路径追踪中出射光线方向的快速采样方法

目的 基于双向反射分布函数的重要性采样方法在渲染物体材质表面时有极佳的拟真度,但采样方式存在复杂和高硬件存储开销的问题。针对上述问题,提出了一种基于权重生成和向量线性插值的采样方法用于解决该问题。方法 在对出射光线方向进行计算时,通过给定的入射光方向、法线方向与物体表面材质光滑度参数,首先计算镜面反射光线方向,再结合余弦与指数函数二者的函数特性生成具有一定分布特征的权重值,并将镜面反射方向与随机生成的漫反射方向进行线性插值,其插值权重即为上述生成的权重值,最后规范化得到具有一定分布特征的新的出射方向。结果 本文基于该快速采样方法,给出了路径追踪渲染算法的一套完整实现,并利用本文算法,从常见各类物体表面中抽取9种进行渲染,将所得实验结果与通过原始双向反射分布函数采样算法所渲染得到的实际结果进行比较,发现利用快速采样算法后渲染速度可提升1.521.99倍,且由于近似所造成的相对误差可控制在8%以内,并将原本用于描述物体表面的34 MB数据量降为仅几个浮点数的数据量,可知上述采样方法既具有极低硬件存储开销的特点,其渲染的图片又能保有较高的拟真度。随着光滑度参数的连续变化,可使得被渲染的物体表面由理想漫反射到理想镜面反射之间均匀过渡,从而统一了漫反射、高光反射与镜面反射三者的采样形式。结论 本文使用简化的出射光方向采样算法替代传统BRDF重要性采样算法,并配套给出基于新采样算法实现的一套完整的路径追踪渲染方法,使得在不失真实度的情况下使得计算机在模拟漫反射、高光反射与镜面反射的形式得以简化与统一。本文方法亦可作为现有诸多采样方法的替代方案,其极低的存储开销优势可用于渲染含有大量不同材质的复杂场景;在渲染一般的粗糙表面、瓷器以及金属等常见各向同性材质时也有较佳的表现力。上述的完整实现方式可以在需要的时候对静态场景做不失真实度的快速渲染。     

一种真实物体表面反射属性采集与建模方法

为了快速获取物体表面反射属性数据和三维几何数据,研制了一套包括相机、光源、三维扫描仪、控制系统等的物体表面反射属性数据采集系统,在此基础上,提出一种单材质物体表面反射属性建模方法.该方法根据物体反射特性对漫反射与镜面反射分别建模,能够逼真地构造出物体表面反射属性模型,并且保证了参数求解的稳定性.最后设计并实现了反射属性模型编辑工具.实验结果表明,利用该编辑工具可以实时、可视地调整模型参数,从而满足用户对反射属性模型编辑的需求.     

利用采样球体提取真实感纹理

提出了一种从真实物体中提取纹理的方法.利用具有复杂纹理的参考球体作为被采样物体,计算其组成材质的BRDF(bidirectional reflectance distribution function)模型参数以及各点由不同材质构成的比例,形成一幅材质权重图.该图作为纹理映射到3D物体上后,配合BRDF模型参数进行渲染,形成一种适用于重光照(relighting)的纹理.被渲染物体可根据自身方位以及光源亮度/方位呈现出自然的光影变化,达到较为逼真的外观效果.     

三维物体表面材质实时编辑

艺术家进行设计时,常常需要一种可以交瓦地修改模型表面材质的工具.为了在环境光下对模型表面的材质进行实时编辑,提出一种基于预计算辐射传输的算法:首先预计算环境光相对于模型表面每一个顶点的可见性;然后在绘制时实时计算物体表面的双向反射分布函数(BRDF);最后通过查找环境光相对于模型表面每一个顶点的可见性,快速绘制出物体表面材质.实验结果表明,使用该算法,用户可以通过调节BRDF的参数,实现物体表面材质的实时动态编辑,同时支持动态视点和动态环境光.     

基于混合反射模型的SFS有限元方法的研究

提出了基于混合反射模型的由明暗恢复物体三维形状的有限元算法。用正方形面元逼近光滑曲面,把曲面表示为所有节点基函数的线性组合;基于既含有漫反射成分又有镜面反射成分的混合模型,结合节点基函数,将反射图线性化。考虑数字图像的特点,直接使用离散形式的SFS问题的亮度约束形式,用最小化方法得到高度满足的线性方程;使用Kaczmarz算法计算出表面三维形状。使用合成图像和实际图像验证该文算法的有效性,探讨了该算法的性能。     

基于线性变换球面分布的实时间接光泽反射

目的 在实时渲染领域中,立即辐射度算法是用于实时模拟间接光泽反射效果的算法之一。基于立即辐射度的GGX SLC(stochastic light culling)算法中使用符合真实物理定律的GGX BRDF(bidirectional reflectance distribution function)光照模型计算间接光泽反射,计算复杂度很高,并且其计算开销会随着虚拟点光源的数量呈明显的线性增长。为解决上述问题,提出一种更高效的实时间接光泽反射渲染算法。方法 基于数学方法中的线性变换球面分布,将计算复杂度很高的GGX BRDF球面分布近似为一种计算复杂度较低的球面分布,并基于该球面分布提出了在单点光源以及多点光源环境下的基于物理的快速光照模型。该光照模型相比GGX BRDF光照模型具有更低的计算开销。然后基于该光照模型,提出实时间接光泽反射渲染算法,计算虚拟点光源对着色点的辐射强度,结合多点光源光照模型对着色点着色,高效地渲染间接光泽反射效果。结果 实验结果表明,改进后的实时间接光泽反射算法能够以更高的渲染效率实现与GGX SLC算法相似的渲染效果,渲染效率提升了20%～40%,并且场...     

一种基于物理反射模型颜色不变性的阈值分割算法

提出了一种适用于视频监控场景的基于物理反射模型的阈值分割算法,该算法主要解决背景颜色识别受光强非均匀分布、高光效应影响的问题.算法步骤主要包括:首先基于Phong反射模型推导出漫反射分量颜色不变性并根据这一判定条件计算得到漫反射分量系数;其次,利用微分法则实现对模型镜面反射分量系数和镜面反射强度指数的估计;最后,根据建立的物理反射模型实现背景阈值分割.大量实验分析结果表明,文中提出的算法利用视频监控的物理反射模型和大量统计信息,能够更好地解决受光强非均匀分布和高光效应影响的颜色识别问题.     

从单幅高动态范围图像恢复环境中物体的材质

提出一种从单幅高动态范围图像恢复一般环境中物体材质的方法,适用于单一材质物体,对物体形状和光照条件没有任何特殊要求.在一般光照环境中,获取被考察物体的一幅高动态范围图像以及用来近似物体光照的一个或几个高动态范围环境映照,然后用模拟退火算法求解逆向绘制问题.在求解过程中采用了基于图像的光照和光线跟踪技术,充分考虑了物体自身互反射的影响.最后得到了物体表面反射模型的最优参数.若与基于图像的建模技术相结合,可以根据真实物体的照片建立真实感模型.     

均场退火算法在单幅灰度图像高光检测与恢复中的应用

为了解决单幅灰度图像高光去除方法恢复结果存在的图像失真问题,提出一种基于均场退火算法的单幅灰度图像高光检测方法.首先利用反射模型分别对镜面反射分量和漫反射分量的分布进行建模;然后通过均场退火算法的迭代过程估计镜面反射分量和漫反射分量的比例,对可能存在的高光区域进行检测;最后利用基于BSCB模型的图像修复方法修复高光区域.采用一种主观评价方法和客观评价方法相结合的性能的评价方法对文中方法进行验证,结果表明,该方法是有效的;与传统的高光检测与恢复的方法相比,该方法能够有效地检测出灰度图像中镜面反射区域,且恢复效果更符合人眼视觉、恢复后的图像质量更好,提高了图像高光区域的恢复率.     

照明方向及反射特性参数的鲁棒估计

由图象明暗度提取物体表面三维形状需要预知照明方向及表面反射特性参数，但这些参数在实际应用中往往难于得到，文中提出了一种新的方法，该方法只需图象存在奇点，就可直接由灰度图象估计照明方向和反射特性参数，实验证明，该方法具有计算量少，误差小，鲁棒性好等优点。     

Surface identification using the dichromatic reflection model

The author describes a method based on the dichromatic reflection model for identifying object surfaces. The surface spectral reflectance function of an inhomogeneous object is described as the sum of a constant interface (specular) reflectance and a body (diffuse) reflectance under all illumination geometries. The interface component is used to estimate the spectral power distribution of the illuminant without using a reference white standard, whereas the body component is used as the principal indication of the surface identity. The body reflectance function of each surface is recovered. A method to classify the observed reflectances is developed, and an algorithm to estimate a body reflectance function, unique to each surface, from the classified reflectances is proposed. The author shows the reliability of the surface classification method and the accuracy of estimated body reflectance function     

Shape and View Independent Reflectance Map from Multiple Views

We consider the problem of estimating the 3D shape and reflectance properties of an object made of a single material from a set of calibrated views. To model the reflectance, we propose to use the View Independent Reflectance Map (VIRM), which is a representation of the joint effect of the diffuse+specular Bidirectional Reflectance Distribution Function (BRDF) and the environment illumination. The object shape is parameterized using a triangular mesh. We pose the estimation problem as minimizing the cost of matching input images, and the images synthesized using the shape and VIRM estimates. We show that by enforcing a constant value of VIRM as a global constraint, we can minimize the cost function by iterating between the VIRM and shape estimation. Experimental results on both synthetic and real objects show that our algorithm can recover both the 3D shape and the diffuse/specular reflectance information. Our algorithm does not require the light sources to be known or calibrated. The estimated VIRM can be used to predict the appearances of objects with the same material from novel viewpoints and under transformed illumination. The support of National Science Foundation under grant ECS 02-25523 is gratefully acknowledged. Tianli Yu was supported in part by a Beckman Institute Graduate Fellowship.     

高质量图像绘制的LDI改进算法

对于漫反射场景,LayeredDepthImage(LDI)能够产生很好的绘制效果,但对于高光的场景,它存在绘制图像失真的问题。文章提出一种能够有效地绘制漫反射和高光场景的LDI改进算法。该算法对LDI的每个深度像素增加一个方向向量,对位于同一深度的像素采用加权平均的方法生成新视点下的目标图像。同时采用将方向向量离散化的方法,有效地降低了存储量。实验表明,新算法在绘制速度和绘制质量方面都取得了比较理想的效果。     

Separation of diffuse and specular components of surface reflection by use of polarization and statistical analysis of images

The image of an opaque object is created by observing the reflection of the light incident on its surface. The dichromatic reflection model describes the surface reflection as the sum of two components, diffuse and specular terms. The specular reflection component is usually strong in its intensity and polarized significantly compared to the diffuse components. On the other hand, the intensity of the diffuse component is weak and it tends to be unpolarized except near occluding contours. Thus, the observation of an object through a rotating polarizer approximately yields images containing constant diffuse component and specular component of different intensity. In this paper, we show that diffuse and specular components of surface reflection can be separated as two independent components when we apply independent component analysis to the images observed through a polarizer of different orientations. We give a separation simulation of artificial data and also give some separation results of real scenes.     

Separation of Reflection Components Using Color and Polarization

Specular reflections and interreflections produce strong highlights in brightness images. These highlights can cause vision algorithms for segmentation, shape from shading, binocular stereo, and motion estimation to produce erroneous results. A technique is developed for separating the specular and diffuse components of reflection from images. The approach is to use color and polarization information, simultaneously, to obtain constraints on the reflection components at each image point. Polarization yields local and independent estimates of the color of specular reflection. The result is a linear subspace in color space in which the local diffuse component must lie. This subspace constraint is applied to neighboring image points to determine the diffuse component. In contrast to previous separation algorithms, the proposed method can handle highlights on surfaces with substantial texture, smoothly varying diffuse reflectance, and varying material properties. The separation algorithm is applied to several complex scenes with textured objects and strong interreflections. The separation results are then used to solve three problems pertinent to visual perception; determining illumination color, estimating illumination direction, and shape recovery.     

A Framework for Automatically Recovering Object Shape,Reflectance and Light Sources from Calibrated Images

In this paper, we present a complete framework for recovering an object shape, estimating its reflectance properties and light sources from a set of images. The whole process is performed automatically. We use the shape from silhouette approach proposed by R. Szeliski (1993) combined with image pixels for reconstructing a triangular mesh according to the marching cubes algorithm. A classification process identifies regions of the object having the same appearance. For each region, a single point or directional light source is detected. Therefore, we use specular lobes, lambertian regions of the surface or specular highlights seen on images. An identification method jointly (i) decides what light sources are actually significant and (ii) estimates diffuse and specular coefficients for a surface represented by the modified Phong model (Lewis, 1994). In order to validate our algorithm efficiency, we present a case study with various objects, light sources and surface properties. As shown in the results, our system proves accurate even for real objects images obtained with an inexpensive acquisition system.     

Light source position and reflectance estimation from a single view without the distant illumination assumption

Several techniques have been developed for recovering reflectance properties of real surfaces under unknown illumination. However, in most cases, those techniques assume that the light sources are located at infinity, which cannot be applied safely to, for example, reflectance modeling of indoor environments. In this paper, we propose two types of methods to estimate the surface reflectance property of an object, as well as the position of a light source from a single view without the distant illumination assumption, thus relaxing the conditions in the previous methods. Given a real image and a 3D geometric model of an object with specular reflection as inputs, the first method estimates the light source position by fitting to the Lambertian diffuse component, while separating the specular and diffuse components by using an iterative relaxation scheme. Our second method extends that first method by using as input a specular component image, which is acquired by analyzing multiple polarization images taken from a single view, thus removing its constraints on the diffuse reflectance property. This method simultaneously recovers the reflectance properties and the light source positions by optimizing the linearity of a log-transformed Torrance-Sparrow model. By estimating the object's reflectance property and the light source position, we can freely generate synthetic images of the target object under arbitrary lighting conditions with not only source direction modification but also source-surface distance modification. Experimental results show the accuracy of our estimation framework.     

Transparent and Specular Object Reconstruction

This state of the art report covers reconstruction methods for transparent and specular objects or phenomena. While the 3D acquisition of opaque surfaces with Lambertian reflectance is a well‐studied problem, transparent, refractive, specular and potentially dynamic scenes pose challenging problems for acquisition systems. This report reviews and categorizes the literature in this field. Despite tremendous interest in object digitization, the acquisition of digital models of transparent or specular objects is far from being a solved problem. On the other hand, real‐world data is in high demand for applications such as object modelling, preservation of historic artefacts and as input to data‐driven modelling techniques. With this report we aim at providing a reference for and an introduction to the field of transparent and specular object reconstruction. We describe acquisition approaches for different classes of objects. Transparent objects/phenomena that do not change the straight ray geometry can be found foremost in natural phenomena. Refraction effects are usually small and can be considered negligible for these objects. Phenomena as diverse as fire, smoke, and interstellar nebulae can be modelled using a straight ray model of image formation. Refractive and specular surfaces on the other hand change the straight rays into usually piecewise linear ray paths, adding additional complexity to the reconstruction problem. Translucent objects exhibit significant sub‐surface scattering effects rendering traditional acquisition approaches unstable. Different classes of techniques have been developed to deal with these problems and good reconstruction results can be achieved with current state‐of‐the‐art techniques. However, the approaches are still specialized and targeted at very specific object classes. We classify the existing literature and hope to provide an entry point to this exiting field.     

全局光照环境中的逆向绘制

提出一种恢复场景中所有物体的反射特性的方法.算法以一个全景图、场景的完整几何模型和光源信息为输入,结果是场景的一个完整反射模型.恢复是以逐步求精的方式进行的.先假定物体表面是漫反射面并生成一幅全景图,然后算法逐步迭代,比较绘制的全景图和原始全景图,如果有的物体的误差超过某个阈值,算法为他们选择更负责的反射模型.最后,场景中的每个物体有了一个合适的反射模型,可以在新的光照和视点条件下绘制,旧的物体可以从场景中移去,新的物体可以添加到场景中.对漫反射、各向同性反射和各向异性反射纹理面的纹理恢复也作了深入研究;高光和阴影的影响也能基本去除.