Smart monopole antenna with pattern and frequency reconfiguration characteristics based on programmable metasurface

Metasurfaces having ultrathin and planar structure with sub‐wavelength unit cell, have recently gained significant potential for use thanks to their control capabilities over the electromagnetic waves from microwave to the visible range. The structure and the dimensions of the sub‐wavelength elements determine the electromagnetic properties, capabilities, and functionalities of the metasurfaces providing a full control of the reflected and transmitted fields and these metasurfaces are referred to as analog metasurfaces. When adjustability is added to the unit cells, programmable or digital metasurfaces are obtained, allowing us to take multiple unique functionality advantages controlled by external stimuli. In this study, we propose a metasurface structure, also known as 1‐bit coding metasurface, which is controlled depending on the “On/Off” state. The “On/Off” state is controlled by a computer program using genetical algorithm. Depending on the operating state, electromagnetic waves can be manipulated and different functionalities of the metasurfaces can be realized. The contribution and innovation of the study is the demonstration of the beam rotation, resonance frequency shift and radiation pattern reconfiguration properties of a simple monopole antenna by using controllable metasurface composed of T shaped resonator and circular patch with an operating frequency between 4.3 and 5.6 GHz.     

Physically Meaningful Rendering using Tristimulus Colours

In photorealistic image synthesis the radiative transfer equation is often not solved by simulating every wavelength of light, but instead by computing tristimulus transport, for instance using sRGB primaries as a basis. This choice is convenient, because input texture data is usually stored in RGB colour spaces. However, there are problems with this approach which are often overlooked or ignored. By comparing to spectral reference renderings, we show how rendering in tristimulus colour spaces introduces colour shifts in indirect light, violation of energy conservation, and unexpected behaviour in participating media. Furthermore, we introduce a fast method to compute spectra from almost any given XYZ input colour. It creates spectra that match the input colour precisely. Additionally, like in natural reflectance spectra, their energy is smoothly distributed over wide wavelength bands. This method is both useful to upsample RGB input data when spectral transport is used and as an intermediate step for corrected tristimulus‐based transport. Finally, we show how energy conservation can be enforced in RGB by mapping colours to valid reflectances.     

A New Ward BRDF Model with Bounded Albedo

Due to its realistic appearance, computational convenience, and efficient Monte Carlo sampling, Ward's anisotropic BRDF is widely used in computer graphics for modeling specular reflection. Incorporating the criticism that the Ward and the Ward‐Dür model do not meet energy balance at grazing angles, we propose a modified BRDF that is energy conserving and preserves Helmholtz reciprocity. The new BRDF is computationally cheap to evaluate, admits efficient importance sampling, and thus sustains the main benefits of the Ward model. We show that the proposed BRDF is better suited for fitting measured reflectance data of a linoleum floor used in a real‐world building than the Ward and the Ward‐Dür model.     

An Image‐Based Approach for Stochastic Volumetric and Procedural Details

Noisy volumetric details like clouds, grounds, plaster, bark, roughcast, etc. are frequently encountered in nature and bring an important contribution to the realism of outdoor scenes. We introduce a new interactive approach, easing the creation of procedural representations of “stochastic” volumetric details by using a single example photograph. Instead of attempting to reconstruct an accurate geometric representation from the photograph, we use a stochastic multi‐scale approach that fits parameters of a multi‐layered noise‐based 3D deformation model, using a multi‐resolution filter banks error metric. Once computed, visually similar details can be applied to arbitrary objects with a high degree of visual realism, since lighting and parallax effects are naturally taken into account. Our approach is inspired by image‐based techniques. In practice, the user supplies a photograph of an object covered by noisy details, provides a corresponding coarse approximation of the shape of this object as well as an estimated lighting condition (generally a light source direction). Our system then determines the corresponding noise‐based representation as well as some diffuse, ambient, specular and semi‐transparency reflectance parameters. The resulting details are fully procedural and, as such, have the advantage of extreme compactness, while they can be infinitely extended without repetition in order to cover huge surfaces.     

Computer‐Suggested Facial Makeup

Finding the best makeup for a given human face is an art in its own right. Experienced makeup artists train for years to be skilled enough to propose a best‐fit makeup for an individual. In this work we propose a system that automates this task. We acquired the appearance of 56 human faces, both without and with professional makeup. To this end, we use a controlled‐light setup, which allows to capture detailed facial appearance information, such as diffuse reflectance, normals, subsurface‐scattering, specularity, or glossiness. A 3D morphable face model is used to obtain 3D positional information and to register all faces into a common parameterization. We then define makeup to be the change of facial appearance and use the acquired database to find a mapping from the space of human facial appearance to makeup. Our main application is to use this mapping to suggest the best‐fit makeup for novel faces that are not in the database. Further applications are makeup transfer, automatic rating of makeup, makeup‐training, or makeup‐exaggeration. As our makeup representation captures a change in reflectance and scattering, it allows us to synthesize faces with makeup in novel 3D views and novel lighting with high realism. The effectiveness of our approach is further validated in a user‐study.     

Intrinsic Decompositions for Image Editing

Intrinsic images are a mid‐level representation of an image that decompose the image into reflectance and illumination layers. The reflectance layer captures the color/texture of surfaces in the scene, while the illumination layer captures shading effects caused by interactions between scene illumination and surface geometry. Intrinsic images have a long history in computer vision and recently in computer graphics, and have been shown to be a useful representation for tasks ranging from scene understanding and reconstruction to image editing. In this report, we review and evaluate past work on this problem. Specifically, we discuss each work in terms of the priors they impose on the intrinsic image problem. We introduce a new synthetic ground‐truth dataset that we use to evaluate the validity of these priors and the performance of the methods. Finally, we evaluate the performance of the different methods in the context of image‐editing applications.     

Characteristic Point Maps

Extremely dense spatial sampling is often needed to prevent aliasing when rendering objects with high frequency variations in geometry and reflectance. To accelerate the rendering process, we introduce characteristic point maps (CPMs), a hierarchy of view-independent points, which are chosen to preserve the appearance of the original model across different scales. In preprocessing, randomized matrix column sampling is used to reduce an initial dense sampling to a minimum number of characteristic points with associated weights. In rendering, the reflected radiance is computed using a weighted average of reflectances from characteristic points. Unlike existing techniques, our approach requires no restrictions on the original geometry or reflectance functions.     

Near‐Instant Capture of High‐Resolution Facial Geometry and Reflectance

We present a near‐instant method for acquiring facial geometry and reflectance using a set of commodity DSLR cameras and flashes. Our setup consists of twenty‐four cameras and six flashes which are fired in rapid succession with subsets of the cameras. Each camera records only a single photograph and the total capture time is less than the 67ms blink reflex. The cameras and flashes are specially arranged to produce an even distribution of specular highlights on the face. We employ this set of acquired images to estimate diffuse color, specular intensity, specular exponent, and surface orientation at each point on the face. We further refine the facial base geometry obtained from multi‐view stereo using estimated diffuse and specular photometric information. This allows final submillimeter surface mesostructure detail to be obtained via shape‐from‐specularity. The final system uses commodity components and produces models suitable for authoring high‐quality digital human characters.     

Towards Perceptual Simplification of Models with Arbitrary Materials

Real‐time rendering of models with high polygon count is still an important issue in interactive computer graphics. A common way to improve rendering performance is to generate different levels of detail of a model. These are mostly computed using polygonal simplification techniques, which aim to reduce the number of polygons without significant loss of visual fidelity. Most existing algorithms use geometric error bounds, which are well‐suited for silhouette preservation. They ignore the fact that a much more aggressive simplification is possible in low‐contrast areas inside the model. The main contribution of this paper is an efficient simplification algorithm based on the human visual system. The key idea is to move the domain of error computation from image‐space to vertex‐space to avoid a costly per‐pixel comparison. This way the error estimation of a simplification operation can be accelerated significantly. To account for the human vision, we introduce a perceptually based metric depending on the contrast and spatial frequency of the model at a single vertex. Finally, we validate our approach with a user study.     

Stereo Light Probe

In this paper we present a practical, simple and robust method to acquire the spatially‐varying illumination of a real‐world scene. The basic idea of the proposed method is to acquire the radiance distribution of the scene using high‐dynamic range images of two reflective balls. The use of two light probes instead of a single one allows to estimate, not only the direction and intensity of the light sources, but also the actual position in space of the light sources. To robustly achieve this goal we first rectify the two input spherical images, then, using a region‐based stereo matching algorithm, we establish correspondences and compute the position of each light. The radiance distribution so obtained can be used for augmented reality applications, photo‐realistic rendering and accurate reflectance properties estimation. The accuracy and the effectiveness of the method have been tested by measuring the computed light position and rendering synthetic version of a real object in the same scene. The comparison with standard method that uses a simple spherical lighting environment is also shown.     

Pre‐convolved Radiance Caching

The incident indirect light over a range of image pixels is often coherent. Two common approaches to exploit this inter‐pixel coherence to improve rendering performance are Irradiance Caching and Radiance Caching. Both compute incident indirect light only for a small subset of pixels (the cache), and later interpolate between pixels. Irradiance Caching uses scalar values that can be interpolated efficiently, but cannot account for shading variations caused by normal and reflectance variation between cache items. Radiance Caching maintains directional information, e.g., to allow highlights between cache items, but at the cost of storing and evaluating a Spherical Harmonics (SH) function per pixel. The arithmetic and bandwidth cost for this evaluation is linear in the number of coefficients and can be substantial. In this paper, we propose a method to replace it by an efficient per‐cache item pre‐filtering based on MIP maps — such as previously done for environment maps — leading to a single constant‐time lookup per pixel. Additionally, per‐cache item geometry statistics stored in distance‐MIP maps are used to improve the quality of each pixel's lookup. Our approximate interactive global illumination approach is an order of magnitude faster than Radiance Caching with Phong BRDFs and can be combined with Monte Carlo‐raytracing, Point‐based Global Illumination or Instant Radiosity.     

汽车组合仪表有意电磁干扰空时域联合分离系统设计

有意电磁波与汽车仪器电磁传输波产生的混合干扰,降低了汽车组合仪表的稳定运行能力,造成仪表设备失灵。为避免上述情况的发生,设计汽车组合仪表有意电磁干扰空时域联合分离系统。在步进电机驱动电路中,设置汽车组合仪表控制器、分离电源与 PCB 电路板、有意电磁干扰数字传感器。分配有意电磁波空时域源地址,通过计算干扰信号平坦度的方式,确定脉冲参数的取值范围,实现汽车组合仪表有意电磁的空时域干扰效应分析。估算有意电磁波干扰信号的数目,按照信号分解的处理原则,求解联合分离修正函数,实现电磁干扰的联合分离。实验结果表明,设计系统应用后可以在混合信号中,按照空域、时域标准的不同分离有意电磁波,不会因混合干扰降低汽车组合仪表的稳定运行能力。     

BendyLights: Artistic Control of Direct Illumination by Curving Light Rays

In computer cinematography, artists routinely use non‐physical lighting models to achieve desired appearances. This paper presents BendyLights, a non‐physical lighting model where light travels nonlinearly along splines, allowing artists to control light direction and shadow position at different points in the scene independently. Since the light deformation is smoothly defined at all world‐space positions, the resulting non‐physical lighting effects remain spatially consistent, avoiding the frequent incongruences of many non‐physical models. BendyLights are controlled simply by reshaping splines, using familiar interfaces, and require very few parameters. BendyLight control points can be keyframed to support animated lighting effects. We demonstrate BendyLights both in a realtime rendering system for editing and a production renderer for final rendering, where we show that BendyLights can also be used with global illumination.     

Seamless Montage for Texturing Models

We present an automatic method to recover high‐resolution texture over an object by mapping detailed photographs onto its surface. Such high‐resolution detail often reveals inaccuracies in geometry and registration, as well as lighting variations and surface reflections. Simple image projection results in visible seams on the surface. We minimize such seams using a global optimization that assigns compatible texture to adjacent triangles. The key idea is to search not only combinatorially over the source images, but also over a set of local image transformations that compensate for geometric misalignment. This broad search space is traversed using a discrete labeling algorithm, aided by a coarse‐to‐fine strategy. Our approach significantly improves resilience to acquisition errors, thereby allowing simple and easy creation of textured models for use in computer graphics.     

Path‐space Motion Estimation and Decomposition for Robust Animation Filtering

Renderings of animation sequences with physics‐based Monte Carlo light transport simulations are exceedingly costly to generate frame‐by‐frame, yet much of this computation is highly redundant due to the strong coherence in space, time and among samples. A promising approach pursued in prior work entails subsampling the sequence in space, time, and number of samples, followed by image‐based spatio‐temporal upsampling and denoising. These methods can provide significant performance gains, though major issues remain: firstly, in a multiple scattering simulation, the final pixel color is the composite of many different light transport phenomena, and this conflicting information causes artifacts in image‐based methods. Secondly, motion vectors are needed to establish correspondence between the pixels in different frames, but it is unclear how to obtain them for most kinds of light paths (e.g. an object seen through a curved glass panel). To reduce these ambiguities, we propose a general decomposition framework, where the final pixel color is separated into components corresponding to disjoint subsets of the space of light paths. Each component is accompanied by motion vectors and other auxiliary features such as reflectance and surface normals. The motion vectors of specular paths are computed using a temporal extension of manifold exploration and the remaining components use a specialized variant of optical flow. Our experiments show that this decomposition leads to significant improvements in three image‐based applications: denoising, spatial upsampling, and temporal interpolation.     

Mixing Fluids and Granular Materials

Fluid animations in computer graphics show interactions with various kinds of objects. However, fluid flowing through a granular material such as sand is still not possible within current frameworks. In this paper, we present the simulation of fine granular materials interacting with fluids. We propose a unified Smoothed Particle Hydrodynamics framework for the simulation of both fluid and granular material. The granular volume is simulated as a continuous material sampled by particles. By incorporating previous work on porous flow in this simulation framework we are able to fully couple fluid and sand. Fluid can now percolate between sand grains and influence the physical properties of the sand volume. Our method demonstrates various new effects such as dry soil transforming into mud pools by rain or rigid sand structures being eroded by waves.     

Product Importance Sampling for Light Transport Path Guiding

The efficiency of Monte Carlo algorithms for light transport simulation is directly related to their ability to importance‐sample the product of the illumination and reflectance in the rendering equation. Since the optimal sampling strategy would require knowledge about the transport solution itself, importance sampling most often follows only one of the known factors – BRDF or an approximation of the incident illumination. To address this issue, we propose to represent the illumination and the reflectance factors by the Gaussian mixture model (GMM), which we fit by using a combination of weighted expectation maximization and non‐linear optimization methods. The GMM representation then allows us to obtain the resulting product distribution for importance sampling on‐the‐fly at each scene point. For its efficient evaluation and sampling we preform an up‐front adaptive decimation of both factor mixtures. In comparison to state‐of‐the‐art sampling methods, we show that our product importance sampling can lead to significantly better convergence in scenes with complex illumination and reflectance.     

On the Effective Dimension of Light Transport

Light transport is often characterized within a high‐dimensional space although practitioners have long known that it commonly behaves as a much lower‐dimensional phenomenon. We study the effective dimension of light transport over a neighborhood on the scene manifold and show that under plausible assumptions the dimensionality is characterized by the spectrum of the spatio‐spectral concentration problem. This allows us to improve existing estimates for the dimension in computer graphics using a more insightful derivation and for the first time we obtain optimal representations. The relevance of our results for existing rendering applications is discussed.     

Acquisition, Synthesis, and Rendering of Bidirectional Texture Functions

One of the main challenges in computer graphics is still the realistic rendering of complex materials such as fabric or skin. The difficulty arises from the complex meso structure and reflectance behavior defining the unique look‐and‐feel of a material. A wide class of such realistic materials can be described as 2D‐texture under varying light‐ and view direction, namely, the Bidirectional Texture Function (BTF). Since an easy and general method for modeling BTFs is not available, current research concentrates on image‐based methods, which rely on measured BTFs (acquired real‐world data) in combination with appropriate synthesis methods. Recent results have shown that this approach greatly improves the visual quality of rendered surfaces and therefore the quality of applications such as virtual prototyping. This state‐of‐the‐art report (STAR) will present the techniques for the main tasks involved in producing photo‐realistic renderings using measured BTFs in details.     

An Energy‐Conserving Hair Reflectance Model

We present a reflectance model for dielectric cylinders with rough surfaces such as human hair fibers. Our model is energy conserving and can evaluate arbitrarily many orders of internal reflection. Accounting for compression and contraction of specular cones produces a new longitudinal scattering function which is non‐Gaussian and includes an off‐specular peak. Accounting for roughness in the azimuthal direction leads to an integral across the hair fiber which is efficiently evaluated using a Gaussian quadrature. Solving cubic equations is avoided, caustics are included in the model in a consistent fashion, and more accurate colors are predicted by considering many internal pathways.