基于动态Light Map的增强现实光照算法

为实现增强现实系统中光照的实时准确性,提出一种基于动态Light Map的快速光照算法。该方法通过采集视频图像中校准物体的像素亮度,计算出摄像机的信号放大量和信号偏置,并利用动态更新的Light Map所记录的环境光照信息实现虚、实场景之间的一致光照,且能够适应光照变化的场景。实验结果表明该算法的显示速度能够达到实时交互的帧率。     

基于级联体素纹理的VCT全局光照算法

针对大规模场景的全局光照渲染往往因为计算量过大而无法满足实时性要求的问题进行了研究,提出一种高性能的体素圆锥追踪（VCT）全局光照算法。算法包括：a）在体素化阶段,提出一种新型的场景光照信息表示级联体素纹理结构,该结构极大地减少了存储场景的内存消耗而且具有各向异性,在处理大规模场景时具有速度快、质量高的优势;b）在光照计算阶段,基于级联体素纹理结构提出一种改进的圆锥追踪滤波器,能够提高光照注入和反射光计算的效率;c）改进场景的体素化更新策略进一步提高了算法的运行时帧率。实验证明,本算法在降低内存占用空间和提高速度方面均远优于原VCT算法,满足了大规模场景中全局光照计算的实时性要求。     

Phong明暗处理方法的探讨与改进

明暗处理是图形真实感处理的重要内容。物体明暗效果的模拟以光照模型为数学基础,通过不同算法模拟光照射在物体上的反射,透射等效果。文章以Phong局部光照模型为基础,分别用Gouraud方法和Phong方法实现了正方体单点光源光照模型,分析对比了两种方法的缺陷,在此基础上提出了P－G方法,成功模拟了多边形内部的高光并使光强度变化层次均匀。     

基于上下文Transformer的低光照图像增强网络

由于现实环境中明暗光照的剧烈变化,现有的低光照图像增强方法往往会导致增强后的图像亮度和对比度不足,出现伪影和模糊等情况。此外,当前的低光照图像增强工作仅针对于图像亮度的提升,而对于噪声影响的处理较少,这些都不利于低光图像的增强。为了解决上述问题,论文提出了一种基于上下文Transformer的低光照图像增强算法。具体地,论文首先利用动态卷积网络对低光照图像进行特征提取;接着,设计了上下文Transformer对得到的特征图进行全局关联的深层特征提取,并使用金字塔池化模块进行去噪处理;最后,通过瓶颈结构的卷积网络输出得到增强后的图像。在多个主流数据集（LOL,LIME,DICM等）上的对比实验结果表明,与目前已有的主流工作相比,论文所提方法的结果不仅在主观视觉上有更好的视觉效果,更加符合人眼的视觉特点;而且在各种定量客观评价指标上也有良好的表现,尤其在PSNR和SSIM两个指标上有明显的提升。     

一种面向分布式虚拟环境的分层迭代负载平衡算法

为了支持大规模用户共享虚拟环境,多服务器结构被应用到分布式虚拟环境系统中,每个服务器负责虚拟环境的一个区域划分.由于用户不可预知的移动和交互,可能会导致某些服务器负载过重.现有的负载平衡算法注重于将负载在服务器间重分配,但引入开销过大,影响系统交互性能.提出一种分层迭代的动态负载平衡算法,以过载区域为中心,分层地选择周围有限数量的区域作为调整目标,将过载部分由内向外迭代地扩散到各层,多次迭代达到负载平衡状态.针对倾斜和聚簇两种典型用户分布的虚拟环境,对算法进行验证并与现有的3种负载平衡算法进行比较.结果表明,该算法可以快速、有效地调整负载并引入较少的开销.     

基于OpenGL的光照处理技术及实现

光照处理是增强图形真实感最重要的组成部分,包括光照模型的选择和明暗处理.通过研究影响物体表面反射光的相关因素,提出了真实感图形绘制中如何进行模拟光照计算和明暗插值计算的问题.在分析和研究OpenGL图形库下实现光照效果的改善,并系统地阐述了利用OpenGL函数在VC 环境下实现光照图形的基本过程和方法.最后在计算机设备上实例绘制了不同光照处理方法下的对比图形,显示出了真实感光照的效果,同时具有一定的使用指导意义.     

复杂环境光源下虚实融合光照实时计算

在互动电子游戏、增强现实等对实时计算要求很高的交互式图形应用中,大量使用复杂环境光源对虚拟物体进行照明,使其和真实场景的光照一致,虚实融合.提出了用Cook Torrance光照模型进行虚实场景的光照计算;利用球面调和基函数的方法,实时地计算高动态范围环境映射光照系数,得到高动态范围环境映射的二次多项式表达形式,在着色器计算该式得到漫反射分量;通过环境映射技术对镜面反射进行模拟,全部光照计算在GPU中完成.实验结果表明,该方法在动态变化的复杂环境光源下,完成对虚拟物体光照实时计算,绘制速度每秒30帧以上,绘制结果具有较强的真实感.     

大规模三维云实时模拟方法

针对虚拟环境中大规模三维云渲染开销大的问题,提出一种大规模三维云实时模拟方法.在云建模方面,利用Navier-Stokes流体力学公式模拟云的动态生成,提出一种基于八叉树的模型化简策略,减少了云模型粒子数;在渲染阶段,提出一种基于Cell的绘制更新策略,结合Impostor技术自动混合绘制三维云与Impostor,实现了大规模三维云的实时模拟.实验结果表明,该方法基于物理的方法模拟云,同时在绘制阶段根据视点的移动实时更新,效果逼真;与同类方法相比,基于Cell的绘制策略更新时计算量更小,有效地避免了绘制更新时常见的抖动和跳变问题.     

异步DVE系统中生命周期约束下的因果一致性控制方法研究

分布式虚拟环境是模拟现实世界的虚拟空间,对因果一致性控制具有实时性要求,必须在事件生命周期结束前得到维护.然而,在大规模网络条件下,网络传输高延迟和动态性会导致部分事件不能及时到达,使已传到事件间因果关系无法在生命周期限制内有效传递.在现有方法中,部分方法基于所有事件一定能及时传到的假设,没有考虑生命周期对因果关系的制约;而另一部分方法虽然考虑了生命周期的约束,但其因果关系传递要求仿真时钟精确同步,且因果控制效率随系统规模的扩大而快速降低,限制了虚拟环境的普适性和实时性.提出了生命周期约束下的因果一致性控制方法LCO,突破了异步时钟间的时间值比较、多路径因果控制信息选择的终止条件、网络状况敏感的因果控制信息动态调节等关键技术,能够在事件无法及时传到时,仍可以根据已传到的事件计算出因果传递关系.实验证明,LCO既能维护生命周期内的因果一致性,又使因果控制信息量与系统规模无关,降低网络传输和计算开销.     

一种低管理开销的网格计算模型

针对利用Internet上大量空闲计算资源来解决大规模分布式计算问题这一需求,提出了一种低管理开销的网格计算模型。在该模型中,不存在任何节点来管理动态变化的资源,而与之相适应的信息机制、任务调度算法和有限任务复制算法在没有管理节点存在的情况下,以较低的开销使系统在动态的环境中达到自然的协调,实现大规模的分布计算。开发的仿真软件验证了该模型的有效性,并对相关结果进行了初步的性能分析;仿真结果表明,该模型在动态的环境中负载分布合理,资源的计算能力能得到充分利用,为高效地完成参数扫描、蒙特卡罗模拟等大规模易并行计算提供了一个可行的方法。     

Photometric stereo using LCD displays

This paper considers the problem of shape-from-shading using nearby extended light sources. The paper reviews a number of methods that employ nearby illuminants, and describes a new technique that assumes a rectangular planar nearby distributed uniform isotropic illuminant. It is shown that such a light source illuminating a small Lambertian surface patch is equivalent to a single isotropic point light source at infinity, in the absence of shadowing. A closed-form solution is given for the equivalent point light source direction in terms of the illuminant corner locations. Equivalent point light sources can be obtained for distinct illuminant patterns allowing standard photometric stereo algorithms to be used. An extension is given to the case of a rectangular planar illuminant with arbitrary radiance distribution. Experimental results are shown demonstrating the application of the theory to photometric stereo using illumination from a LCD computer monitor. Details on the photometric calibration of the illumination source and image acquisition device are provided.     

Gamut Constrained Illuminant Estimation

This paper presents a novel solution to the illuminant estimation problem: the problem of how, given an image of a scene taken under an unknown illuminant, we can recover an estimate of that light. The work is founded on previous gamut mapping solutions to the problem which solve for a scene illuminant by determining the set of diagonal mappings which take image data captured under an unknown light to a gamut of reference colours taken under a known light. Unfortunately, a diagonal model is not always a valid model of illumination change and so previous approaches sometimes return a null solution. In addition, previous methods are difficult to implement. We address these problems by recasting the problem as one of illuminant classification: we define a priori a set of plausible lights thus ensuring that a scene illuminant estimate will always be found. A plausible light is represented by the gamut of colours observable under it and the illuminant in an image is classified by determining the plausible light whose gamut is most consistent with the image data. We show that this step (the main computational burden of the algorithm) can be performed simply and efficiently by means of a non-negative least-squares optimisation. We report results on a large set of real images which show that it provides excellent illuminant estimation, outperforming previous algorithms. First online version published in February, 2006     

Incorporating illumination constraints in deformable models for shape from shading and light direction estimation

We present a method for the integration of nonlinear holonomic constraints in deformable models and its application to the problems of shape and illuminant direction estimation from shading. Experimental results demonstrate that our method performs better than previous Shape from Shading algorithms applied to images of Lambertian objects under known illumination. It is also more general as it can be applied to non-Lambertian surfaces and it does not require knowledge of the illuminant direction. In this paper, (1) we first develop a theory for the numerically robust integration of nonlinear holonomic constraints within a deformable model framework. In this formulation, we use Lagrange multipliers and a Baumgarte stabilization approach (1972). (2) We also describe a fast new method for the computation of constraint based forces, in the case of high numbers of local parameters. (3) We demonstrate how any type of illumination constraint, from the simple Lambertian model to more complex highly nonlinear models can be incorporated in a deformable model framework. (4) We extend our method to work when the direction of the light source is not known. We couple our shape estimation method with a method for light estimation, in an iterative process, where improved shape estimation results in improved light estimation and vice versa. (5) We perform a series of experiments.     

Color by correlation: a simple, unifying framework for colorconstancy

The paper considers the problem of illuminant estimation: how, given an image of a scene, recorded under an unknown light, we can recover an estimate of that light. Obtaining such an estimate is a central part of solving the color constancy problem. Thus, the work presented will have applications in fields such as color-based object recognition and digital photography. Rather than attempting to recover a single estimate of the illuminant, we instead set out to recover a measure of the likelihood that each of a set of possible illuminants was the scene illuminant. We begin by determining which image colors can occur (and how these colors are distributed) under each of a set of possible lights. We discuss how, for a given camera, we can obtain this knowledge. We then correlate this information with the colors in a particular image to obtain a measure of the likelihood that each of the possible lights was the scene illuminant. Finally, we use this likelihood information to choose a single light as an estimate of the scene illuminant. Computation is expressed and performed in a generic correlation framework which we develop. We propose a new probabilistic instantiation of this correlation framework and show that it delivers very good color constancy on both synthetic and real images. We further show that the proposed framework is rich enough to allow many existing algorithms to be expressed within it: the gray-world and gamut-mapping algorithms are presented in this framework and we also explore the relationship of these algorithms to other probabilistic and neural network approaches to color constancy     

Multiple illuminant direction detection with application to imagesynthesis

Pentland observed (1982, 1984) that the human eye is sensitive to the change of intensities. On an image of a smooth surface, the change of intensities is maximal whenever the illuminant direction is perpendicular to the normal of the surface. This motivates us to introduce the concept of critical points, where the surface normal is perpendicular to some light source direction. Apparently, the illuminant direction has a simple geometric relationship with the corresponding critical points. In this paper, for simplicity reasons, we restrict our discussions to the shading of a Lambertian sphere of known size in a multiple distant light source environment. A novel global representation of the intensity function is derived. Based on this intensity characterization, the least-squares and iteration techniques are used to determine critical points and, thus, the light source directions and their intensities if certain conditions are satisfied. The performance of this new approach is evaluated using both synthetic images and real images. As an application, we use it as a tool to determine light sources in real image synthesis. The experimental results show that this technique can be used to superimpose synthetic objects with a real scene     

Eye‐Centered Color Adaptation in Global Illumination

Color adaptation is a well known ability of the human visual system (HVS). Colors are perceived as constant even though the illuminant color changes. Indeed, the perceived color of a diffuse white sheet of paper is still white even though it is illuminated by a single orange tungsten light, whereas it is orange from a physical point of view. Unfortunately global illumination algorithms only focus on the physics aspects of light transport. The ouput of a global illuminantion engine is an image which has to undergo chromatic adaptation to recover the color as perceived by the HVS. In this paper, we propose a new color adaptation method well suited to global illumination. This method estimates the adaptation color by averaging the irradiance color arriving at the eye. Unlike other existing methods, our approach is not limited to the view frustrum, as it considers the illumination from all the scene. Experiments have shown that our method outperforms the state of the art methods.     

基于照明参数与反射系数的分层SFS算法

提出一种由明暗信息复原形状的鲁棒算法.此算法能有效地估计照明方向、漫反射 系数、照明天顶角以及沿图像轮廓由明暗信息复原形状,并且在考虑自阴影影响情况下,用新 方法从图像的统计特征估计照明的仰角和表面反射系数,使重建强度梯度接近输入图像梯度 实现平滑约束.该方法为数据驱动,稳定可靠,能同时更新表面斜率与高度图,大大减小发射 项与可积分项内的剩余误差.最后给出SFS(Shape from Shading)算法的分层实现.     

基于照明参数与反射系数的分层SFS算法1)

提出一种由明暗信息复原形状的鲁棒算法.此算法能有效地估计照明方向、漫反射系数、照明天顶角以及沿图像轮廓由明暗信息复原形状,并且在考虑自阴影影响情况下,用新方法从图像的统计特征估计照明的仰角和表面反射系数,使重建强度梯度接近输入图像梯度实现平滑约束.该方法为数据驱动,稳定可靠,能同时更新表面斜率与高度图,大大减小发射项与可积分项内的剩余误差.最后给出SFS(Shape from Shading)算法的分层实现.     

基于光照无关图的阴影去除方法

为了在检测目标时排除阴影的干扰,首先论述了光照无关图的原理及其重要性质,然后在此基础上提出了一种基于光照无关图的阴影去除方法。该方法根据光学成像原理通过对图像进行变换来得到一幅与光照无关的灰度图,以达到去除阴影的目的。同时针对该方法需事先测定摄像机的光照无关角的不便之处,还提出了基于直方图统计的摄像机光照无关角判定法则。通过对大量不同场景下视频监控图像的实际测试结果表明,基于光照无关图的阴影去除方法以及基于直方图统计的光照无关角判定方法,可以有效去除目标阴影,并可准确分割目标。     

Modeling and visualization for a pearl-quality evaluation simulator

Visual simulation using CG and VR has attracted wide attention in the machine vision field. This paper proposes a method of modeling and visualizing pearls that will be the central technique of a pearl-quality evaluation simulator. Pearls manifest a very specific optical phenomenon that is not dependent on the direction of the light source. To investigate this feature, we propose a physical model, called an illuminant model for multilayer film interference considering the multiple reflection in spherical bodies. The rendering algorithm has been configured from such representations of physical characteristics as interference, mirroring, and texture, which correspond, respectively, to the sense of depth, brightness, and grain that are the main evaluation factors obtained from psychological experiments. Further, portions of photos of real pearls and the images generated by the present method were evaluated based on a scale of psychological evaluations of pearl-like quality demonstrating, thereby, that not merely the generated images as a whole, but the respective parts of images can present such a pearl-like quality