Relationship between phoria and visual fatigue in autostereoscopic 3D displays

Many people complain about visual fatigue arising from viewing three‐dimensional (3D) displays. This paper investigates relationship between visual fatigue and viewers' phoria for viewing autostereoscopic 3D displays. Visual fatigue is evaluated through subjective symptoms with a questionnaire and optometric indicators comprising fusion range as well as accommodation convergence/accommodation (AC/A) ratio to measure the variation in visual functions. A screening test is adopted to divide the subjects into two groups based on whether they suffer from phoria. Then a 2 × 2 × 2 mixed design experiment is conducted with display type, viewing stage, and visual state as factors to examine visual fatigue during viewing session. The results show that phoria subjects obtain more severe visual fatigue than normal on subjective evaluation. The normal subjects reveal a more marked difference with phoria in fusion range and AC/A ratio after viewing 3D video clip. Fusion range can significantly distinguish between the two‐dimensional (2D) and 3D condition as well as between the pre‐ and post‐viewing stages. The sensitivity and specificity of fusion range is higher than AC/A ratio with respect to viewing of 3D contents, so it is more appropriate as an optometric indicator of visual fatigue for autostereoscopic 3D displays.     

Compressive Image Reconstruction in Reduced Union of Subspaces

We present a new compressed sensing framework for reconstruction of incomplete and possibly noisy images and their higher dimensional variants, e.g. animations and light‐fields. The algorithm relies on a learning‐based basis representation. We train an ensemble of intrinsically two‐dimensional (2D) dictionaries that operate locally on a set of 2D patches extracted from the input data. We show that one can convert the problem of 2D sparse signal recovery to an equivalent 1D form, enabling us to utilize a large family of sparse solvers. The proposed framework represents the input signals in a reduced union of subspaces model, while allowing sparsity in each subspace. Such a model leads to a much more sparse representation than widely used methods such as K‐SVD. To evaluate our method, we apply it to three different scenarios where the signal dimensionality varies from 2D (images) to 3D (animations) and 4D (light‐fields). We show that our method outperforms state‐of‐the‐art algorithms in computer graphics and image processing literature.     

Orthogonal Array Sampling for Monte Carlo Rendering

We generalize N‐rooks, jittered, and (correlated) multi‐jittered sampling to higher dimensions by importing and improving upon a class of techniques called orthogonal arrays from the statistics literature. Renderers typically combine or “pad” a collection of lower‐dimensional (e.g. 2D and 1D) stratified patterns to form higher‐dimensional samples for integration. This maintains stratification in the original dimension pairs, but looses it for all other dimension pairs. For truly multi‐dimensional integrands like those in rendering, this increases variance and deteriorates its rate of convergence to that of pure random sampling. Care must therefore be taken to assign the primary dimension pairs to the dimensions with most integrand variation, but this complicates implementations. We tackle this problem by developing a collection of practical, in‐place multi‐dimensional sample generation routines that stratify points on all t‐dimensional and 1‐dimensional projections simultaneously. For instance, when t=2, any 2D projection of our samples is a (correlated) multi‐jittered point set. This property not only reduces variance, but also simplifies implementations since sample dimensions can now be assigned to integrand dimensions arbitrarily while maintaining the same level of stratification. Our techniques reduce variance compared to traditional 2D padding approaches like PBRT's (0,2) and Stratified samplers, and provide quality nearly equal to state‐of‐the‐art QMC samplers like Sobol and Halton while avoiding their structured artifacts as commonly seen when using a single sample set to cover an entire image. While in this work we focus on constructing finite sampling point sets, we also discuss potential avenues for extending our work to progressive sequences (more suitable for incremental rendering) in the future.     

A Framework for Exploring Multidimensional Data with 3D Projections

Visualization of high‐dimensional data requires a mapping to a visual space. Whenever the goal is to preserve similarity relations a frequent strategy is to use 2D projections, which afford intuitive interactive exploration, e.g., by users locating and selecting groups and gradually drilling down to individual objects. In this paper, we propose a framework for projecting high‐dimensional data to 3D visual spaces, based on a generalization of the Least‐Square Projection (LSP). We compare projections to 2D and 3D visual spaces both quantitatively and through a user study considering certain exploration tasks. The quantitative analysis confirms that 3D projections outperform 2D projections in terms of precision. The user study indicates that certain tasks can be more reliably and confidently answered with 3D projections. Nonetheless, as 3D projections are displayed on 2D screens, interaction is more difficult. Therefore, we incorporate suitable interaction functionalities into a framework that supports 3D transformations, predefined optimal 2D views, coordinated 2D and 3D views, and hierarchical 3D cluster definition and exploration. For visually encoding data clusters in a 3D setup, we employ color coding of projected data points as well as four types of surface renderings. A second user study evaluates the suitability of these visual encodings. Several examples illustrate the framework's applicability for both visual exploration of multidimensional abstract (non‐spatial) data as well as the feature space of multi‐variate spatial data.     

Parameter estimation of the 2D‐GTD model and RCS reconstruction based on an improved 2D‐ESPRIT algorithm

The two‐dimensional estimating signal parameter via rotational invariance techniques (2D‐ESPRIT) algorithm is a classical method to estimate parameters of the two‐dimensional geometric theory of diffraction (2D‐GTD) model. While as signal‐to‐noise‐ratio (SNR) decreases, the parameter estimation performance of 2D‐ESPRIT algorithm is severely influenced. To solve this problem, a performance‐enhanced 2D‐ESPRIT algorithm is proposed in this article. The improved 2D‐ESPRIT algorithm combines the conjugate data with the original back‐scattered data and obtains a novel covariance matrix by squaring the original total covariance matrix. Simulation results indicate that the improved algorithm has a better noise robustness and a more stable parameter estimation performance than the classical ESPRIT algorithm and the classical TLS‐2D‐ESPRIT algorithm. To further validate the superiority of the improved 2D‐ESPRIT algorithm, reconstructed radar cross section (RCS) is presented in this article. Compared with the classical 2D‐ESPRIT algorithm, the proposed algorithm presents higher RCS fitting precision. Furthermore, the impacts of other factors on parameter estimation, such as matrix pencil parameters and paring parameters, are also studied in this article.     

Curved OLED display to effectively enhance natural3D

We studied the stereoscopic effect obtained from a two‐dimensional image without using binocular parallax, which we call “natural3D” (n3D). Unlike a parallax‐based three‐dimensional (3D) display system, n3D causes less tiredness and is free from a decrease of the resolution by half because of image division and viewing position dependence. To make the display with these effects comfortable to use, we conducted statistical tests with sensory evaluation experiments and a quantitative evaluation based on physiological responses. These examinations revealed that the n3D effect can be effectively obtained by using, for example, the characteristics of an organic light‐emitting diode display, such as high contrast and easy bendability. This study discusses optimal display curvatures for displays of different sizes that enhance n3D and reduce tiredness, which are revealed through statistical tests. In addition, we performed an experiment with a frame called an n3D window (n3Dw) that is placed before the display such that a subject views the display through the opening of the frame. We found that the combination of a curve and the n3Dw causes n3D more effectively.     

3D palmprint recognition using shape index representation and fragile bits

Recent years have witnessed a growing interesting in developing automatic palmprint recognition methods. Most of the previous works have concentrated on two dimensional (2D) palmprint recognition in the past decade. However, the shape information is lost in 2D plamprint images. What’s more, 2D plamprint recognition is not robust enough in practice since its data could be easily counterfeited or contaminated by noise. Consequently, three dimensional (3D) palmprint recognition is treated as an important alternative road to both enhance the performance and robustness of current available palmprint recognition systems. In this paper, we first explore geometrical information of 3D palmprint data by employing shape index formulation, from which Gabor wavelet features are then extracted. Furthermore, we first discover that by incorporating fragile bits information, the performance of coding strategy related 3D recognition method can be further improved. Experiments conducted on the public available 3D plamprint database validate that our method can obtain the highest recognition performance among the state-of-the-art methods estimated.     

Coupled 3D master equation and 1D drift‐diffusion approach for advanced OLED modeling

A novel simulation approach for excitonic organic light‐emitting diodes (OLEDs) is established by combining a continuous one‐dimensional (1D) drift‐diffusion (DD) model for the charge carrier dynamics with a three‐dimensional (3D) master equation (ME) model describing the exciton dynamics in a multilayer OLED stack with an additional coupling to a thin‐film optics solver. This approach effectively combines the computational efficiency of the 1D DD solver with the physical accuracy of a discrete 3D ME model, where excitonic long‐range interactions for energy transfer can be taken into account. The coupling is established through different possible charge recombination types as well as the carrier densities themselves. We show that such a hybrid approach can efficiently and accurately describe steady‐state and transient behavior of optoelectronic devices reported in literature. Such a tool will facilitate the optimization and characterization of multilayer OLEDs and other organic semiconductor devices.     

摄像机旋转运动下的多帧图像对齐技术

针对传统旋转运动参数估计都是采用两帧图像对齐技术,提出了为多帧运动参数估计方法,即使用多帧子空间约束技术．证明了当摄像机参数不变时,多帧运动参数集合可嵌入一个低维线性子空间上;使用奇异值分解方法来降低线性子空间的秩,用最小二乘技术求解所有帧的运动参数．该方法不需要恢复任何3D信息;由于多帧参数估计法比两帧有更多的约束,因此取得更精确的图像对齐效果．该方法可用小图像进行参数估计．     

Soft Folding

We introduce soft folding, a new interactive method for designing and exploring thin‐plate forms. A user specifies sharp and soft folds as two‐dimensional(2D) curves on a flat sheet, along with the fold magnitude and sharpness of each. Then, based on the soft folds, the system computes the three‐dimensional(3D) folded shape. Internally, the system first computes a fold field, which defines local folding operations on a flat sheet. A fold field is a generalization of a discrete fold graph in origami, replacing a graph with sharp folds with a continuous field with soft folds. Next, local patches are folded independently according to the fold field. Finally, a globally folded 3D shape is obtained by assembling the locally folded patches. This algorithm computes an approximation of 3D developable surfaces with user‐defined soft folds at an interactive speed. The user can later apply nonlinear physical simulation to generate more realistic results. Experimental results demonstrated that soft folding is effective for producing complex folded shapes with controllable sharpness.     

MOEA/D + uniform design: A new version of MOEA/D for optimization problems with many objectives

To extend multiobjective evolutionary algorithm based on decomposition (MOEA/D) in higher dimensional objective spaces, this paper proposes a new version of MOEA/D with uniform design, named the uniform design multiobjective evolutionary algorithm based on decomposition (UMOEA/D), and compares the proposed algorithm with MOEA/D and NSGA-II on some scalable test problems with three to five objectives. UMOEA/D adopts the uniform design method to set the aggregation coefficient vectors of the subproblems. Compared with MOEA/D, distribution of the coefficient vectors is more uniform over the design space, and the population size neither increases nonlinearly with the number of objectives nor considers a formulaic setting. The experimental results indicate that UMOEA/D outperforms MOEA/D and NSGA-II on almost all these many-objective test instances, especially on problems with higher dimensional objectives and complicated Pareto set shapes. Experimental results also show that UMOEA/D runs faster than NSGA-II for the problems used in this paper. In additional, the results obtained are very competitive when comparing UMOEA/D with some other algorithm on the multiobjective knapsack problems.     

Applying Visual Analytics to Physically Based Rendering

Physically based rendering is a well‐understood technique to produce realistic‐looking images. However, different algorithms exist for efficiency reasons, which work well in certain cases but fail or produce rendering artefacts in others. Few tools allow a user to gain insight into the algorithmic processes. In this work, we present such a tool, which combines techniques from information visualization and visual analytics with physically based rendering. It consists of an interactive parallel coordinates plot, with a built‐in sampling‐based data reduction technique to visualize the attributes associated with each light sample. Two‐dimensional (2D) and three‐dimensional (3D) heat maps depict any desired property of the rendering process. An interactively rendered 3D view of the scene displays animated light paths based on the user's selection to gain further insight into the rendering process. The provided interactivity enables the user to guide the rendering process for more efficiency. To show its usefulness, we present several applications based on our tool. This includes differential light transport visualization to optimize light setup in a scene, finding the causes of and resolving rendering artefacts, such as fireflies, as well as a path length contribution histogram to evaluate the efficiency of different Monte Carlo estimators.     

Four‐Dimensional Geometry Lens: A Novel Volumetric Magnification Approach

We present a novel methodology that utilizes four‐dimensional (4D) space deformation to simulate a magnification lens on versatile volume datasets and textured solid models. Compared with other magnification methods (e.g. geometric optics, mesh editing), 4D differential geometry theory and its practices are much more flexible and powerful for preserving shape features (i.e. minimizing angle distortion), and easier to adapt to versatile solid models. The primary advantage of 4D space lies at the following fact: we can now easily magnify the volume of regions of interest (ROIs) from the additional dimension, while keeping the rest region unchanged. To achieve this primary goal, we first embed a 3D volumetric input into 4D space and magnify ROIs in the fourth dimension. Then we flatten the 4D shape back into 3D space to accommodate other typical applications in the real 3D world. In order to enforce distortion minimization, in both steps we devise the high‐dimensional geometry techniques based on rigorous 4D geometry theory for 3D/4D mapping back and forth to amend the distortion. Our system can preserve not only focus region, but also context region and global shape. We demonstrate the effectiveness, robustness and efficacy of our framework with a variety of models ranging from tetrahedral meshes to volume datasets.     

3D shape recovery from image focus using kernel regression in eigenspace

Shape from focus (SFF) is one of the optical passive methods for three dimensional (3D) shape recovery of an object from its two dimensional (2D) images. The focus measure plays important role in SFF algorithms. Mostly, conventional focus measures are based on gradient, so their performance is restricted under noisy conditions. Moreover, SFF methods also suffer from loss of focus information due to discreteness. This paper introduces a new SFF method based on principal component analysis (PCA) and kernel regression. The focus values are computed through PCA by considering a sequence of small 3D neighborhood for each object point. We apply unsupervised regression through Nadaraya and Watson Estimate (NWE) on depth values to get a refined 3D shape of the object. It reduces the effect of noise within a small surface area as well as approximates the accurate 3D shape by exploiting the depth dependencies in the neighborhood. Performance of the proposed scheme is investigated in the presence of different types of noises and textured areas. Experimental results demonstrate effectiveness of the proposed approach.     

Three dimensional numerical simulations of long-span bridge aerodynamics, using block-iterative coupling and DES

The design of long-span bridges often depends on wind tunnel testing of sectional or full aeroelastic models. Some progress has been made to find a computational alternative to replace these physical tests. In this paper, an innovative computational fluid dynamics (CFD) method is presented, where the fluid-structure interaction (FSI) is solved through a self-developed code combined with an ANSYS-CFX solver. Then an improved CFD method based on block-iterative coupling is also proposed. This method can be readily used for two dimensional (2D) and three dimensional (3D) structure modelling. Detached-Eddy simulation for 3D viscous turbulent incompressible flow is applied to the 3D numerical analysis of bridge deck sections. Firstly, 2D numerical simulations of a thin airfoil demonstrate the accuracy of the present CFD method. Secondly, numerical simulations of a U-shape beam with both 2D and 3D modelling are conducted. The comparisons of aerodynamic force coefficients thus obtained with wind tunnel test results well meet the prediction that 3D CFD simulations are more accurate than 2D CFD simulations. Thirdly, 2D and 3D CFD simulations are performed for two generic bridge deck sections to produce their aerodynamic force coefficients and flutter derivatives. The computed values agree well with the available computational and wind tunnel test results. Once again, this demonstrates the accuracy of the proposed 3D CFD simulations. Finally, the 3D based wake flow vision is captured, which shows another advantage of 3D CFD simulations. All the simulation results demonstrate that the proposed 3D CFD method has good accuracy and significant benefits for aerodynamic analysis and computational FSI studies of long-span bridges and other slender structures.     

Robust stabilization of nonlinear stochastic 2‐D systems: LaSalle‐type theorem approach

LaSalle theorem (also known as the LaSalle invariance principle) plays an essential role in the systems and control theory. Recently, it has been extensively studied and developed for various types of one‐dimensional (1‐D) systems including deterministic and stochastic 1‐D systems in discrete‐ and continuous‐time domains. For two‐dimensional (2‐D) systems, such studies have received considerably less attention. In this article, based on discrete martingale theory, a LaSalle‐type theorem is first developed for a class of discrete‐time nonlinear stochastic 2‐D systems described by a Roesser model. The proposed result can be regarded as an extension of stochastic Lyapunov‐like theorem, which guarantees the convergence almost surely of system state trajectories. Extensions to the problem of optimal guaranteed cost control of nonlinear stochastic 2‐D systems are also presented. The proposed schemes are then utilized to derive tractable synthesis conditions of a suboptimal state‐feedback controller for uncertain 2‐D systems with multiplicative stochastic noises. The effectiveness of the obtained results is illustrated by given numerical examples and simulations.     

Visualization of 3‐D computer‐aided design objects

There are many significant human factors issues associated with the design and visualization of complex, computer‐generated images. One such issue is to determine the most effective techniques for providing engineers with realistic three‐dimensional (3‐D) objects. Differences in subjects’ ability to discriminate between the shape of two 3‐D, perspective, computer‐aided design‐type (CAD‐type) objects were investigated for various levels of monocular coding techniques and the binocular cue stereopsis. Performance was assessed at all combinations of five levels of monocular cues and two levels of disparity. The task was similar to the classic mental rotation paradigm except that subjects were provided with the ability to rotate one of the objects using a two‐dimensional (2‐D) joystick. Results indicate that interposition was the only depth cue that significantly enhanced subject performance. One explanation for the lack of significance of stereopsis is that, for this particular task, depth information provided by disparity was not needed. Detailed analysis of object rotation data using an orientation index (OI) suggests that subjects employed a feature‐by‐feature comparison task strategy. With tools that can evaluate cognitive activity such as the mental rotation paradigm and orientation index, researchers can learn more about how designers visualize and understand 3‐D CAD objects.     

Sketch‐Based Editing Tools for Tumour Segmentation in 3D Medical Images

In the past years sophisticated automatic segmentation algorithms for various medical image segmentation problems have been developed. However, there are always cases where automatic algorithms fail to provide an acceptable segmentation. In these cases the user needs efficient segmentation editing tools, a problem which has not received much attention in research. We give a comprehensive overview on segmentation editing for three‐dimensional (3D) medical images. For segmentation editing in two‐dimensional (2D) images, we discuss a sketch‐based approach where the user modifies the segmentation in the contour domain. Based on this 2D interface, we present an image‐based as well as an image‐independent method for intuitive and efficient segmentation editing in 3D in the context of tumour segmentation in computed tomography (CT). Our editing tools have been evaluated on a database containing 1226 representative liver metastases, lung nodules and lymph nodes of different shape, size and image quality. In addition, we have performed a qualitative evaluation with radiologists and technical experts, proving the efficiency of our tools.     

A high optical efficiency 3D/2D convertible integral imaging display

We propose a high optical efficiency three‐dimensional (3D)/two‐dimensional (2D) convertible integral imaging display by using a pinhole array on a reflective polarizer. The 3D mode is realized by adopting a pinhole array on a reflective polarizer to generate a point light source array. Three‐dimensional/2D convertible feature is realized by electrically controlling a polarization switcher. The reflective polarizer can reflect the light that has the orthogonal polarization direction with the reflective polarizer and transmit the light that has the same polarization direction with the reflective polarizer. The reflected light is recycled, so the optical efficiencies for both 3D and 2D modes are enhanced. In the practical experiments, the optical efficiencies of the proposed integral imaging display increase by 8.04 times and 1.65 times in 3D and 2D modes comparing with the conventional integral imaging display that has no light recycle, respectively.     

A 2D–3D integrated tabletop environment for multi‐user collaboration

This paper proposes a novel tabletop display system for natural communication and flexible information sharing. The proposed system is specifically designed to integrate two‐dimensional (2D) and three‐dimensional (3D) user interfaces by using a multi‐user stereoscopic display, IllusionHole. The proposed system takes awareness into consideration and provides both 2D and 3D information and user interfaces. On the display, a number of standard Windows desktop environments are provided as personal workspaces, as well as a shared workspace with a dedicated graphical user interface. In the personal workspaces, users can simultaneously access existing applications and data, and exchange information between personal and shared workspaces. In this way, the proposed system can seamlessly integrate personal, shared, 2D, and 3D workspaces with conventional user interfaces and effectively support communication and information sharing. To demonstrate the capabilities of the proposed display system, a modeling application was implemented. A preliminary experiment confirmed the effectiveness of this system. Copyright © 2006 John Wiley & Sons, Ltd.