大规模外存场景的交互绘制

在场景分割的基础上,提出一种连续分层层次细节模型组织场景,并对视点空间进行划分,为每个视点单元计算恰好满足单元内任意视点屏幕像素误差的场景图节点列表,称为cell-front;然后利用cell-front对外存模型的存储进行重新设计.在绘制时采用多线程技术,绘制线程对当前cell-front进行可见性剔除和视点相关的选择绘制;预取线程采用一种基于视点单元的预取策略,利用视点单元之间cell-front的变化控制预取数据的调度.该算法能够在保证场景绘制质量的前提下,在普通的PC机上实现大规模外存场景的实时交互显示.     

QuickWalk:一个大规模场景交互漫游系统

随着三维扫描与建模技术的飞速发展,三维场景的数据量急剧增大,无法一次性载入内存,而且难以进行交互绘制.研究开发了一个大规模外存场景的交互漫游系统QuickWalk,该系统集成了视点相关的层次细节技术、可见性剔除和场景数据的内外存调度,能够有效地减少运行时刻的内存需要,使CPU、GPU和I/O三者的效率得到充分发挥.实验表明,在保证场景绘制质量的前提下,该系统能够在目前普通的PC上实现大规模外存场景的实时显示和交互操纵.     

基于多线程并行的大规模场景交互漫游研究

针对大规模三维场景的交互漫游,提出了一种基于多线程并行调度解决方案,并给出了相应的交互漫游算法.该方法使用离散层次细节技术结合视点相关的动态连续层次细节选择和过渡的批LOD技术.在预处理阶段,对大规模场景进行分层分块处理;在实时漫游阶段,采用多线程并行技术:绘制线程利用四又树层次进行可见性剔除和视点相关简化获取当前可绘地形,并将其提交给GPU进行绘制.预取线程通过预测视点的位置,从外存预取相关的几何数据并调入内存.将该方法应用于具体实例,取得了良好效果,证明了该并行方法的有效性.     

大型三维网格模型的简化及基于视点的LOD控制

传统的三维网格简化及多分辨率建模方法对数据量超出内存限制的大型网格模型已不适用．提出一种基于外存的网格简化和基于视点的细节层次控制方法．该方法建立在网格分割的基础上，利用分割边界的对应性，在一次遍历中对所有的网格分块进行简化，从而克服了通常的网格分割简化方法需要多次分割、重复简化的缺点；同时实现了针对大型网格模型的基于视点的选择件绘制．对模型进行绘制时，模型局部细节可以被快速抽取出来，并且网格的分辨率在整个模型表面呈连续分布．     

大规模点云内外存调度绘制技术

为实现大规模点云的快速绘制,提出以部分内存访问机制为基础、以节点点数上限为叶节点形成条件的平衡八叉树存储结构。设计点云内外存调度绘制流程,包括节点可见性判断、内外存数据调度和点云绘制等环节。为提高可见性判断的效率,在视点与节点距离、夹角约束条件的基础上给出节点可视半径约束。利用实测大规模点云数据进行实验,结果证明,该技术可以在有限的内存资源条件下,以较小的内存消耗实现上亿级规模点云从整体到局部的流畅绘制。     

基于视点的大规模点云数据实时预测调度策略

针对海量数据难以实时渲染的问题,提出基于视点的大规模点云数据实时预测调度策略——“5-5-5”动态调度策略。对整个三维点云进行“分区-子块化”处理,经过多分辨率压缩后保存到服务器端的数据库中。客户端根据视点的变化和菱形调度规则对子块数据进行内外存动态调度并实时绘制,同时向服务器发送传输新数据的请求。实验证明,该算法能有效解决漫游过程中的“抖动”现象,减少单次向服务器请求传输的数据量,实现漫游显示的连续性和平滑性。     

大型网格模型多分辨率的外存构建与交互绘制

结合多分辨率、网格排布和基于视点的绘制技术,提出一种外存多分辨率构建和绘制算法.采用适应性八叉树对模型的包围盒进行划分,自顶向下构建模型的多分辨率层次结构,较好地保持了原模型的细节分布;并对多分辨率结构中每个节点所包含的三角形片段进行网格排布优化,降低了缓存的平均失效率;在实时绘制时,采用基于视点的细节层次选择策略进行模型的细化;最后通过引入数据预取机制来隐藏磁盘I/O延时,进一步提高绘制性能.实验结果表明,该算法在绘制速度与细节保留上均优于同类MRMM算法.     

基于曲线拟合函数和GPU的地形无缝渲染

针对大规模地形实时渲染时不同层次细节过渡产生的画面不连续性问题,以及计算机实时调度大量数据而造成帧速较低的问题,提出了一种基于曲线拟合函数和GPU加速的地形实时绘制方法。根据采样数据点采用最小二乘法构造曲线拟合函数,通过曲线函数控制不同层次网格顶点的布局,从而消除因层次细节变化产生的裂缝。同时根据分辨率不同构建金字塔模型,针对不同层次细节区域数据进行有损或无损压缩,依据视点运动预测实时解压相应数据。实验表明,该方法在地形实时渲染阶段,在保证了较高帧速率的同时,利用视点运动预测保证了帧速率变化小,有效的消除了裂缝,增强了画面效果。     

基于连续HLOD的大规模场景快速绘制算法

大规模场景的快速绘制是虚拟现实技术重要的研究课题之一.为了加速场景的绘制,一般采用层次细节模型和可见性裁剪方法,但是现有算法在处理大规模场景时存在着局限性.本文提出了一种新的大规模场景快速绘制算法,该算法在场景层次划分的基础上,利用拓扑结构可变的网格简化方法为场景层次计算连续的分层层次细节模型（HLOD）;然后在实时绘制阶段,对场景分层层次细节模型进行视点相关的全局和局部细化,并结合快速有效的视域裁剪,从而大大加速了场景绘制速度.实验结果表明该算法是简单有效的,并且算法还可以进一步扩展到外存方式.     

视相关地形多分辨率模型在飞行仿真中的应用

对于飞行仿真中海量地形数据,现有的软硬件无法直接对其进行实时连续的绘制,采用视点相关的层次细节模型可以有效地提高实时绘制的性能.该文针对飞行仿真中大地形实时显示问题,对现有的视点相关多分辨率模型算法进行了改进,采用四叉树结构来表示地形,给出了节点的数据结构和构建四叉树的算法;提出了一种新的细节层次选择误差度量标准;实现了视点相关的连续多分辨率地形网格的简化和实时绘制.     

Out-of-core selection and editing of huge point clouds

In this paper we present an out-of-core editing system for point clouds, which allows selecting and modifying arbitrary parts of a huge point cloud interactively. We can use the selections to segment the point cloud, to delete points, or to render a preview of the model without the points in the selections. Furthermore, we allow for inserting points into an already existing point cloud. All operations are conducted on a rendering optimized data structure that uses the raw point cloud from a laser scanner, and no additionally created points are needed for an efficient level-of-detail (LOD) representation using this data structure. We also propose an algorithm to alleviate the artifacts when rendering a point cloud with large discrepancies in density in different areas by estimating point sizes heuristically. These estimated point sizes can be used to mimic a closed surface on the raw point cloud, also when the point cloud is composed of several raw laser scans.     

An efficient multi-resolution framework for high quality interactive rendering of massive point clouds using multi-way kd-trees

We present an efficient technique for out-of-core multi-resolution construction and high quality interactive visualization of massive point clouds. Our approach introduces a novel hierarchical level of detail (LOD) organization based on multi-way kd-trees, which simplifies memory management and allows control over the LOD-tree height. The LOD tree, constructed bottom up using a fast high-quality point simplification method, is fully balanced and contains all uniformly sized nodes. To this end, we introduce and analyze three efficient point simplification approaches that yield a desired number of high-quality output points. For constant rendering performance, we propose an efficient rendering-on-a-budget method with asynchronous data loading, which delivers fully continuous high quality rendering through LOD geo-morphing and deferred blending. Our algorithm is incorporated in a full end-to-end rendering system, which supports both local rendering and cluster-parallel distributed rendering. The method is evaluated on complex models made of hundreds of millions of point samples.     

Visualizing nonmanifold and singular implicit surfaces with point clouds

We use octree spatial subdivision to generate point clouds on complex nonmanifold implicit surfaces in order to visualize them. The new spatial subdivision scheme only uses point sampling and an interval exclusion test. The algorithm includes a test for pruning the resulting plotting nodes so that only points in the closest nodes to the surface are used in rendering. This algorithm results in improved image quality compared to the naive use of intervals or affine arithmetic when rendering implicit surfaces, particularly in regions of high curvature. We discuss and compare CPU and GPU versions of the algorithm. We can now render nonmanifold features such as rays, ray-like tubes, cusps, ridges, thin sections that are at arbitrary angles to the octree node edges, and singular points located within plot nodes, all without artifacts. Our previous algorithm could not render these without severe aliasing. The algorithm can render the self-intersection curves of implicit surfaces by exploiting the fact that surfaces are singular where they self-intersect. It can also render the intersection curves of two implicit surfaces. We present new image space and object space algorithms for rendering these intersection curves as contours on one of the surfaces. These algorithms are better at rendering high curvature contours than our previous algorithms. To demonstrate the robustness of the node pruning algorithm we render a number of complex implicit surfaces such as high order polynomial surfaces and Gaussian curvature surfaces. We also compare the algorithm with ray casting interms of speed and image quality. For the surfaces presented here, the point clouds can be computed in seconds to minutes on atypical Intel based PC. Once this is done, the surfaces can be rendered at much higher frame rates to allow some degree of interactive visualization.     

View-dependent textured splatting

We present a novel approach to render low resolution point clouds with multiple high resolution textures – the type of data typical from passive vision systems. The low precision, noisy, and sometimes incomplete nature of such data sets is not suitable for existing point-based rendering techniques that are designed to work with high precision and high density point clouds. Our new algorithm – view-dependent textured splatting (VDTS) – combines traditional splatting with a view-dependent texturing strategy to reduce rendering artifacts caused by imprecision or noise in the input data.VDTS requires no pre-processing of input data, addresses texture aliasing, and most importantly, processes texture visibility on-the-fly. The combination of these characteristics makes VDTS well-suited for interactive rendering of dynamic scenes. Towards this end, we present a real-time view acquisition and rendering system to demonstrate the effectiveness of VDTS. In addition, we show that VDTS can produce high quality rendering when the texture images are augmented with per-pixel depth. In this scenario, VDTS is a reasonable alternative for interactive rendering of large CG models.     

使用GPU编程的光线投射体绘制算法

将传统的光线投射体绘制算法在具有可编程管线的图形处理器(GPU)上重新实现.首先将体数据作为三维纹理保存在显存中,然后通过编写顶点程序和片段程序将光线进入点/离开点计算和光线遍历的计算移入GPU中执行,最后根据不同的采样点颜色混合公式实现不同的绘制效果.文中算法仅需绘制一个四边形即可完成三维重建.实验结果表明:在进行光照效果的重建时,该算法能够达到实时交互的绘制要求,并能实现半透明等复杂绘制效果.     

Processing and interactive editing of huge point clouds from 3D scanners

This paper describes a new out-of-core multi-resolution data structure for real-time visualization, interactive editing and externally efficient processing of large point clouds. We describe an editing system that makes use of the novel data structure to provide interactive editing and preprocessing tools for large scanner data sets. Using the new data structure, we provide a complete tool chain for 3D scanner data processing, from data preprocessing and filtering to manual touch-up and real-time visualization. In particular, we describe an out-of-core outlier removal and bilateral geometry filtering algorithm, a toolset for interactive selection, painting, transformation, and filtering of huge out-of-core point-cloud data sets and a real-time rendering algorithm, which all use the same data structure as storage backend. The interactive tools work in real-time for small model modifications. For large scale editing operations, we employ a two-resolution approach where editing is planned in real-time and executed in an externally efficient offline computation afterwards. We evaluate our implementation on example data sets of sizes up to 63 GB, demonstrating that the proposed technique can be used effectively in real-world applications.     

基于点的绘制与压缩技术

基于点的模型数据往往非常庞大,因此怎样在有限的硬件环境下对庞大的点云数据进行压缩传输和实时绘制成为基于点的图形学中两个最重要的问题.回顾了基于点的绘制的最新研究进展,将基于点模型的压缩算法分为渐进压缩编码和单分辨率压缩编码两类分别进行介绍和分析比较,并给出了一些研究建议.     

基于最优传输理论的高质量点云重采样方法

目前通过3D扫描仪获取的点云仍旧存在一些缺陷:点云含有噪声,点云在不同方向上分布不均匀等.本文针对上述问题开展研究.主要工作为提出一种新的算法用于在点云上进行高质量的重采样,即使用较为稀疏的重采样点集去表达较为密集的原始点云的几何形状,同时重采样点集的分布可以满足用户预先指定的目标分布,并具备一定的蓝噪声性质.在最优传...     

图形图像融合的海量建筑绘制

目的 城市3维模型数据海量且结构复杂,缺乏一个高效完善的可视化系统往往是影响数字城市应用的瓶颈之一。通常利用多层次细节（LOD）与调度算法减少每一帧绘制的数据量来提高绘制效率,当场景规模足够大时,即使采用复杂的优化算法也难以取得较好的效果。为此,本文在传统算法基础上,提出一种图形图像融合的海量建筑物场景绘制方法。方法 提出并采用视域分级绘制策略,将视椎体平行分割为感兴趣区域、次感兴趣区域和非感兴趣区域,感兴趣区域采用图形实时绘制方法,使用离屏渲染技术将次感兴趣和非感兴趣区域绘制在纹理图像中,每一帧绘制完成后将二者进行顾及深度信息的融合,实现完整场景渲染。结果 使用公开的纽约市区CityGML文件作为实验数据,数据包含了118 195个LOD1和LOD2级别的建筑物模型。分别构建多组不同建筑数量的场景进行帧率统计实验,绘制帧率都达到20帧/s以上。算法实现了视觉无损失的场景完整渲染,并与Cesium平台进行对比实验,证明算法有效且系统运行流畅。结论 图形图像融合的绘制方法,既保持了图形渲染的漫游连续性,同时也具有图像渲染的场景复杂度无关的优点。实验结果表明,针对大规模的低分辨率建筑模型场景,算法可以有效提高系统的渲染能力,在性能相对较低的硬件条件下也能实现海量建筑物实体模型的流畅漫游,并达到视觉无损失的场景完整绘制。     

A fast rendering method for clouds illuminated by lightning taking into account multiple scattering

Methods for rendering natural scenes are used in many applications such as virtual reality, computer games, and flight simulators. In this paper, we focus on the rendering of outdoor scenes that include clouds and lightning. In such scenes, the intensity at a point in the clouds has to be calculated by taking into account the illumination due to lightning. The multiple scattering of light inside clouds is an important factor when creating realistic images. However, the computation of multiple scattering is very time-consuming. To address this problem, this paper proposes a fast method for rendering clouds that are illuminated by lightning. The proposed method consists of two processes. First, basis intensities are prepared in a preprocess step. The basis intensities are the intensities at points in the clouds that are illuminated by a set of point light sources. In this precomputation, both the direct light and also indirect light (i.e., multiple scattering) are taken into account. In the rendering process, the intensities of clouds are calculated in real-time by using the weighted sum of the basis intensities. A further increase in speed is achieved by using a wavelet transformation. Our method achieves the real-time rendering of realistic clouds illuminated by lightning.