不透明材质反射属性采集及建模技术综述

在计算机图形学和计算机视觉领域,材质反射属性模型能够展现真实世界中材质复杂、丰富的光学现象,但反射属性数据具有高维度且材质反射现象复杂多变的特性,因此其采集和建模技术一直是研究的热点及难点.文中介绍了近年来国内外对不透明材质反射现象的采集及建模技术方向取得的最新研究进展,并给出了分析和总结.最后对该领域研究存在的挑战和未来发展趋势提出了一些看法.     

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.     

纹理物体表面反射参数的恢复

物体表面反射参数的恢复是新兴的逆向绘制技术的核心问题，提出一种恢复物体表面BRDF模型参数的方法，假定物体表面的BRDF模型可以近似分解为漫射纹理和整体不变的镜面反射分量，则每一点的反射参数可以用Phong模型来近似计算，首先选取物体表面的一片区域，利用该区域在不同视点光照条件下采样的几幅图像，计算得到该区域的平均镜面反射分量，作为整个物体表面的镜面反射分量，然后据此从物体表面各点的采样中分离出漫射分量，计算各点的漫反射参数，得到近似的BRDF模型，实验数据表明算法是有效的。     

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。     

一种三维物体建模和编码压缩方法

真实物体的三维建模和编码压缩是虚拟现实研究的热点问题.针对三维扫描设备采集的物体表面深度图像数据,文中提出了一种两幅深度图像的自动配准方法,以及基于回路的自动全局配准算法,可以快速、自动地配准全部深度图像,构造出逼真的三维模型.三维模型数据量大,为满足网络条件下的应用需求,文中提出了一种三维网格模型压缩编/解码方法,可编码压缩几何、拓扑和属性数据,压缩比高,并且支持递进传输.研究成果已成功应用在数字博物馆中.     

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.     

基于模型的三维物体识别

实现了一个完整的基于模型的三维物体识别系统,它可识别灰度图象中包含的物 体,如对遮挡加以限制,还可识别被遮挡的物体.该系统能实现物体的自动建模,也可先定性 识别某一物体的立体图对以获取高层知识,然后在高层知识的指导下准确地匹配立体图对中 相对应的特征.此外,还提出了利用最能表示物体特征的表面(特征面)来识别物体的方法,以 提高系统抗噪声的能力.大量实验证明,该系统具有相当的稳健性.     

草图交互式地质建模研究

提出一种简单、快捷的草图交互式地质建模方法,旨在帮助地质学家们在地质勘测初期直观、快速地创建无数据地质概念模型.迄今,现存专业地质建模工具依赖成本较高的真实数据创建精细复杂的三维地质模型,且通常具有建模用时长、不易于学习和使用等缺陷.因此,采用直观的“纸-笔”建模隐喻,提供了一套从草图绘制到三维模型创建,再到三维模型编辑的完整建模流程,允许用户在自由定义的绘图平面上绘制描述模型地质特征的三维草图,并对其构成的连通草图网络实时地进行三维模型重建.模型重建使用分治的思想,大致分为3个步骤完成：首先利用三维草图的几何信息,即拐点,根据其拓扑连接搜寻草图网络中近似平面的能量最小圈,然后通过调和函数计算草图网络中每个圈包围区域的目标平均曲率标量及其法线方向,随后以Laplacian方程优化生成曲面片,最后将曲面片拼接成完整的三维模型.褶皱、断层地质现象可以分别通过重绘和切割操作进行建模.此外,利用层级结构树存储地质模型间的层级关系,并通过变形传递的方式对与形变物体接触的地质模型进行形变,从而保持了地质结构中多物质体相互接触的特性.相比现有基于草图的交互式建模工具,该方法融合了地质学知识,且能够更有效地使用少量草图描述地质物体的特征.基于用户体验调查,该方法具有操作简单、建模直观的特点,能够同时满足专业和非专业人士快速创建地质概念模型的需求.     

融合意图捕捉的笔式草绘特征建模

实现了一种基于笔式草绘特征建模方法.该方法模仿传统的纸笔草绘交互设计方式,利用意图捕捉机制揣测用户的设计意图,并采用基于特征的建模方法构造出三维实体概念模型.支持在模型表面上直接草绘截面和轨迹线,并通过特征切削或添加操作构造复杂物体模型;初步实现了基于手势的模型编辑操作.实验结果表明,该方法简单、高效,适合于快速表达不精确的概念模型.     

物探数据三维属性模型高效构建方法研究

针对传统三维地质属性建模方法进行了研究,提出了一种物探数据三维属性模型的高效构建方法。该方法利用结构化数据快速搜索策略,并采用了分块建模机制。在PC机上的实验表明,该方法不仅克服了大规模数据引起的计算机系统硬件瓶颈,而且在保证物探属性模型质量的前提下,构建效率显著提高。     

Manual/automatic colorization for three-dimensional geometric models utilizing laser reflectivity

While laser scanners can produce a high-precision 3D shape of a real object, appearance information of the object has to be captured by an image sensor, such as a digital camera. This paper proposes a novel and simple technique for colorizing 3D geometric models based on laser reflectivity. Laser scanners capture the range data of a target object from the sensors. Simultaneously, the power of the reflected laser is obtained as a by-product of the range data. The reflectance image, which is a collection of laser reflectance depicted as a grayscale image, contains rich appearance information about the target object. The proposed technique is an alternative to texture mapping, which has been widely used to realize photo-realistic 3D modeling but requires strict alignment between range data and texture images. The proposed technique first colorizes a reflectance image based on the similarity of color and reflectance images. Then the appearance information (color and texture information) is added to a 3D model by transferring the color in the colorized reflectance image to the corresponding range image. Some experiments and comparisons between texture mapping and the proposed technique demonstrate the validity of the proposed technique.     

Rapid classification of specular and diffuse reflection from image velocities

We propose a method for rapidly classifying surface reflectance directly from the output of spatio-temporal filters applied to an image sequence of rotating objects. Using image data from only a single frame, we compute histograms of image velocities and classify these as being generated by a specular or a diffusely reflecting object. Exploiting characteristics of material-specific image velocities we show that our classification approach can predict the reflectance of novel 3D objects, as well as human perception.     

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.     

Stereo Image Analysis of Non-Lambertian Surfaces

Stereo image analysis is based on establishing correspondences between a pair of images by determining similarity measures for potentially corresponding image parts. Such similarity criteria are only strictly valid for surfaces with Lambertian (diffuse) reflectance characteristics. Specular reflections are viewpoint dependent and may thus cause large intensity differences at corresponding image points. In the presence of specular reflections, traditional stereo approaches are often unable to establish correspondences at all, or the inferred disparity values tend to be inaccurate, or the established correspondences do not belong to the same physical surface point. The stereo image analysis framework for non-Lambertian surfaces presented in this contribution combines geometric cues with photometric and polarimetric information into an iterative scheme that allows to establish stereo correspondences in accordance with the specular reflectance behaviour and at the same time to determine the surface gradient field based on the known photometric and polarimetric reflectance properties. The described approach yields a dense 3D reconstruction of the surface which is consistent with all observed geometric and photopolarimetric data. Initially, a sparse 3D point cloud of the surface is computed by traditional blockmatching stereo. Subsequently, a dense 3D profile of the surface is determined in the coordinate system of camera 1 based on the shape from photopolarimetric reflectance and depth technique. A synthetic image of the surface is rendered in the coordinate system of camera 2 using the illumination direction and reflectance properties of the surface material. Point correspondences between the rendered image and the observed image of camera 2 are established with the blockmatching technique. This procedure yields an increased number of 3D points of higher accuracy, compared to the initial 3D point cloud. The improved 3D point cloud is used to compute a refined dense 3D surface profile. These steps are iterated until convergence of the 3D reconstruction. An experimental evaluation of our method is provided for areas of several square centimetres of forged and cast iron objects with rough surfaces displaying both diffuse and significant specular reflectance components, where traditional stereo image analysis largely fails. A comparison to independently measured ground truth data reveals that the root-mean-square error of the 3D reconstruction results is typically of the order 30–100 μm at a lateral pixel resolution of 86 μm. For two example surfaces, the number of stereo correspondences established by the specular stereo algorithm is several orders of magnitude higher than the initial number of 3D points. For one example surface, the number of stereo correspondences decreases by a factor of about two, but the 3D point cloud obtained with the specular stereo method is less noisy, contains a negligible number of outliers, and shows significantly more surface detail than the initial 3D point cloud. For poorly known reflectance parameters we observe a graceful degradation of the accuracy of 3D reconstruction.     

Reflectance and Shape from Images Using a Collinear Light Source

In this paper, a novel technique, called the photogeometric technique, is presented for surface reflectance extraction and surface recovery from an image sequence of a rotating object illuminated under a collinear light source (where the illuminant direction of the light source lies on or near the viewing direction of the camera). The rotation of the object is precisely controlled. The object surface is assumed to be smooth and uniform. The technique first computes the 3D locations of some surface points which give singular brightness values and builds the surface reflectance function by extracting the brightness values of these surface points from the image sequence. Then the technique uses the surface reflectance function and two images of the surface to recover surface depth and orientation simultaneously. The technique has been tested on real images of surfaces with different reflectance properties and geometric structures. The experimental results and comprehensive analysis show that the proposed technique is efficient and robust.     

Quality assessment of Landsat surface reflectance products using MODIS data

Surface reflectance adjusted for atmospheric effects is a primary input for land cover change detection and for developing many higher level surface geophysical parameters. With the development of automated atmospheric correction algorithms, it is now feasible to produce large quantities of surface reflectance products using Landsat images. Validation of these products requires in situ measurements, which either do not exist or are difficult to obtain for most Landsat images. The surface reflectance products derived using data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS), however, have been validated more comprehensively. Because the MODIS on the Terra platform and the Landsat 7 are only half an hour apart following the same orbit, and each of the 6 Landsat spectral bands overlaps with a MODIS band, good agreements between MODIS and Landsat surface reflectance values can be considered indicators of the reliability of the Landsat products, while disagreements may suggest potential quality problems that need to be further investigated. Here we develop a system called Landsat-MODIS Consistency Checking System (LMCCS). This system automatically matches Landsat data with MODIS observations acquired on the same date over the same locations and uses them to calculate a set of agreement metrics. To maximize its portability, Java and open-source libraries were used in developing this system, and object-oriented programming (OOP) principles were followed to make it more flexible for future expansion. As a highly automated system designed to run as a stand-alone package or as a component of other Landsat data processing systems, this system can be used to assess the quality of essentially every Landsat surface reflectance image where spatially and temporally matching MODIS data are available. The effectiveness of this system was demonstrated using it to assess preliminary surface reflectance products derived using the Global Land Survey (GLS) Landsat images for the 2000 epoch. As surface reflectance likely will be a standard product for future Landsat missions, the approach developed in this study can be adapted as an operational quality assessment system for those missions.     

Categorization of indoor places by combining local binary pattern histograms of range and reflectance data from laser range finders

This paper presents an approach to categorize typical places in indoor environments using 3D scans provided by a laser range finder. Examples of such places are offices, laboratories, or kitchens. In our method, we combine the range and reflectance data from the laser scan for the final categorization of places. Range and reflectance images are transformed into histograms of local binary patterns and combined into a single feature vector. This vector is later classified using support vector machines. The results of the presented experiments demonstrate the capability of our technique to categorize indoor places with high accuracy. We also show that the combination of range and reflectance information improves the final categorization results in comparison with a single modality.     

Microstructure Control in 3D Printing with Digital Light Processing

Digital light processing stereolithography is a promising technique for 3D printing. However, it offers little control over the surface appearance of the printed object. The printing process is typically layered, which leads to aliasing artefacts that affect surface appearance. An antialiasing option is to use greyscale pixel values in the layer images that we supply to the printer. This enables a kind of subvoxel growth control. We explore this concept and use it for editing surface microstructure. In other words, we modify the surface appearance of a printed object by applying a greyscale pattern to the surface voxels before sending the cross-sectional layer images to the printer. We find that a smooth noise function is an excellent tool for varying surface roughness and for breaking the regularities that lead to aliasing. Conversely, we also present examples that introduce regularities to produce controlled anisotropic surface appearance. Our hope is that subvoxel growth control in stereolithography can lead 3D printing towards customizable surface appearance. The printing process adds what we call ground noise to the printed result. We suggest a way of modelling this ground noise to provide users with a tool for estimating a printer's ability to control surface reflectance.     

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.     

Surface radiance correction for shape from shading

It is well known that many surfaces exhibit reflectance that is not well modelled by Lambert's law. This is the case not only for surfaces that are rough or shiny, but also those that are matte and composed of materials that are particle suspensions. As a result, standard Lambertian shape from shading methods cannot be applied directly to the analysis of rough and shiny surfaces. In order to overcome this difficulty, in this paper, we consider how to reconstruct the Lambertian component for rough and shiny surfaces when the object is illuminated in the viewing direction (retroreflection). To do this we make use of the diffuse reflectance models described by Oren and Nayar, and by Wolff. Our experiments with synthetic and real-world data reveal the effectiveness of the correction method, leading to improved surface normal and height recovery.