In order to reduce the total resistance of a hull, an optimization framework for the bulbous bow optimization was presented. The total resistance in calm water was selected as the objective function, and the overset mesh technique was used for mesh generation. RANS method was used to calculate the total resistance of the hull. In order to improve the efficiency and smoothness of the geometric reconstruction, the arbitrary shape deformation (ASD) technique was introduced to change the shape of the bulbous bow. To improve the global search ability of the particle swarm optimization (PSO) algorithm, an improved particle swarm optimization (IPSO) algorithm was proposed to set up the optimization model. After a series of optimization analyses, the optimal hull form was found. It can be concluded that the simulation based design framework built in this paper is a promising method for bulbous bow optimization.

Hull form optimisation in waves based on CFD technique

ABSTRACTThe seakeeping behavior of a ship in waves is different from its behavior in calm water. The resistance and seakeeping performance of a ship must be considered in the early-stage design. Therefore, this paper proposes a hull form optimization framework aiming to achieve the minimum total resistance in waves using a computational fluid dynamics (CFD) technique. A sinusoidal wave is adopted to establish the numerical wave tank and the overset mesh technique is used to facilitate the motions of the ships in question. The total resistance of the hull in waves is regarded as the objective function which is calculated using the Reynolds averaged Navier–Stokes (RANS) method. The arbitrary shape deformation (ASD) technique is used to change the geometry. Under displacement and design variables, a hybrid algorithm is developed to evaluate the objective function combining the optimal Latin hypercube design (Opt LHD) and the non-linear programming by quadratic Lagrangian (NLPQL) algorithm. Finally, two examples of hull form optimization are presented and discussed for David Taylor Model Basin (DTMB) model 5512 and WIGLEY III cases. The results show the effectiveness of the optimization framework developed in the present study, which can lay the foundation for further optimization of full-scale ships.

Computational fluid dynamics-based hull form optimization using approximation method

ABSTRACTWith the rapid development of the computational technology, computational fluid dynamics (CFD) tools have been widely used to evaluate the ship hydrodynamic performances in the hull forms optimization. However, it is very time consuming since a great number of the CFD simulations need to be performed for one single optimization. It is of great importance to find a high-effective method to replace the calculation of the CFD tools. In this study, a CFD-based hull form optimization loop has been developed by integrating an approximate method to optimize hull form for reducing the total resistance in calm water. In order to improve the optimization accuracy of particle swarm optimization (PSO) algorithm, an improved PSO (IPSO) algorithm is presented where the inertia weight coefficient and search method are designed based on random inertia weight and convergence evaluation, respectively. To improve the prediction accuracy of total resistance, a data prediction method based on IPSO-Elman neural network (NN) is proposed. Herein, IPSO algorithm is used to train the weight coefficients and self-feedback gain coefficient of ElmanNN. In order to build IPSO-ElmanNN model, optimal Latin hypercube design (Opt LHD) is used to design the sampling hull forms, and the total resistance (objective function) of these hull forms are calculated by Reynolds averaged Navier–Stokes (RANS) method. For the purpose of this article, this optimization framework has been employed to optimize two ships, namely, the DTMB5512 and WIGLEY III, and these hull forms are changed by arbitrary shape deformation (ASD) technique. The results show that the optimization framework developed in this study can be used to optimize hull forms with significantly reduced computational effort.

Medial-axis-driven shape deformation with volume preservation

The medial axis is a natural skeleton for shapes. However, it is rarely used in the existing skeleton-based shape deformation techniques. In this paper, we propose a novel medial-axis-driven skin surface deformation algorithm with volume preservation property. Specifically, an as-rigid-as-possible deformation scheme is used to deform the medial axis so that its local transform is as close as possible to a rigid transform. We maintain surface features of the deformed shape based on an implicit skinning method. Our experiments show that the proposed algorithm effectively preserves the volume of deformed shape and addresses the bending and twisting problems associated with traditional skeleton-based shape deformation techniques.

Smooth Rotation Enhanced As-Rigid-As-Possible Mesh Animation.

In recent years, the As-Rigid-As-Possible (ARAP) shape deformation and shape interpolation techniques gained popularity, and the ARAP energy was successfully used in other applications as well. We improve the ARAP animation technique in two aspects. First, we introduce a new ARAP-type energy, named SR-ARAP, which has a consistent discretization for surfaces (triangle meshes). The quality of our new surface deformation scheme competes with the quality of the volumetric ARAP deformation (for tetrahedral meshes). Second, we propose a new ARAP shape interpolation method that is superior to prior art also based on the ARAP energy. This method is compatible with our new SR-ARAP energy, as well as with the ARAP volume energy.

Pattern-aware shape deformation using sliding dockers

This paper introduces a new structure-aware shape deformation technique. The key idea is to detect continuous and discrete regular patterns and ensure that these patterns are preserved during free-form deformation. We propose a variational deformation model that preserves these structures, and a discrete algorithm that adaptively inserts or removes repeated elements in regular patterns to minimize distortion. As a tool for such structural adaptation, we introduce sliding dockers, which represent repeatable elements that fit together seamlessly for arbitrary repetition counts. We demonstrate the presented approach on a number of complex 3D models from commercial shape libraries.

Optimization of the head shape of the CRH3 high speed train

Aiming at optimizing the head shape of the CRH3 high speed train, an efficient optimization approach is proposed. The CFD analysis by solving Navier-Stokes equations is coupled with optimization calculation based on the multi-objective genetic algorithm, meanwhile the arbitrary shape deformation technique (ASD) is also introduced into the design flow, which greatly shortens the time consumption for geometry regeneration and flow field remeshing. As a result, the efficiency of the optimization calculation is highly improved. Statistical analysis is done to the designs in the design space, and the correlation between the design variables and the objective is studied to find out the key variables that most affect the objective. Response surface analysis is also performed to get the nonlinear relationship between the key design variables and the objective with the Kriging algorithm. Finally, after the optimization, an aerodynamic performance comparison between the optimal shape and the original shape reveals that the original shape of CRH3 high speed train owns a very stable aerodynamic performance and can be trustingly used in industry.

Performance capture from sparse multi-view video

This paper proposes a new marker-less approach to capturing human performances from multi-view video. Our algorithm can jointly reconstruct spatio-temporally coherent geometry, motion and textural surface appearance of actors that perform complex and rapid moves. Furthermore, since our algorithm is purely meshbased and makes as few as possible prior assumptions about the type of subject being tracked, it can even capture performances of people wearing wide apparel, such as a dancer wearing a skirt. To serve this purpose our method efficiently and effectively combines the power of surface- and volume-based shape deformation techniques with a new mesh-based analysis-through-synthesis framework. This framework extracts motion constraints from video and makes the laser-scan of the tracked subject mimic the recorded performance. Also small-scale time-varying shape detail is recovered by applying model-guided multi-view stereo to refine the model surface. Our method delivers captured performance data at high level of detail, is highly versatile, and is applicable to many complex types of scenes that could not be handled by alternative marker-based or marker-free recording techniques.

Skeleton‐based Variational Mesh Deformations

Abstract In this paper, a new free‐form shape deformation approach is proposed. We combine a skeleton‐based mesh deformation technique with discrete differential coordinates in order to create natural‐looking global shape deformations. Given a triangle mesh, we first extract a skeletal mesh, a two‐sided Voronoibased approximation of the medial axis. Next the skeletal mesh is modified by free‐form deformations. Then a desired global shape deformation is obtained by reconstructing the shape corresponding to the deformed skeletal mesh. The reconstruction is based on using discrete differential coordinates. Our method preserves fine geometric details and original shape thickness because of using discrete differential coordinates and skeleton‐based deformations. We also develop a new mesh evolution technique which allow us to eliminate possible global and local self‐intersections of the deformed mesh while preserving fine geometric details. Finally, we present a multi‐resolution version of our approach in order to simplify and accelerate the deformation process. In addition, interesting links between the proposed free‐form shape deformation technique and classical and modern results in the differential geometry of sphere congruences are established and discussed.

Scalar-field-guided adaptive shape deformation and animation

In this paper, we propose a novel scalar-field-guided adaptive shape deformation (SFD) technique founded on PDE-based flow constraints and scalar fields of implicit functions. Scalar fields are used as embedding spaces. Upon deformation of the scalar field, a corresponding displacement/velocity field will be generated accordingly, which results in a shape deformation of the embedded object. In our system, the scalar field creation, sketching, and manipulation are both natural and intuitive. The embedded model is further enhanced with self-optimization capability. During the deformation we can also enforce various constraints on embedded models. In addition, this technique can be used to ease the animation design. Our experiments demonstrate that the new SFD technique is powerful, efficient, versatile, and intuitive for shape modeling and animation.

Modeling Surperspective Projection of Landscapes for Geographical Guide-Map Generation

It is still challenging to generate hand-drawn pictures because they differ from ordinary photographs in that they are often drawn as seen from multiple viewpoints. This paper presents a new approach for modeling such surperspective projection based on shape deformation techniques. Specifically, surperspective landscape images for guide-maps are generated from 3D geographical elevation data. Our method first partitions a target geographical surface into feature areas to provide designers with landmarks suitable for editing. The system takes as input 2D visual effects, which are converted to 3D geometric constraints for geographical surface deformation. Using ordinary perspective projection, the deformed shape is then transformed into a target guide-map image where each landmark enjoys its own vista points. An algorithm for calculating such 2D visual effects semi-automatically from the geographical shape features is also considered.

Inverse Neumann obstacle problem

Results are reported for direct and inverse scattering of plane acoustic waves from sound-hard scatterers of arbitrary shapes in an infinite, homogeneous ambience. The direct problem is solved via a shape deformation technique which is valid for finite deformations. The resulting solution requires solving only a set of algebraic recursion relations, but neither integral equations nor Green’s function. The methodology has three essential features: all calculations refer exclusively to a known simple boundary Γs instead of the iteratively updated scatterer shapes; the Jacobian of the scattered field is evaluated by solving a series of Helmholtz’s equations (with different boundary data) in the region exterior to the simple shape Γs; and no ambiguity in the solution arises due to the interior eigenvalues. The inverse problem of recovering the scatterer boundary shape is solved by least square minimization using the Levenberg–Marquardt algorithm. Inversions of several two-dimensional shapes with varying degrees of complexity are reported. The procedures described generalize straightforwardly to transmission and three-dimensional problems.