Rendering Pearlescent Appearance Based On Paint-Composition Modelling

We describe a new approach to modelling pearlescent paints based on decomposing paint layers into stacks of imaginary thin sublayers. The sublayers are chosen so thin that multiple scattering can be considered across different sublayers, while it can be neglected within each of the sublayers. Based on this assumption, an efficient recursive procedure of assembling the layers is developed, which enables to compute the paint BRDF at interactive speeds. Since the proposed paint model connects fundamental optical properties of multi-layer pearlescent and metallic paints with their microscopic structure, interactive prediction of the paint appearance based on its composition becomes possible.     

A Physically Based Colour Model

We propose an intuitively simple way of representing colour which has the additional virtue that, it permits mixing and overlaying of transparent and opaque paints to an arbitrary degree. Our approach is related to the earlier alpha channel model used for compositing. It includes this as a special case but has applications in many other areas, especially animation, paint programs and graphics libraries.     

Multi-Camera Piecewise Planar Object Tracking with Mutual Information

Real-time and robust tracking of 3D objects based on a 3D model with multiple cameras is still an unsolved problem albeit relevant in many practical and industrial applications. Major problems are caused by appearance changes of the object. We present a template-based tracking algorithm for piecewise planar objects. It is robust against changes in the appearance of the object (occlusion, illumination variation, specularities). The version we propose supports multiple cameras. The method consists in minimizing the error between the observed images of the object and the warped images of the planes. We use the mutual information as registration function combined with an inverse composition approach for reducing the computational costs and get a near-real-time algorithm. We discuss different hypotheses that can be made for the optimization algorithm.     

Brush up your painting skills

Most present-day interactive paint applications lack the means of adequately capturing a user’s gestures and translating them into realistic and predictable strokes, despite the importance of such a mechanism. We present a novel brush design that adopts constrained energy optimization to deform the brush tuft according to the user’s input movement. It incorporates bidirectional paint transfer and an anisotropic friction model. The main advantage of our method is its ability to handle a wide range of brush tuft shapes that are animated using a freeform deformation lattice, which is associated with the tuft’s geometry. This way, almost no conditions or limitations are placed upon the appearance of the brush. Examples range from round brushes modeled as polygon meshes, to flat brushes with individual bristles. Less common deformable tools that are used to apply or remove paint on the canvas, like sponges, can be created as well. The model is integrated in our interactive painting system for creating images with watery paint.     

The inverse approach of FlexPaint [robotic spray painting]

Industrial painting automation with robots is very efficient and fast and often used in production lines. However, a big disadvantage is the off-line programming paradigm for the painting robots. This is time-consuming and can be justified economically only for large lot sizes. Hence, a totally new approach to robot programming is required to enable painting of small lot sizes. The objective of the FlexPaint project is to automate robot-programming applications of small lot sizes with a very high number of part variants. This article reports the new approach, referred to as an inverse approach that automatically generates the painting motion. This approach opens new markets for robotic applications. The automatic robot program generation enables, for the first time, painting parts of a lot size of one. The principle of this approach is based on formalizing the technological knowledge in a geometry library and a process library. Laser range sensors are used to obtain an accurate scan of the part. Process-relevant classes of features are detected as specified in the geometry library. Feature classes are linked in the process library to basic paint strategies, which are grouped to automatically generate the robot paint tool trajectory. Finally collisions-free and executable robot motions are automatically obtained for the actual robot kinematics. Painting results for several parts, e.g., different motors with gearboxes, would result with this new approach.     

Computer-aided design of porous artifacts

Heterogeneous structures represent an important new frontier for 21st century engineering. Human tissues, composites, ‘smart’ and multi-material objects are all physically manifest in the world as three-dimensional (3D) objects with varying surface, internal and volumetric properties and geometries. For instance, a tissue engineered structure, such as bone scaffold for guided tissue regeneration, can be described as a heterogeneous structure consisting of 3D extra-cellular matrices (made from biodegradable material) and seeded donor cells and/or growth factors.The design and fabrication of such heterogeneous structures requires new techniques for solid models to represent 3D heterogeneous objects with complex material properties. This paper presents a representation of model density and porosity based on stochastic geometry. While density has been previously studied in the solid modeling literature, porosity is a relatively new problem. Modeling porosity of bio-materials is critical for developing replacement bone tissues. The paper uses this representation to develop an approach to modeling of porous, heterogeneous materials and provides experimental data to validate the approach. The authors believe that their approach introduces ideas from the stochastic geometry literature to a new set of engineering problems. It is hoped that this paper stimulates researchers to find new opportunities that extend these ideas to be more broadly applicable for other computational geometry, graphics and computer-aided design problems.     

Modelling the Texture of Paint

We present an extension to the WET & STICKY model. A method of modelling textured and shiny paint is described using bump mapping and standard illumination models. The qualities of the paint are used to supply input to the texture and lighting models. We demonstrate that a dynamic model of textured paint provides the user with valuable visual cluesfor the production of realistic painted images. We also propose further extensions which would allow the use of different lighting models for different paints, allowing for paint attributes which are unachievable either with traditional painting or with earlier forms of electronic painting.     

Linear programming models for traffic engineering in 100% survivable networks under combined IS–IS/OSPF and MPLS-TE

This paper concerns the problem of minimizing the maximum link utilization of IP telecommunication networks under the joint use of traditional IGP routing protocols, such as IS–IS and OSPF, and the more sophisticated MPLS-TE technology. It is shown that the problem of choosing the optimal routing, both under working conditions and under single link failure scenarios, can be cast as a linear program of reasonable size. The proposed model is validated by a computational experimentation performed on synthetic and real networks: the obtained results show that the new approach considerably reduces the maximum link utilization of the network with respect to simply optimizing the IGP weights, at the cost of adding a limited number of label switched paths (LSPs). Optimizing the set of IGP weights within the overall approach further improves performances. The computational time needed to solve the models matches well with real-time requirements, and makes it possible to consider network design problems.     

Inverse data envelopment analysis model to preserve relative efficiency values: The case of variable returns to scale

This paper studies the inverse Data Envelopment Analysis (inverse DEA) for the case of variable returns to scale (inverse BCC). The developed inverse BCC model can preserve relative efficiency values of all decision making units (DMUs) in a new production possibility set composing of all current DMUs and a perturbed DMU with new input and output values. We consider the inverse BCC model for a resource allocation problem, where increases of some outputs and decreases of the other outputs of the considered DMU can be taken into account simultaneously. The inverse BCC problem is in the form of a multi-objective nonlinear programming model (MONLP), which is not easy to solve. We propose a linear programming model, which gives a Pareto-efficient solution to the inverse BCC problem. However, there exists at least an optimal solution to the proposed model if and only if the new output vector is in the set of current production possibility set. The proposed approach is illustrated via a case study of a motorcycle-part company.     

用演化算法求解抛物型方程扩散系数的识别问题

基于演化算法给出了一类求解参数识别反问题的一般方法,该方法表明只要找到好的、求解相应的正问题的数值方法,演化算法就可以用于求解此类反问题。设计有效的求解反问题的演化算法的关键是寻找一种适合反问题的解空间的编码表示形式、适当的适应值函数形式以及有效的计算正问题的数值方法。该文结合算法、传统的求解反问题的工方法和正则化技术,设计了一类求解参数识别反问题的方法。为验证此类方法,将其用于求解一维扩散方程的     

Hierarchical decision making for proactive quality control: system development for defect reduction in automotive coating operations

Product quality control (QC) in manufacturing usually relies solely on inspection. Once a quality problem is found, a solution is sought usually based on experience, which is basically ad hoc. A new generation of QC requires the integration of both quality prediction and inspection. Automotive coating is a typical example. In the paint shop of an automotive assembly plant, topcoat filmbuild quality on vehicle surface has been a major concern. In production, defects are frequently generated in the very thin coating layers, which can degrade severely both coating appearance and durability. Trial and error in troubleshooting is a usual practice.In this paper, we introduce a proactive QC approach by resorting to artificial intelligence and engineering fundamentals. The approach is developed for solving a class of engineering problems for which conventional reactive QC approaches are feeble due to system complexity and uncertainties, such as that in paint applications. The main focus of the approach is on-process, rather than post-process. Thus, the domain knowledge about a process is fully explored and correlation of the process to product quality is established in a systematic way. In this approach the knowledge is expressed either symbolically or numerically, and structured in a hierarchy as reasoning progresses. Decision making is performed by a fuzzy MIN–MAX algorithm for heuristic knowledge and optimization for fundamental knowledge. To demonstrate the efficacy of the methodology, an application to QC of automotive topcoat is illustrated through developing an intelligent decision support system. This system is capable of evaluating process performance, and providing various valuable decision supports for defect prevention in different stages of a topcoat application process.     

A Bayesian Inference Framework for Procedural Material Parameter Estimation

Procedural material models have been gaining traction in many applications thanks to their flexibility, compactness, and easy editability. We explore the inverse rendering problem of procedural material parameter estimation from photographs, presenting a unified view of the problem in a Bayesian framework. In addition to computing point estimates of the parameters by optimization, our framework uses a Markov Chain Monte Carlo approach to sample the space of plausible material parameters, providing a collection of plausible matches that a user can choose from, and efficiently handling both discrete and continuous model parameters. To demonstrate the effectiveness of our framework, we fit procedural models of a range of materials—wall plaster, leather, wood, anisotropic brushed metals and layered metallic paints—to both synthetic and real target images.     

Task-oriented design of robot kinematics using the Grid Method

This paper presents a task-oriented design method for robot kinematics based on the Grid Method, which is widely used in the finite difference method and heat transfer/fluid flow analyses. This approach drastically reduces the complexity of the whole problem and increases the efficiency compared with previous approaches. More specifically, the Grid Method with a new formulation simplifies the design to a problem of a four-design-variable unit grid, which does not require solving inverse/forward kinematics. The efficiency of the Grid Method has been confirmed through a kinematics design of a planar robot for nuclear power plants and spatial robots.     

Real-time image marbleization

We present a new real-time image marbleization method that converts an image into a marble-like appearance automatically. The approach models the marbleization process as a two-dimensional fluid dynamics problem, whereby color advection of an input image results in a marbleized image. During the fluid dynamics simulation, we add a pixel-level external force field which is tangent to salient features in the image. The forces are computed from the image characteristics without user intervention. A stylized image with marble-like appearance is easily created that maintains the basic shape of objects in the input image. The entire modeling framework is implemented on a graphics processing unit, thus enabling real-time visual feedback. This approach provides a new tool to design figurative marbling textures without mixing of colors, which are almost impossible with previous computer-generated marbling methods.     

Developing a novel inverse data envelopment analysis (DEA) model for evaluating after-sales units

This paper proposes a novel model of inverse data envelopment analysis (IDEA) based on the slack-based measure (SBM) approach. The developed inverse SBM model can maintain relative efficiency of decision making units (DMUs) with new input and output. This model can also measure the input and output volumes when a decision maker (DM) increases efficiency score. The inverse SBM model is a kind of multi-objective non-linear programming (MONLP) problem, which is not easy to solve. Therefore, we suggest a linear programming model for solving inverse SBM model. In this model efficiency score of DMU under evaluation remains unchanged. Furthermore, we suggest an optimal combination of inputs and outputs in the production possibility set (PPS). A case study is presented to demonstrate the efficacy of our proposed model.     

Rasterizing algebraic curves and surfaces

A new, recursive, space-subdivision algorithm for rasterizing algebraic curves and surfaces gets its accuracy from a newly devised, computationally efficient, and asymptotically correct test. The approach followed is essentially the interval arithmetic method for rendering implicit curves. The author's contribution is a particularly efficient way to construct inclusion functions for polynomials. An ideal algorithm is given for rendering an algebraic curve Z(f)={(x,y):f(x,y)=0} in a square box of side n. The algorithm scans the square and paints only those pixels cut by the curve. This algorithm is ideal, because every correct algorithm should paint exactly the same pixels, but it is impractical. It requires n² test evaluations, one for each pixel in the square. However, since in general it will be rendering a curve on a planar region, the number of pixels it is expected to paint is only O(n). We need a more efficient algorithm. There are two issues to examine. The first is how to reduce the computational complexity by recursive subdivision. The second is how to test whether the curve Z(f) cuts a square     

基于多表观模型竞争的视觉跟踪算法

在视觉跟踪中,如何适时地更新目标模型是影响跟踪算法跟踪精度和鲁棒性的关键性因素,也是当前研究中面临的重点和难点问题。对此,提出了一种基于多表观模型竞争的模型更新策略,通过多表观模型中各子模型的贡献度大小确定竞争优势排序,当最优子模型的贡献度满足多表观模型更新阈值时,对各子模型及其对应的系数进行更新,否则,仅对部分子模型进行更新。在此基础上,以粒子滤波算法为跟踪框架,提出了基于多表观模型竞争的视觉跟踪算法。实验结果表明,所提算法能够较好地处理视觉跟踪中的模型更新问题,跟踪性能较无模型更新策略的粒子滤波算法有明显提高。     

Identification of time-varying pH processes using sinusoidal signals

This paper presents an approach to the identification of time-varying, nonlinear pH processes based on the Wiener model structure. The algorithm produces an on-line estimate of the titration curve, where the shape of this static nonlinearity changes as a result of changes in the weak-species concentration and/or composition of the process feed stream. The identification method is based on the recursive least-squares algorithm, a frequency sampling filter model of the linear dynamics and a polynomial representation of the inverse static nonlinearity. A sinusoidal signal for the control reagent flow rate is used to generate the input-output data along with a method for automatically adjusting the input mean level to ensure that the titration curve is identified in the pH operating region of interest. Experimental results obtained from a pH process are presented to illustrate the performance of the proposed approach. An application of these results to a pH control problem is outlined.     

Combined Direct and Inverse Kinematic Control for Articulated Figure Motion Editing

A new approach for the animation of articulated figures is presented. We propose a system of articulated motion design which offers a full combination of both direct and inverse kinematic control of the joint parameters. Such an approach allows an animator to specify interactively goal-directed changes to existing sampled joint motions, resulting in a more general and expressive class of possible joint motions. The fundamental idea is to consider any desired-joint space motion as a reference model inserted into the secondary task of an inverse kinematic control scheme. This approach profits from the use of half-space Cartesian main tasks in conjunction with a parallel control of the articulated figure called the coach-trainee metaphor. In addition, a transition function is introduced so as to guarantee the continuity of the control. The resulting combined kinematic control scheme leads to a new methodology of joint-motion editing which is demonstrated through the improvement of a functional model of human walking.     

Adaptive fuzzy model based inverse controller design using BB-BC optimization algorithm

The use of inverse system model as a controller might be an efficient way in controlling non-linear systems. It is also a known fact that fuzzy logic modeling is a powerful tool in representing nonlinear systems. Therefore, inverse fuzzy model can be used as a controller for controlling nonlinear plants. In this context, firstly, a new fuzzy model based inverse controller design methodology is presented in this study. The design methodology introduced here is based on a recursive optimization procedure that searches for an optimal inverse model control signal at every sampling time. Since the task of optimization should be accomplished in between two sampling periods the use of a fast optimization algorithm becomes essential. For this reason, Big Bang-Big Crunch (BB-BC) optimization algorithm is used due to its low computational time and high global convergence properties. Even though, inverse model controllers may produce perfect control while operating in an open loop fashion, this open loop control would not be sufficient in the case of modeling mismatches or disturbances that might occur over the system. In order to overcome this problem, secondly, an on-line adaptation mechanism via BB-BC optimization algorithm is introduced in addition to BB-BC optimization based fuzzy model inverse controller. The adaptation mechanism is used to update the related parameters of the model while minimizing the absolute value of the instantaneous error between the system and model outputs. In this manner, the system output is somehow fed back, the overall control form can be considered as a closed-loop system. The new fuzzy model based inverse control scheme with the new online adaptation mechanism has been implemented and tested on the two real time processes; namely, heat transfer and pH processes and very satisfactory results has been reported.