基于光线跟踪算法的纹理映射技术

提出了一种基于光线跟踪算法的纹理映射方法，给出了既适用于光线跟踪算法又适用于纹理映射的图形反混淆方法，并扼要介绍了对一些特殊问题的处理方法。     

大规模海浪场景的真实感绘制

针对计算机图形学中大规模海浪场景绘制的难题,提出一种实时绘制高真实感海浪的方法.首先提出同心圆网格模型来模拟海浪表面;然后利用基于GPU的快速傅里叶变换方法生成海浪高度图,并模拟了Choppy波,减轻了磁砖效应.分别采用立方体纹理映射、平面反射及Phong镜面反射技术模拟海面对天空、景物、太阳的反射效果,并在海面的折射效果中考虑了海水深度的影响.最后模拟了海浪中的泡沫以及景物在海面上的阴影效果.该方法已成功地应用在航海模拟器中.     

运用层次纹理映射的基于图像绘制算法

提出一种基于图像绘制(image-basedrendering,简称IBR)的算法,以发挥图形卡的纹理映射功能,并能表现物体表面的三维凹凸细节.首先将深度图像的像素按其相关深度分为多层纹理图像,然后利用纹理映射的硬件支持,将这些层次纹理图像依次投影到与视点相关的成像面上,以得到所需目标图像.为了避免目标图像上出现空洞,在生成时,将纹素在深度层次上进行扩展.由于层次纹理图像需要较大的存储空间,并且在装入纹理缓冲时要花费大量时间,为此还提出一种基于压缩层次纹理图像的目标图像生成算法.实验表明新算法是有效的,尤其适于处理与整个物体大小相比深度层次不太多的三维景物,如有表面凹凸纹理(浮雕、门窗等)的建筑物表面等.     

基于PC和OpenGL的全景图象360度漫游技术

讨论了利用OpenGL图形软件开发系统在PC机上实现全景图象360度漫游。,探讨了采用基于像素匹配的方法进行图象拼接来生成全景图象,并在此基础上利用OpenGL的纹理映射的技术,将全景图象的一部分作为纹理图象映射到由OpenGL预先构造出的虚拟视点空间上,通过改变纹理图象在PC机上实现虚拟场景的360度任意漫游。     

基于BRDF 和GPU 并行计算的全局光照实时渲染

基于光线追踪,将屏幕图像像素分解为投射光线与场景对象交点面片辐射亮度和 纹理贴图的合成,每个面片的辐射亮度计算基于双向反射分布函数(BRDF)基的线性组合,并通 过图形处理器(GPU)处理核心并行绘制进行加速,最后与并行计算的纹理映射结果进行合成。 提出了一种基于BRDF 和GPU 并行计算的全局光照实时渲染算法,利用GPU 并行加速,在提 高绘制效率的前提下,实现动态交互材质的全局光照实时渲染。重点研究：对象表面对光线的 多次反射用BRDF 基的线性组合来表示,将非线性问题转换为线性问题,从而提高绘制效率; 利用GPU 并行加速,分别计算对象表面光辐射能量和纹理映射及其线性组合,进一步提高计算 效率满足实时绘制需求。     

生成真实感图形的四大技术

本文系统地分析了生成计算机真实感图形的四大技术：浓淡处理，光线跟踪，纹理效应和阴影处理，归纳总结了它们的主要算法思想，研究起源和发展动态。     

基于直接投射扩散的烟雾阴影实时模拟

为了提高烟雾模拟的真实感,提出了一种基于直接投射扩散的烟雾阴影实时生成算法。该方法将3维烟雾密度场直接投射到2维平面上,并保存于光亮缓存中,首先生成一张能描述阴影浓度信息的阴影纹理;然后为了解决阴影浓度过估计问题,还新颖地采用流体力学领域的扩散方程来修正浓度分布情况;最后,在可编程图形硬件上,采取投影纹理映射技术将阴影纹理投射到场景中的相应表面。实验证明,该方法所需计算开销小,能简单高效地实时生成计算机3维游戏和动画的烟雾阴影效果。     

市场纵横

SGI创新3D图形技术SGI日前在AUTOFACT’97上首次大范围公开展示其逼真纹理映射（RealityMapping）技术。这是一种创新的3D软件渲染技术，其渲染性能比传统光线追踪（raytracing）算法快20，000倍。这种新的纹理映射技术对光线追踪算法进行了改进，改善了对高反射度表面的数值计算，使用了一种被称为三束反射映象（tri-beamreflectionmapping）的新技术，它能够对非常复杂的模型进行高质量的交互式成像，完善了工业设计的工作流程。SGI在AUTOFACT’97上全面地展示了其逼真纹理映射技术和完整的数字化原型制作解决方案。逼真纹理…     

真实感图形的计算机生成

以真实感图形为代表的光栅图形技术日益成为计算机图形学发展的主流。本文围绕光照模型、画面绘制、纹理映射、影子生成以及场景造型等诸方面对真实感图形技术作了较为全面的综述,并着重讨论了整体光照模型和实现及其各种光线跟踪技术和光能辐射度方法。     

软阴影算法及实现

提出了一个实时软阴影算法。首先以光源为视点生成包含场景深度信息的“阴影映射图”,然后从观察者视点将场景渲染到一个屏幕纹理缓冲中,进而对此纹理采用percentage closer filtering (PCF)策略进行反走样,最后采用高斯滤波对阴影进行模糊处理。该算法不仅得到了较好的软阴影效果,并且也有较好的实时性,可适应实时动态变化场景的需求。     

基于光学映射虚物体的并行绘制

尽管当前基于全局光照模型的图形绘制方法可以渲染出高质量的图象 ,但因为其计算量巨大 ,难以适用于诸如建筑物漫游、虚拟现实等对绘制速度有严格要求的场合 .为此引入光学映射虚物体的概念 ,利用构建在联网PC机上的集群系统 ,并行创建反射和折射虚物体 ,然后利用集群中各节点的图形加速硬件 ,像处理实际三维物体一样绘制这些虚物体 ,可以快速地绘制出反射 /折射效果的图象 .实验结果证明 ,该方法利用 CU P的计算能力和图形硬件的加速特性实现了真实感图形的高性能绘制 ,特别适用于诸如建筑物漫游、计算机动画和虚拟现实等要求交互式绘制的场合     

Adaptive Supersampling in Object Space Using Pyramidal Rays

We introduce a new approach to three important problems in ray tracing: antialiasing, distributed light sources, and fuzzy reflections of lights and other surfaces. For antialiasing, our approach combines the quality of supersampling with the advantages of adaptive supersampling. In adaptive supersampling, the decision to partition a ray is taken in image-space , which means that small or thin objects may be missed entirely. This is particularly problematic in animation, where the intensity of such objects may appear to vary. Our approach is based on considering pyramidal rays (pyrays) formed by the viewpoint and the pixel. We test the proximity of a pyray to the boundary of an object, and if it is close (or marginal), the pyray splits into 4 sub-pyrays; this continues recursively with each marginal sub-pyray until the estimated change in pixel intensity is sufficiently small.
The same idea also solves the problem of soft shadows from distributed light sources, which can be calculated to any required precision. Our approach also enables a method of defocusing reflected pyrays, thereby producing realistic fuzzy reflections of light sources and other objects. An interesting byproduct of our method is a substantial speedup over regular supersampling even when all pixels are supersampled. Our algorithm was implemented on polygonal and circular objects, and produced images comparable in quality to stochastic sampling, but with greatly reduced run times.     

3D modeling of multiple-object scenes from sets of images

This paper proposes a new approach for multi-object 3D scene modeling. Scenes with multiple objects are characterized by object occlusions under several views, complex illumination conditions due to multiple reflections and shadows, as well as a variety of object shapes and surface properties. These factors raise huge challenges when attempting to model real 3D multi-object scene by using existing approaches which are designed mainly for single object modeling. The proposed method relies on the initialization provided by a rough 3D model of the scene estimated from the given set of multi-view images. The contributions described in this paper consists of two new methods for identifying and correcting errors in the reconstructed 3D scene. The first approach corrects the location of 3D patches from the scene after detecting the disparity between pairs of their projections into images. The second approach is called shape-from-contours and identifies discrepancies between projections of 3D objects and their corresponding contours, segmented from images. Both unsupervised and supervised segmentations are used to define the contours of objects.     

Shadow removal for pedestrian detection and tracking in indoor environments

This paper presents a method of shadow removal to improve the accuracy of pedestrian detection and tracking in indoor environments. The proposed method can be divided into four steps: building a background model which can be automatically updated, extract moving objects region, eliminating moving objects shadows, classifying and track pedestrians. The background model is built with pixel value and the updating of Gussian. The approach for real time background-foreground extraction is used to extract pedestrian region that may contains multiple shadows. In the gray histogram space, based on the depth value of the gray images, a reasonable threshold is set to remove shadows from various pedestrians. In this work, we propose a methodology using the foreground frames without shadows to detect and track the pedestrians across training datasets. Comparative experimental results show that our method is capable of dealing with shadows and detecting moving pedestrians in cluttered environments.     

基于GF-2遥感影像的一种快速水体信息提取方法

在高分辨率遥感影像中,水体与阴影(尤其是高大建筑物阴影)、暗色地物不易区 分。针对 GF-2 遥感影像的光谱特性的大量实验研究,提出了一种新综合水体指数法(NCWI)来 增强水体区域信息;同时利用改进的 OSTU 结合鸡群算法(CSO)快速自适应地确定最佳分割阈 值,进而得到最终的水体区域。将其同归一化 NDWI、改进谱间关系法、主成分分析综合法等 常见水体信息提取方法应用于 GF-2 遥感影像水体信息提取,利用采用实地采样和人工解译的 混淆矩阵对提取的水体区域结果进行精度验证和对比分析,从而验证了其有效性和高效性。4 个实验区域的结果证明,该算法可以快速有效地提取水体信息,精确度分别达到 97.82%, 97.44%,92.13%,96.94%。     

Simulation of SAR images of urban areas by using the ray tracing method with measured values of backscatter coefficients

This study uses the ray tracing method to simulate synthetic aperture radar (SAR) images of urban areas. The images are constructed for polarisations: horizontal-horizontal (HH) and vertical-vertical (VV), and different types of buildings, vegetation, and streets. Simulated images of a given area are compared with real SAR images of the same area acquired by the TerraSAR-X satellite. The simulations use the measured backscatter coefficient for HH and VV polarisations and for five different classes of terrain: houses, trees, shrubs, grass, and ground. For multiple reflections, we apply the generalized bistatic Lambertian model. The results show that, despite the limits of the ray tracing method and the approximations involved in modelling three-dimensional objects in the simulated scene, the simulated SAR images correspond well with the actual scene. All features present in the real image are reproduced in the simulated image; in particular, the double reflections of buildings and the surrounding ground appear clearly. However, discrepancies exist, and these are also discussed.     

Moving Shadow Detection and Removal for Traffic Sequences

Segmentation of moving objects in a video sequence is a basic task for application of computer vision. However, shadows extracted along with the objects can result in large errors in object localization and recognition. In this paper, we propose a method of moving shadow detection based on edge information, which can effectively detect the cast shadow of a moving vehicle in a traffic scene. Having confirmed shadows existing in a figure, we execute the shadow removal algorithm proposed in this paper to segment the shadow from the foreground. The shadow eliminating algorithm removes the boundary of the cast shadow and preserves object edges firstly; secondly, it reconstructs coarse object shapes based on the edge information of objects; and finally, it extracts the cast shadow by subtracting the moving object from the change detection mask and performs further processing. The proposed method has been further tested on images taken under different shadow orientations, vehicle colors and vehicle sizes, and the results have revealed that shadows can be successfully eliminated and thus good video segmentation can be obtained.     

Acquiring a radiance distribution to superimpose virtual objectsonto a real scene

This paper describes a new method for superimposing virtual objects with correct shadings onto an image of a real scene. Unlike the previously proposed methods, our method can measure a radiance distribution of a real scene automatically and use it for superimposing virtual objects appropriately onto a real scene. First, a geometric model of the scene is constructed from a pair of omnidirectional images by using an omnidirectional stereo algorithm. Then, radiance of the scene is computed from a sequence of omnidirectional images taken with different shutter speeds and mapped onto the constructed geometric model. The radiance distribution mapped onto the geometric model is used for rendering virtual objects superimposed onto the scene image. As a result, even for a complex radiance distribution, our method can superimpose virtual objects with convincing shadings and shadows cast onto the real scene. We successfully tested the proposed method by using real images to show its effectiveness