非经典参与介质的渲染方法研究综述

参与介质在自然界中广泛存在,也是包括影视特效、电子游戏、仿真系统等大多数图形应用中的主要场景元素之一,对其外观的模拟和再现,可以极大地提升场景的真实感和沉浸感.但是由于参与介质本身结构以及光线在参与介质中的传播过程都非常复杂,所以迄今为止,对参与介质渲染的研究都一直是图形领域的热点和难点.为了处理的方便和计算的高效,传统的参与介质渲染方法都基于两点假设:独立散射假设和局部连续假设.这两点假设也是经典的辐射传输方程成立的关键.但实际上,自然界中的很多参与介质都不满足这两点假设,因此导致现有的参与介质渲染方法生成的图片效果和真实世界的效果存在一定的差异.近年来,研究者们提出了各种非经典参与介质渲染方法,试图打破上述的两点假设,用更符合物理客观规律的方式来处理参与介质,从而进一步提升参与介质渲染的物理真实感.从相干介质渲染技术和离散介质渲染技术两方面展开对现有的面向非经典参与介质的渲染方法进行分析和讨论,重点阐述经典和非经典参与介质渲染方法的区别,以及现有非经典参与介质渲染方法的原理、优势和不足.最后,展望一些开放性问题并进行总结.本综述希望能启发相关领域的研究人员进一步攻克非经典参与介质渲...     

一种基于图像的非均匀单散射参与介质建模方法

针对非均匀单散射参与介质建模问题,提出一种能够保持密度场空间变化细节的建模方法.使用体数据、吸收和散射系数之比分别描述参与介质空间变化的密度分布及光线在其内部的传输特性,通过构建采集图像像素值与它们之间的表达式,将建模问题转化为非线性数值优化问题,求最优解.为了解决高分辨率体数据下大量体素密度值同时求解带来的时间开销大及数值不稳定问题,提出一种符合采集图像像素值明暗分布规律的密度场体数据初始化算法和一种多分辨率体数据逐步求精优化算法;为了快速计算大量体素密度值梯度,提出一种基于GPU的多体素并行梯度计算算法.实验结果表明,提出的方法能够根据采集图像重构烟模型,并保持其细节信息.     

混合使用细节层次与基于图像渲染技术的大面积森林实时渲染算法研究*

描述了一个新的结合细节层次算法和基于图像渲染的森林渲染系统,平衡了基于图像的渲染方法在渲染质量上的不足与几何渲染方法在效率上的缺陷。提出了一种新的基于四叉树纹理拼图的替代物渲染加速算法,有效地提升了替代物创建与渲染速度。最后,在一个实际的室外场景漫游程序中的运行结果表明了该系统可以用较小的渲染代价获得很高的渲染质量。     

基于图像的卡通画扫描线渲染方法

为了模拟艺术家的卡通风格绘画,提出了一种基于图像的卡通画扫描线渲染方法,对用户输入的用数码相机拍摄的图像首先提取轮廓,然后进行颜色处理,最后合并得到具有卡通风格的图像。同时,给出了基于直方图的边缘参数的计算和基于扫描线的颜色处理两个算法,自动实时地完成了渲染过程。实验结果表明,该方法的渲染效果更接近于手绘风格,适合于卡通动画和个性化照片等领域的应用。     

基于注意力机制的蒙特卡罗渲染去噪方法

针对蒙特卡罗渲染在低采样率下绘制图像的噪声问题,提出基于注意力机制的蒙特卡罗噪声去除方法。在模型上,设计去除批归一化层的注意力残差块减少模型的计算量,引入空间注意力和通道注意力关注渲染图像的细节。使用图像的颜色和辅助信息作为网络的输入,加入感知损失函数训练网络。实验结果表明,相比其他蒙特卡罗渲染去噪方法,该方法在去除噪声的同时不仅取得了更高的量化值,而且保留了更多的细节特征。     

MCMC方法在多孔介质流体预测中的应用

孔隙度和渗透率作为油气储层的重要参数,对石油产量的预测有至关重要的作用。在多孔介质流体流动过程中,孔隙度和渗透率的概率密度分布函数结构复杂,难以用经典分布予以描述,该文介绍了应用马尔可夫链蒙特卡罗方法(Markov chain Monte Carlo method)对孔隙度和渗透率进行贝叶斯估计,然后在其后验概率分布中采样,得到部分已知流量数据并计算流量的似然分布,最终得到生产曲线并用该方法成功预测了生产曲线的走势。同时在文章的最后,基于现存方法中存在的问题,提出了相关的改进方向。     

适于点绘制的图形表示方法的研究

在基于点的图形绘制技术中,作为绘制基本元素的点不是数学上无意义的点,它有位置、形状、大小等属性,如何基于点有效地表示图形将影响图形绘制的效果。论文研究了基于点的图形表示方法——单纯基于点的表示、圆球表示和表面足迹表示,重点讨论了足迹表示法的关键问题——足迹大小的求解,提出了一种基于协方差分析的表面足迹的求解方法,结果表明这种方法是有效的。     

一种基于位置的移动信息服务测试数据随机生成方法

基于位置的移动信息服务通过智能移动终端的GPS定位,为用户提供了位置相关的、个性化、方便、有趣的信息。由于位置区域广袤、网络和定位环境复杂,兴趣点数量众多、以及位置服务更新频繁等因素,使得基于位置的移动信息服务测试非常困难。本文探索基于蒙特卡罗随机模拟抽样方法,按照兴趣点位置分布概率随机生成位置点测试数据,实现对地理区域和兴趣点的高覆盖测试。实验表明,与简单随机测试数据生成方法相比,该方法能够有效提高测试效率和测试质量。     

基于信任机制与遗传算法的渲染网格作业调度研究

信任关系是网格作业调度中一个很重要的因素,也是影响网格计算有效性和性能的关键技术之一。将信任机制引入到渲染网格作业调度中,建立渲染网格环境中基于信任机制的作业调度模型,在调度策略上对基本遗传算法进行了改进,提出了基于信任机制的遗传算法。实验结果表明,该算法可以提高任务完成率和平均信任效益,是适用于渲染网格的一种有效作业调度方法。     

基于光场的渲染技术研究

基于图像的渲染技术(Image-Based Rendering,IBR)逐渐成为场景渲染的主要手段之一,目前已有大量的基于此技术的方法提出,其中光场渲染(Light Field Renderin,LFR)是在不需要图像的深度信息或相关性的条件下,通过相机阵列或由一个相机按设计好的路径移动把场景拍摄下来作为输入图像集,对于任意给定的新视点,找出该视点邻近的几个采样点进行简单的重新采样,就能得到该视点处的视图.本文采用两平面参数化的方法设计实施了一套光场渲染的软件方案,用光场渲染的方法实现了真实场景中物体的实时漫游.     

Adaptive lattice‐based light rendering of participating media

The visual world around us displays a rich set of light effects because of translucent and participating media. It is hard and time consuming to render these effects with scattering, caustic, and shaft because of the complex interaction between light and different media. This paper presents a new rendering method based on adaptive lattice for lighting participating media of translucent materials such as marble, wax, and shaft light. Firstly, on the basis of the lattice‐based photon tracing model, multi‐scale hierarchical lattice was constructed by mixed lattice types sampling combined cubic Cartesian and face‐centered cubic with view‐dependent adaptive resolution. Then, an adaptive method to trace diffuse photons and marked specular photons with different phase functions was suggested. Multiple lights and heterogeneous materials were also considered here. Further, the mixed rendering method and GPU accelerate technology were introduced to render different light effects under different participating media. Copyright © 2011 John Wiley & Sons, Ltd.     

基于光流场动态参与介质绘制算法

为了解决动态参与介质场景连续帧的实时绘制问题,提出了一种基于光流场动态参与介质场景的绘制算法。首先,采用区域匹配的方法计算关键帧之间的光流场;然后,通过插值的方法计算中间帧之间的光流场,采用帧间光流连贯性函数表示帧与帧之间光流一致性的度量,保证帧与帧之间介质运动不会发生突变;最后,按照所产生的光流场,绘制连续动态变化的参与介质场景。在连续5帧动态参与介质场景绘制中,所提算法比基于径向基函数模型(RBF)参与介质的光子映射算法效率提高了近3倍,能够达到连续帧的实时绘制,且绘制质量比较高。     

Interactive rendering of globally illuminated scenes including anisotropic and inhomogeneous participating media

Although new graphics hardware has accelerated the rendering process, the realistic simulation of scenes including participating media remains a difficult problem. Interactive results have been achieved for isotropic media as well as for single scattering. In this paper, we present an interactive global illumination algorithm for the simulation of scenes that include participating media, even anisotropic and/or inhomogeneous media. The position of the observer is important in order to render inhomogeneous media according to the transport equation. Previous work normally needed to be ray-based in order to compute this equation properly. Our approach is capable of achieving real time using two 3D textures on a simple desktop PC. For anisotropic participating media we combine density estimation techniques and graphics hardware capabilities.     

Image-based modeling of inhomogeneous single-scattering participating media

We propose a method to reconstruct inhomogeneous single-scattering participating media, which could preserve fine high-frequency details of density field.Volumetric data and the ratio of absorption coefficient to scattering coefficient are used to describe the spatial-varying density distribution and optical properties of certain participating media, and a function between the above parameters and captured pixel values is built.Thus the problem of how to find solutions to these parameters is formulated into...     

Combining estimators for Monte Carlo volume rendering with shading

Monte Carlo volume rendering (MCVR), which allows for generating X-ray like images, offers significant advantages over existing volume rendering techniques in terms of time and memory complexity. The classical shading for MCVR, however, results in a low quality image. In this paper, a so-called estimators combining technique is presented that estimates a realistic rendering using the Lambertian reflection illumination model. Such a technique is particularly adapted to changes in viewing and lighting, and provides high quality shading images exhibiting strong shape and spatial relationship of objects.     

A smooth estimator for MC/QMC methods in finance

We investigate the effect of martingale control as a smoother for MC/QMC methods. Numerical results of estimating low-biased solutions for American put option prices under the Black-Scholes model demonstrate that using QMC methods can be problematic. But it can be fixed by adding a (local) martingale control variate into the least-squares estimator to gain accuracy and efficiency. In examples of estimating European option prices under multi-factor stochastic volatility models, randomized QMC methods improve the variance by merely a single digit. After adding a martingale control, the variance reduction ratio raise up to 700 times for randomized QMC and about 50 times for MC simulations. When the delta estimation problem is considered, the efficiency of the martingale control variate method decreases. We propose an importance sampling method which performs better particularly in the presence of rare events.     

A mesh reconfiguration scheme for speeding up Monte Carlo simulations of electromagnetic scattering by random rough surfaces

Traditional methods of Monte Carlo simulations of random rough surface scattering that use the finite element method involve the generation of multiple meshes for the purpose of taking ensemble averages. We propose a mesh reconfiguration scheme that instead uses a single master mesh. The main idea is to locally modify only the air–surface interface region in the mesh for each instance of a random rough surface. This method achieves a four fold improvement in computation time without any loss of accuracy.     

Overview of Bayesian sequential Monte Carlo methods for group and extended object tracking

This work presents the current state-of-the-art in techniques for tracking a number of objects moving in a coordinated and interacting fashion. Groups are structured objects characterized with particular motion patterns. The group can be comprised of a small number of interacting objects (e.g. pedestrians, sport players, convoy of cars) or of hundreds or thousands of components such as crowds of people. The group object tracking is closely linked with extended object tracking but at the same time has particular features which differentiate it from extended objects. Extended objects, such as in maritime surveillance, are characterized by their kinematic states and their size or volume. Both group and extended objects give rise to a varying number of measurements and require trajectory maintenance. An emphasis is given here to sequential Monte Carlo (SMC) methods and their variants. Methods for small groups and for large groups are presented, including Markov Chain Monte Carlo (MCMC) methods, the random matrices approach and Random Finite Set Statistics methods. Efficient real-time implementations are discussed which are able to deal with the high dimensionality and provide high accuracy. Future trends and avenues are traced.