Flexible and Accurate Transparent‐Object Matting and Compositing Using Refractive Vector Field

In digital image editing, environment matting and compositing are fundamental and interesting operations that can capture and simulate the refraction and reflection effects of light from an environment. The state‐of‐the‐art real‐time environment matting and compositing method is short of flexibility, in the sense that it has to repeat the entire complex matte acquisition process if the distance between the object and the background is different from that in the acquisition stage, and also lacks accuracy, in the sense that it can only remove noises but not errors. In this paper, we introduce the concept of refractive vector and propose to use a refractive vector field as a new representation for environment matte. Such refractive vector field provides great flexibility for transparent‐object environment matting and compositing. Particularly, with only one process of the matte acquisition and the refractive vector field extraction, we are able to composite the transparent object into an arbitrary background at any distance. Furthermore, we introduce a piecewise vector field fitting algorithm to simultaneously remove both noises and errors contained in the extracted matte data. Experimental results show that our method is less sensitive to artefacts and can generate perceptually good composition results for more general scenarios.     

Flow‐Induced Inertial Steady Vector Field Topology

Traditionally, vector field visualization is concerned with 2D and 3D flows. Yet, many concepts can be extended to general dynamical systems, including the higher‐dimensional problem of modeling the motion of finite‐sized objects in fluids. In the steady case, the trajectories of these so‐called inertial particles appear as tangent curves of a 4D or 6D vector field. These higher‐dimensional flows are difficult to map to lower‐dimensional spaces, which makes their visualization a challenging problem. We focus on vector field topology, which allows scientists to study asymptotic particle behavior. As recent work on the 2D case has shown, both extraction and classification of isolated critical points depend on the underlying particle model. In this paper, we aim for a model‐independent classification technique, which we apply to two different particle models in not only 2D, but also 3D cases. We show that the classification can be done by performing an eigenanalysis of the spatial derivatives' velocity subspace of the higher‐dimensional 4D or 6D flow. We construct glyphs that depict not only the types of critical points, but also encode the directional information given by the eigenvectors. We show that the eigenvalues and eigenvectors of the inertial phase space have sufficient symmetries and structure so that they can be depicted in 2D or 3D, instead of 4D or 6D.     

Space‐Time Bifurcation Lines for Extraction of 2D Lagrangian Coherent Structures

We present a novel and efficient technique to extract Lagrangian coherent structures in two‐dimensional time‐dependent vector fields. We show that this can be achieved by employing bifurcation line extraction in the space‐time representation of the vector field, and generating space‐time bifurcation manifolds therefrom. To show the utility and applicability of our approach, we provide an evaluation of existing extraction techniques for Lagrangian coherent structures, and compare them to our approach.     

Efficient Gradient‐Domain Compositing Using an Approximate Curl‐free Wavelet Projection

Gradient‐domain compositing has been widely used to create a seamless composite with gradient close to a composite gradient field generated from one or more registered images. The key to this problem is to solve a Poisson equation, whose unknown variables can reach the size of the composite if no region of interest is drawn explicitly, thus making both the time and memory cost expensive in processing multi‐megapixel images. In this paper, we propose an approximate projection method based on biorthogonal Multiresolution Analyses (MRA) to solve the Poisson equation. Unlike previous Poisson equation solvers which try to converge to the accurate solution with iterative algorithms, we use biorthogonal compactly supported curl‐free wavelets as the fundamental bases to approximately project the composite gradient field onto a curl‐free vector space. Then, the composite can be efficiently recovered by applying a fast inverse wavelet transform. Considering an n‐pixel composite, our method only requires 2n of memory for all vector fields and is more efficient than state‐of‐the‐art methods while achieving almost identical results. Specifically, experiments show that our method gains a 5× speedup over the streaming multigrid in certain cases.     

Advection‐Based Function Matching on Surfaces

A tangent vector field on a surface is the generator of a smooth family of maps from the surface to itself, known as the flow. Given a scalar function on the surface, it can be transported, or advected, by composing it with a vector field's flow. Such transport is exhibited by many physical phenomena, e.g., in fluid dynamics. In this paper, we are interested in the inverse problem: given source and target functions, compute a vector field whose flow advects the source to the target. We propose a method for addressing this problem, by minimizing an energy given by the advection constraint together with a regularizing term for the vector field. Our approach is inspired by a similar method in computational anatomy, known as LDDMM, yet leverages the recent framework of functional vector fields for discretizing the advection and the flow as operators on scalar functions. The latter allows us to efficiently generalize LDDMM to curved surfaces, without explicitly computing the flow lines of the vector field we are optimizing for. We show two approaches for the solution: using linear advection with multiple vector fields, and using non‐linear advection with a single vector field. We additionally derive an approximated gradient of the corresponding energy, which is based on a novel vector field transport operator. Finally, we demonstrate applications of our machinery to intrinsic symmetry analysis, function interpolation and map improvement.     

A critical analysis of the “improved Clarke and Wright savings algorithm”

In their paper “An improved Clarke and Wright savings algorithm for the capacitated vehicle routing problem,” published in ScienceAsia (38, 3, 307–318, 2012), Pichpibul and Kawtummachai developed a simple stochastic extension of the well‐known Clarke and Wright savings heuristic for the capacitated vehicle routing problem. Notwithstanding the simplicity of the heuristic, which they call the “improved Clarke and Wright savings algorithm” (ICW), the reported results are among the best heuristics ever developed for this problem. Through a careful reimplementation, we demonstrate that the results published in the paper could not have been produced by the ICW heuristic. Studying the reasons how this paper could have passed the peer review process to be published in an ISI‐ranked journal, we have to conclude that the necessary conditions for a thorough examination of a typical paper in the field of optimization are generally lacking. We investigate how this can be improved and come to the conclusion that disclosing source code to reviewers should become a prerequisite for publication.     

Quad‐Based Fourier Transform for Efficient Diffraction Synthesis

Far‐field diffraction can be evaluated using the Discrete Fourier Transform (DFT) in image space but it is costly due to its dense sampling. We propose a technique based on a closed‐form solution of the continuous Fourier transform for simple vector primitives (quads) and propose a hierarchical and progressive evaluation to achieve real‐time performance. Our method is able to simulate diffraction effects in optical systems and can handle varying visibility due to dynamic light sources. Furthermore, it seamlessly extends to near‐field diffraction. We show the benefit of our solution in various applications, including realistic real‐time glare and bloom rendering.     

Large‐Scale Pixel‐Precise Deferred Vector Maps

Rendering vector maps is a key challenge for high‐quality geographic visualization systems. In this paper, we present a novel approach to visualize vector maps over detailed terrain models in a pixel‐precise way. Our method proposes a deferred line rendering technique to display vector maps directly in a screen‐space shading stage over the 3D terrain visualization. Due to the absence of traditional geometric polygonal rendering, our algorithm is able to outperform conventional vector map rendering algorithms for geographic information systems, and supports advanced line anti‐aliasing as well as slope distortion correction. Furthermore, our deferred line rendering enables interactively customizable advanced vector styling methods as well as a tool for interactive pixel‐based editing operations.     

Improved Corners with Multi‐Channel Signed Distance Fields

We propose an extension to the state‐of‐the‐art text rendering technique based on sampling a 2D signed distance field from a texture. This extension significantly improves the visual quality of sharp corners, which is the most problematic feature to reproduce for the original technique. We achieve this by using a combination of multiple distance fields in conjunction, which together provide a more thorough representation of the given glyph's (or any other 2D shape's) geometry. This multi‐channel distance field representation is described along with its application in shader‐based rendering. The rendering process itself remains very simple and efficient, and is fully compatible with previous monochrome distance fields. The introduced method of multi‐channel distance field construction requires a vector representation of the input shape. A comparative measurement of rendering quality shows that the error in the output image can be reduced by up to several orders of magnitude.     

Who are “stinkybug” and “Packerfan4”? Email Pseudonyms and Participants’ Perceptions of Demography,Productivity, and Personality

This study explores whether in the absence of face‐to‐face interaction individuals rely on mediated “clues” for constructing their perceptions of other individuals. Specifically, we assess whether individuals use the information in email usernames to create basic assumptions about the sender of a message. Ninety‐four male and 206 female participants completed self‐report surveys asking their perceptions of an instructor‐assigned, fictional group member including sex, age, race, and work productivity. A majority of participants assigned biological sex, ethnicity, and age to the fictional member. Participants often identified the creative emails as belonging to Caucasian males, while plain usernames were unknown and perceived as significantly more productive. The majority of participants chose to delete the message, listing lack of recognition as a reason for avoidance. These results suggest that email usernames may shape perceptions when other, nonverbal cues are absent.     

Designing N‐PolyVector Fields with Complex Polynomials

We introduce N‐PolyVector fields, a generalization of N‐RoSy fields for which the vectors are neither necessarily orthogonal nor rotationally symmetric. We formally define a novel representation for N‐PolyVectors as the root sets of complex polynomials and analyze their topological and geometric properties. A smooth N‐PolyVector field can be efficiently generated by solving a sparse linear system without integer variables. We exploit the flexibility of N‐PolyVector fields to design conjugate vector fields, offering an intuitive tool to generate planar quadrilateral meshes.     

Robust Reference Frame Extraction from Unsteady 2D Vector Fields with Convolutional Neural Networks

Robust feature extraction is an integral part of scientific visualization. In unsteady vector field analysis, researchers recently directed their attention towards the computation of near‐steady reference frames for vortex extraction, which is a numerically challenging endeavor. In this paper, we utilize a convolutional neural network to combine two steps of the visualization pipeline in an end‐to‐end manner: the filtering and the feature extraction. We use neural networks for the extraction of a steady reference frame for a given unsteady 2D vector field. By conditioning the neural network to noisy inputs and resampling artifacts, we obtain numerically stabler results than existing optimization‐based approaches. Supervised deep learning typically requires a large amount of training data. Thus, our second contribution is the creation of a vector field benchmark data set, which is generally useful for any local deep learning‐based feature extraction. Based on Vatistas velocity profile, we formulate a parametric vector field mixture model that we parameterize based on numerically‐computed example vector fields in near‐steady reference frames. Given the parametric model, we can efficiently synthesize thousands of vector fields that serve as input to our deep learning architecture. The proposed network is evaluated on an unseen numerical fluid flow simulation.     

Latest developments for “system‐on‐glass” displays using low‐temperature poly‐Si TFTs

Abstract— A 2.3‐in.‐diagonal QVGA‐formatted “System‐On‐Glass” display has been developed by using low‐temperature poly‐Si TFT‐LCD technology. This display fully integrates 6‐bit RGB digital interface drivers as well as all the power supply circuitry to drive the LCD, which requires neither external driver ICs nor power‐supply ICs. This paper discusses the newly developed TFT circuit technologies used in this LCD. The development trend of the “System‐On‐Glass” display is also reviewed.     

As‐Killing‐As‐Possible Vector Fields for Planar Deformation

Cartoon animation, image warping, and several other tasks in two‐dimensional computer graphics reduce to the formulation of a reasonable model for planar deformation. A deformation is a map from a given shape to a new one, and its quality is determined by the type of distortion it introduces. In many applications, a desirable map is as isometric as possible. Finding such deformations, however, is a nonlinear problem, and most of the existing solutions approach it by minimizing a nonlinear energy. Such methods are not guaranteed to converge to a global optimum and often suffer from robustness issues. We propose a new approach based on approximate Killing vector fields (AKVFs), first introduced in shape processing. AKVFs generate near‐isometric deformations, which can be motivated as direction fields minimizing an “as‐rigid‐as‐possible” (ARAP) energy to first order. We first solve for an AKVF on the domain given user constraints via a linear optimization problem and then use this AKVF as the initial velocity field of the deformation. In this way, we transfer the inherent nonlinearity of the deformation problem to finding trajectories for each point of the domain having the given initial velocities. We show that a specific class of trajectories — the set of logarithmic spirals — is especially suited for this task both in practice and through its relationship to linear holomorphic vector fields. We demonstrate the effectiveness of our method for planar deformation by comparing it with existing state‐of‐the‐art deformation methods.     

Interactive Exploratory Visualization of 2D Vector Fields

In this paper we present several techniques to interactively explore representations of 2D vector fields. Through a set of simple hand postures used on large, touch‐sensitive displays, our approach allows individuals to custom‐design glyphs (arrows, lines, etc.) that best reveal patterns of the underlying dataset. Interactive exploration of vector fields is facilitated through freedom of glyph placement, glyph density control, and animation. The custom glyphs can be applied individually to probe specific areas of the data but can also be applied in groups to explore larger regions of a vector field. Re‐positionable sources from which glyphs—animated according to the local vector field—continue to emerge are used to examine the vector field dynamically. The combination of these techniques results in an engaging visualization with which the user can rapidly explore and analyze varying types of 2D vector fields, using a virtually infinite number of custom‐designed glyphs.     

The State of the Art in Topology‐Based Visualization of Unsteady Flow

Vector fields are a common concept for the representation of many different kinds of flow phenomena in science and engineering. Methods based on vector field topology are known for their convenience for visualizing and analysing steady flows, but a counterpart for unsteady flows is still missing. However, a lot of good and relevant work aiming at such a solution is available. We give an overview of previous research leading towards topology‐based and topology‐inspired visualization of unsteady flow, pointing out the different approaches and methodologies involved as well as their relation to each other, taking classical (i.e. steady) vector field topology as our starting point. Particularly, we focus on Lagrangian methods, space–time domain approaches, local methods and stochastic and multifield approaches. Furthermore, we illustrate our review with practical examples for the different approaches.     

An Operator Approach to Tangent Vector Field Processing

In this paper, we introduce a novel coordinate‐free method for manipulating and analyzing vector fields on discrete surfaces. Unlike the commonly used representations of a vector field as an assignment of vectors to the faces of the mesh, or as real values on edges, we argue that vector fields can also be naturally viewed as operators whose domain and range are functions defined on the mesh. Although this point of view is common in differential geometry it has so far not been adopted in geometry processing applications. We recall the theoretical properties of vector fields represented as operators, and show that composition of vector fields with other functional operators is natural in this setup. This leads to the characterization of vector field properties through commutativity with other operators such as the Laplace‐Beltrami and symmetry operators, as well as to a straight‐forward definition of differential properties such as the Lie derivative. Finally, we demonstrate a range of applications, such as Killing vector field design, symmetric vector field estimation and joint design on multiple surfaces.     

On Typical Hesitant Fuzzy Prioritized “or” Operator in Multi‐Attribute Decision Making

Since hesitant fuzzy set was proposed, multi‐attribute decision making (MADM) with hesitant fuzzy information, which is also called hesitant fuzzy MADM, has been a hot research topic in decision theory. This paper investigates a special kind of hesitant fuzzy MADM problems in which the decision data are expressed by several possible values, and the evaluative attributes are in different priority levels. Firstly, we introduce the definitions of hesitant fuzzy t‐norm and t‐conorm by extending the notions of t‐norm and t‐conorm to the hesitant fuzzy environment and explore their constructions by means of t‐norms and t‐conorms. Then motivated by the prioritized “or” operator (R. R. Yager, Prioritized aggregation operators, International Journal of Approximate Reasoning 2008;48:263–274), we develop the typical hesitant fuzzy prioritized “or” operator based on the developed hesitant fuzzy t‐norms and t‐conorms. In this operator, the degree of satisfaction of each alternative in each priority level is derived from a hesitant fuzzy t‐conorm to preserve trade‐offs among the attributes in the same priority level, and the priority weights of attributes are induced by a hesitant fuzzy t‐norm to model the prioritization relationship among attributes. Furthermore, we apply the developed typical hesitant fuzzy prioritized “or” operator to solving the MADM problems in which the decision data are expressed by several possible values and the attributes are in different priority levels. In addition, two numerical examples are given to, respectively, illustrate the applicability and superiority of the developed aggregation operator by comparative analyses with previous research.     

“StoryWeb”: A storytelling‐based knowledge‐sharing application among multiple stakeholders

The research objective of this paper is to develop a storytelling‐based knowledge‐sharing application that enables users to co‐create their own stories for both individuals and groups. To address this, a design science research methodology was applied for elucidating users' requirements. As empirical evidence, a case study was conducted on the children's book industry to synthesize a knowledge‐sharing design application named “StoryWeb”. Usability tests were conducted to reconfigure users' feedback and suggestions after two StoryWeb prototypes were developed. This study makes three main contributions. First, it empirically tests individual's or group's creativity and co‐creation by a view of knowledge sharing. Second, it methodologically applies a design thinking approach into a knowledge‐sharing study. Third, it also practically suggests feasible guidelines for the creativity and innovation research community on which features of storytelling‐based applications can be configured.     

Designating “hot” items in multiple‐choice questions—A strategy for reviewing course materials

Suppose learners use their free time to go online to review course materials, and they do so by taking optional tests that consist of multiple‐choice questions (MCQs). What will happen if, for every practice question, there is always a choice (out of four possible choices) that is marked as “the (current) hot choice?” Will this make any difference in learning effects? To answer this question, an educational experiment was conducted. It was found that “hot designations” helped the experimental group perform significantly better in both the immediate post‐test exam and a delayed post‐test exam and that learners with higher levels of initial knowledge benefited more from this review strategy. From the results of a follow‐up questionnaire and one‐on‐one interviews, it was found that the proposed review strategy promoted a more thorough thinking style in subjects of the experimental group.