A feature based shape optimization technique for the configuration and parametric design of flat plates

A new feature based shape optimization technique is presented that is capable of modifying the topology (configuration) and shape to reduce the area of 2-D components based on the stress distribution in the component. Shape optimization attempts to maximize material usage to achieve a uniform stress distribution near the allowable limit of the material. Features can be added to the component, or can be modified, in order to optimize the material usage. By using features as a basis for shape modification, the problem of component connectivity can be handled in a consistent, intelligent manner, and the problem of smoothness is eliminated. A program was written to implement the optimization technique and was applied to two example problems, including one from the literature that used a different modification technique. The other example illustrates shape modification capabilities with more complicated geometry. Results from both examples are compared to results obtained using other topological modification techniques.     

Manipulation of CAD surface models with haptics based on shape control functions

With traditional two-dimensional based interfaces, many CAD surface models are difficult to design and edit due to their 3D nature. This paper discusses a technique for the deformation of CAD surface models with haptic interaction based on shape control functions. With the technique, designers can use a haptic interface to directly touch a native B-rep CAD model, and deform it in real-time by pushing, pulling and dragging its surfaces in a natural 3D environment. The deformation is governed by shape control functions. By using the shape functions, designers can specify the area of deformation, and also have greater controls on the shape of deformation. This technique is numerically efficient, and can deform complex surface models involving several thousand control points in real-time. The haptic-based deforming approach gives designers greater flexibility for the manipulation of complex CAD surfaces.     

Improving Initial Flattening of Convex-Shaped Free-Form Mesh Surface Patches Using a Dynamic Virtual Boundary

This study proposes an efficient algorithm for improving flattening result of triangular mesh surface patches having a convex shape. The proposed approach, based on barycentric mapping technique, incorporates a dynamic virtual boundary, which considerably improves initial mapping result. The dynamic virtual boundary approach is utilized to reduce the distortions for the triangles near the boundary caused by the nature of convex combination technique. Mapping results of the proposed algorithm and the base technique are compared by area and shape accuracy metrics measured for several sample surfaces. The results prove the success of the proposed approach with respect to the base method.     

Including shape handles in recursive subdivision surfaces

In the present paper, the problem of the generation of an interpolating surface for a given, general polyhedron is studied. The surface must interpolate the set of vertices of the initial polyhedron, and allow a certain shape control. A two-step process based on a topological modification of the polyhedron, and a subsequent biquadratic recursive subdivision is used. It allows the definition of a set of scalar shape handles associated to the initial vertices, that do not affect the interpolatory properties of the surface. Their effect on the quality of the final shape is discussed, and an iterative algorithm for the computation of an optimal set of shape handles is proposed.     

An interactive local flattening operator to support digital investigations on artwork surfaces

Analyzing either high-frequency shape detail or any other 2D fields (scalar or vector) embedded over a 3D geometry is a complex task, since detaching the detail from the overall shape can be tricky. An alternative approach is to move to the 2D space, resolving shape reasoning to easier image processing techniques. In this paper we propose a novel framework for the analysis of 2D information distributed over 3D geometry, based on a locally smooth parametrization technique that allows us to treat local 3D data in terms of image content. The proposed approach has been implemented as a sketch-based system that allows to design with a few gestures a set of (possibly overlapping) parameterizations of rectangular portions of the surface. We demonstrate that, due to the locality of the parametrization, the distortion is under an acceptable threshold, while discontinuities can be avoided since the parametrized geometry is always homeomorphic to a disk. We show the effectiveness of the proposed technique to solve specific Cultural Heritage (CH) tasks: the analysis of chisel marks over the surface of a unfinished sculpture and the local comparison of multiple photographs mapped over the surface of an artwork. For this very difficult task, we believe that our framework and the corresponding tool are the first steps toward a computer-based shape reasoning system, able to support CH scholars with a medium they are more used to.     

Finger surface as a biometric identifier

We present a novel approach for personal identification and identity verification which utilizes 3D finger surface features as a biometric identifier. Using 3D range images of the hand, a surface representation for the index, middle, and ring finger is calculated and used for comparison to determine subject similarity. We use the curvature based shape index to represent the fingers’ surface. Gallery and probe shape index signatures are compared using the normalized correlation coefficient to compute a match score. A large unique database of hand images supports the research. We use data sets obtained over time to examine the performance of each individual finger surface as a biometric identifier as well as the performance obtained when combining them. Both identification and verification experiments are conducted. In addition, probe and gallery sets sizes are increased to further improve recognition performance in our experiments. Our approach yields good results for a first-of-its-kind biometric technique, indicating that this approach warrants further research.     

A sketching interface for feature curve recovery of free-form surfaces

In this paper, we present a semi-automatic approach to efficiently and robustly recover the characteristic feature curves of a given free-form surface where we do not have to assume that the input is a proper manifold. The technique supports a sketch-based interface where the user just has to roughly sketch the location of a feature by drawing a stroke directly on the input mesh. The system then snaps this initial curve to the correct position based on a graph-cut optimization scheme that takes various surface properties into account. Additional position constraints can be placed and modified manually which allows for an interactive feature curve editing functionality. We demonstrate the usefulness of our technique by applying it to two practical scenarios. At first, feature curves can be used as handles for surface deformation, since they describe the main characteristics of an object. Our system allows the user to manipulate a curve while the underlying non-manifold surface adopts itself to the deformed feature. Secondly, we apply our technique to a practical problem scenario in reverse engineering. Here, we consider the problem of generating a statistical (PCA) shape model for car bodies. The crucial step is to establish proper feature correspondences between a large number of input models. Due to the significant shape variation, fully automatic techniques are doomed to failure. With our simple and effective feature curve recovery tool, we can quickly sketch a set of characteristic features on each input model which establishes the correspondence to a pre-defined template mesh and thus allows us to generate the shape model. Finally, we can use the feature curves and the shape model to implement an intuitive modeling metaphor to explore the shape space spanned by the input models.     

A photometric sampling method for facial shape recovery

The authors propose a photometric method to recover facial shape that is consistent with expected facial proportions. The method borrows ideas from photometric sampling, a technique that estimates shape from continuous variations of a light source around a single circular path. This approach aims at enriching photometric information by including variations of the light source along its zenith angle. To this end, a luminance matrix describing lighting response along both azimuth and zenith angles of the light source is built for each pixel. A method based on fitting sine functions onto the singular vectors of the collected luminance matrices is proposed for estimating a surface normal map. The estimated surface normals are later refined to maximize a facial proportion criterion and finally be integrated. Experiments demonstrate that our approach successfully approximates 3D face shape while preserving facial proportions within the limits of expected depth.     

High-fidelity aerostructural optimization with integrated geometry parameterization and mesh movement

This paper extends an integrated geometry parameterization and mesh movement strategy for aerodynamic shape optimization to high-fidelity aerostructural optimization based on steady analysis. This approach provides an analytical geometry representation while enabling efficient mesh movement even for very large shape changes, thus facilitating efficient and robust aerostructural optimization. The geometry parameterization methodology uses B-spline surface patches to describe the undeflected design and flying shapes with a compact yet flexible set of parameters. The geometries represented are therefore independent of the mesh used for the flow analysis, which is an important advantage to this approach. The geometry parameterization is integrated with an efficient and robust grid movement algorithm which operates on a set of B-spline volumes that parameterize and control the flow grid. A simple technique is introduced to translate the shape changes described by the geometry parameterization to the internal structure. A three-field formulation of the discrete aerostructural residual is adopted, coupling the mesh movement equations with the discretized three-dimensional inviscid flow equations, as well as a linear structural analysis. Gradients needed for optimization are computed with a three-field coupled adjoint approach. Capabilities of the framework are demonstrated via a number of applications involving substantial geometric changes.     

Shape Analysis with Subspace Symmetries

We address the problem of partial symmetry detection, i.e., the identification of building blocks a complex shape is composed of. Previous techniques identify parts that relate to each other by simple rigid mappings, similarity transforms, or, more recently, intrinsic isometries. Our approach generalizes the notion of partial symmetries to more general deformations. We introduce subspace symmetries whereby we characterize similarity by requiring the set of symmetric parts to form a low dimensional shape space. We present an algorithm to discover subspace symmetries based on detecting linearly correlated correspondences among graphs of invariant features. We evaluate our technique on various data sets. We show that for models with pronounced surface features, subspace symmetries can be found fully automatically. For complicated cases, a small amount of user input is used to resolve ambiguities. Our technique computes dense correspondences that can subsequently be used in various applications, such as model repair and denoising.     

Real-Time Volume Deformations

Real-time free-form deformation tools are primarily based on surface or particle representations to allow for interactive modification and fast rendering of complex models. The efficient handling of volumetric representations, however, is still a challenge and has not yet been addressed sufficiently. Volumetric models, on the other hand, form an important class of representation in many applications. In this paper we present a novel approach to the real-time deformation of scalar volume data sets taking advantage of hardware supported 3D texture mapping. In a prototype implementation a modeling environment has been designed that allows for interactive manipulation of arbitrary parts of volumetric objects. In this way, any desired shape can be modeled and used subsequently in various applications. The underlying algorithms have wide applicability and can be exploited effectively for volume morphing and medical data processing.     

The influence of electric fields on nanostructures—Simulation and control

Macroscopic electric fields may be used to influence or even control the shape evolution of single layer islands on a crystalline surface. We validate a phase-field approach to simulate such shape evolutions by comparison with simulations based on a sharp interface approach. The phase-field model is then used to formulate and discretize the control problem of finding an electric field which drives an island to a predefined shape. Some first results of this approach are presented.     

深度图像中基于轮廓曲线和局部区域特征的3维物体识别

为了提高3维物体目标识别系统的性能及降低计算复杂度,提出一种由粗到细的识别方法。该方法利用深度图像所提供的信息,分两步完成识别过程。首先基于轮廓曲线计算其特征点,并映射到原有轮廓空间,以标志点序列表征原由轮廓进行匹配,在识别初期迅速排除模型库中不相似目标和差异较大的姿态,生成目标候选列表用于精确匹配,以提高识别效率。精确匹配采用一种基于局部区域特征的识别方法,以投票的策略获取最佳结果。局部区域由SIFT算子确定位置和数量,区域特征主要由表面指数和法向量夹角组成,具有平移和旋转不变性。为了更进一步提高效率和降低存储空间,模型库的数据分为轮廓和表面信息两部分,分别以标志位序列和哈希表的形式存储。实验结果表明,该方法具有良好的实时性和识别率,对遮挡和干扰有一定的适应性。     

Matching shape sequences in video with applications in human movement analysis

We present an approach for comparing two sequences of deforming shapes using both parametric models and nonparametric methods. In our approach, Kendall's definition of shape is used for feature extraction. Since the shape feature rests on a non-Euclidean manifold, we propose parametric models like the autoregressive model and autoregressive moving average model on the tangent space and demonstrate the ability of these models to capture the nature of shape deformations using experiments on gait-based human recognition. The nonparametric model is based on dynamic time-warping. We suggest a modification of the dynamic time-warping algorithm to include the nature of the non-Euclidean space in which the shape deformations take place. We also show the efficacy of this algorithm by its application to gait-based human recognition. We exploit the shape deformations of a person's silhouette as a discriminating feature and provide recognition results using the nonparametric model. Our analysis leads to some interesting observations on the role of shape and kinematics in automated gait-based person authentication.     

基于能量优化的NURBS曲面几何特征修改

NURBS作为曲面造型技术中的重要方法之一,在计算机辅助几何设计和计算机图形学领域中有着广泛的应用。针对NURBS曲面的几何特征修改,提出了基于能量优化的修改方法。通过对NURBS曲面的控制顶点进行扰动,以曲面的应力能改变为目标函数并使之最小化,实现了NURBS曲面上给定多个点处的位置、一阶偏导矢、二阶偏导矢和法矢等几何特征的修改。数值实例表明该方法用于微调时,可实现对曲面局部形状的多种修改效果,便于交互设计。     

Hydrodynamic design using a derivative-free method

A derivative-free shape optimization tool for computational fluid dynamics (CFD) is developed in order to facilitate the implementation of complex flow solvers in the design procedure. A modified Rosenbrocks method is used, which needs neither gradient evaluations nor approximations. This approach yields a robust and flexible tool and gives the capability of performing optimizations involving complex configurations and phenomena. The flow solver implemented solves the Reynolds-averaged Navier–Stokes equations (RANSE) on unstructured grids, using near-wall, low-Reynolds-number turbulence models. Free surface effects are taken into account by a pseudosteady surface tracking method. A mesh deformation strategy based on both lineal and torsional springs analogies is used to update the mesh while maintaining the quality of the grid near the wall for two-dimensional problems. A free-form-deformation technique is used to manage the mesh and the shape perturbations for three-dimensional cases. Two hydrodynamic applications are presented, concerning first the design of a two-dimensional hydrofoil in relation with the free-surface elevation and then the three-dimensional optimization of a hull shape, at full scale.     

Detection and accommodation of outliers in Wireless Sensor Networks within a multi-agent framework

This paper studies three techniques for outliers detection in the context of Wireless Sensor Networks, including a machine learning technique, a Principal Component Analysis-based methodology and an univariate statistics-based approach. The first methodology is based on a Least Squares-Support Vector Machine technique, together with a sliding window learning. A modification to this approach is also considered in order to improve its performance in non-stationary time-series. The second methodology relies on Principal Component Analysis, along with the robust orthonormal projection approximation subspace tracking with rank-1 modification, while the last approach is based on univariate statistics within an oversampling mechanism. All methods are implemented under a hierarchical multi-agent framework and compared through experiments carried out on a test-bed.