基于Creator的三维模型的简化研究

三维模型是虚拟现实系统中重要的组成部分，在三维模型的处理中存在两个主要问题：一是载入场景文件要花费很多时间；二是即使是在高性能的PC机上，浏览场景也是一件繁重而费时的事。当鼠标移动之后，场景变换要滞后几秒钟甚至几分钟。为此需要对模型进行优化，该文从简化模型和提高渲染速度两个方面介绍了基于Creator的优化三维模型及减少载入时间的几种方法。     

航天测控任务三维场景可视化的设计及实现

从航天测控任务三维场景可视化的需求出发，归纳航天测控任务三维场景的表现方式、数据组织结构和系统体系结构，探索航天测控任务三维场景可视化技术流程。着重研究三维地形生成技术、场景地物建模技术、场景融合技术和视点控制技术等关键技术。从场景数据组织、植被建模和纹理贴图三个方面优化场景。构建航天测控任务三维空间可视化平台，在实时数据的驱动下，实现了航天测控任务三维场景显示，为航天测控任务执行提供可视化技术支持。     

基于场景图的视锥裁减优化

为提高三维大场景中海量三维数据和地形数据的展示性能,加速算法是一种解决办法。根据场景图的组织结构特点,采用视锥体裁减技术。通过研究视锥体判别公式,推导简化高效的判别公式,实现三维场景的加速。实验表明,优化的视锥裁减算法可以提高裁减性能。     

一种面向OPENGL的三维模型的转化方法

在对OpenGL的显示列表和VRML的研究基础上，提出了一种将3DMAX制作的三维模型用VRML模型作中介，将模型数据(包括网格顶点数据，材质，贴图)进行分离、提取、规范化，优化保存．最后在OpenGL建立的虚拟场景中快速生成三维模型并显示其虚拟影象的方法．该方法能使由三维建模软件产生的三维模型方便快速的移植到支持OpenGL的应用程序开发环境中．对于建立虚拟场景的模型有较大的实用价值。     

基于3DS MAX的三维模型的优化研究

三维模型是虚拟现实系统中重要的组成部分,在三维模型的处理中存在两个主要问题：一是导入场景文件的时间过长,甚至因场景文件过大而不能导入。二是在微机上浏览场景费时,甚至出现断断续续的现象。因此需要在建模时进行优化,该文从简化模型和提高渲染速度两个方面提出了基于3DS MAX的优化三维模型及减少导入时间的多种方法。     

基于智能的配电网电力大数据三维场景可视化分析

配电网电力大数据的三维场景重构是实现数据优化挖掘的关键,提出基于人工智能的配电网电力大数据三维场景可视化分析方法。建立配电网电力大数据三维场景的网格分布结构模型,并进行配电网电力大数据三维场景实时数据监测,根据监测结果进行配电网电力大数据的统计特征分析,对配电网电力大数据三维场景实时数据采用信息融合和模糊层析性分析方法进行信息融合和自适应调度,提取配电网电力大数据的三维可视化分布特征量,采用视觉特征重构技术,实现对配电网电力大数据三维场景可视化重构,在人工智能算法控制下提高电力大数据三维场景可视化重构的精度。仿真结果表明,采用该方法进行配电网电力大数据三维场景可视化重构的精度较高,提高了配电网电力大数据挖掘的效能。     

VRML／X3D场景的优化

VRML／X3D是新一代面向Web的交互式三维图形规范,由本地机上VRML的浏览器解释生成三维场景．也就是三维网页的技术规范。作者根据经验所得,从结构层次、文件压缩、源码优化和重复代码的简化等几个方面对VRML／X3D场景进行优化．压缩了VRML／X3D场景文件的大小,加快VRML／X3D三维网页的浏览速度。     

VRML/X3D场景的优化

VRML/X3D是新一代面向Web的交互式三维图形规范,由本地机上VRML的浏览器解释生成三维场景,也就是三维网页的技术规范。作者根据经验所得,从结构层次、文件压缩、源码优化和重复代码的简化等几个方面对VRML/X3D场景进行优化,压缩了VRML/X3D场景文件的大小,加快VRML/X3D三维网页的浏览速度。     

基于弱随机相机位姿图像的三维场景恢复

随着深度学习的快速发展,基于多视图的三维场景恢复研究和应用越来越广泛。许多研究者关注通过优化深度学习网络提高三维场景恢复效果,深度学习使用的训练数据集的相机位姿分布具有规范度高的内在特点。然而在实际应用中,普通用户拍摄目标场景时,相机位姿分布具有较大的随机性,难以保证获取到和训练数据集质量等同或接近的目标场景图像数据,从而影响恢复效果。为了缓解这一问题,该文提出了基于弱随机相机位姿图像的三维场景恢复方法,通过给用户提供目标场景拍摄建议,降低所获取目标场景图像相机位姿分布的随机性,提高场景的三维恢复效果。首先,用户在目标场景拍摄指导下,获得同一场景下不同视角的二维图像数据,然后通过SFM (Structure From Motion)恢复场景的三维稀疏点云和相机位姿,最后在MVS(Multi-View Stereo)网络模型中进行三维点云的稠密重建。实验结果表明,相比拍摄建议前,该方法有效降低了所获取目标场景图像相机位姿分布的随机性,三维场景恢复成功率提高了52.95%。     

基于虚拟现实技术的三维河流仿真系统

虚拟现实技术是当今计算机科学研究的一个热点，该文将这一技术应用到三维河流的虚拟仿真系统中，阐述了创建三维河流虚拟仿真系统的三个具体环节：即三维河流的实体建模，模型数据的读取预处理，虚拟场景的渲染实现，以及在各环节中用到的关键技术。     

基于实例和约束的三维场景概念设计和系统实现

3D场景设计是VR建模中最重要也最耗人力的工作之一,如何解决该问题是一项重要的课题.本文提出一种新的基于实例和约束的三维场景概念设计方法.首先,根据所获取的场景实例中所蕴涵的不同层次的语义信息,对其进行场景元素过滤和场景语义标注,并由此构建三维场景实例库.相应地,对场景中可能出现的元素类别进行分类和语义标注,并建立场景元素库.接着,应用基于实例的方法,并结合场景设计过程中所涉及到的知识(约束),给出三维场景概念设计的一般方法;最后以一个实例对该方法做进一步的说明.研究表明,该方法符合人们对场景设计的一般过程.此外,由于场景实例和场景元素具有丰富的语义信息,使得所生成的场景除了常规的可视效果,还可以直接应用于虚拟现实环境以及三维动画等数字内容制作中.     

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.     

Automatic 3D Indoor Scene Updating with RGBD Cameras

Since indoor scenes are frequently changed in daily life, such as re‐layout of furniture, the 3D reconstructions for them should be flexible and easy to update. We present an automatic 3D scene update algorithm to indoor scenes by capturing scene variation with RGBD cameras. We assume an initial scene has been reconstructed in advance in manual or other semi‐automatic way before the change, and automatically update the reconstruction according to the newly captured RGBD images of the real scene update. It starts with an automatic segmentation process without manual interaction, which benefits from accurate labeling training from the initial 3D scene. After the segmentation, objects captured by RGBD camera are extracted to form a local updated scene. We formulate an optimization problem to compare to the initial scene to locate moved objects. The moved objects are then integrated with static objects in the initial scene to generate a new 3D scene. We demonstrate the efficiency and robustness of our approach by updating the 3D scene of several real‐world scenes.     

基于X3D的三维用户界面组态引擎设计

传统组态软件二维用户界面仿真度低,不能直观反映工业现场生产情况,针对该问题设计并实现了基于X3D的组态软件三维用户界面组态引擎.介绍了三维用户界面组态引擎的系统架构以及使用该引擎进行场景组态时的流程;基于X3D建立了三维场景对象库,并建立对象之间的关联作为场景组态的约束关系,利用其加快场景组态过程;使用XJ3D图形工具包实现了该引擎的原型系统.实验证明该引擎组态简便,使用其组态生成的三维用户界面具有较好的仿真效果.     

多核并行技术在三维场景加载中的应用

研究一种用于三维漫游场景的多核并行加载系统。在多核计算机上采用OGRE进行场景加载,利用OpenMP实现多线程创建与同步,动态设置并行程序的线程数量。通过对一个三维山地漫游场景加载不同数量植物的实例,测试出不同线程下并行加载Mesh的时间,获得较好的加速比。实验结果表明,采用OpenMP并行技术可有效改进三维漫游场景的加载速率,加快地形场景的显示,提高绘制效率。     

Autostereoscopic Rendering of Multiple Light Fields

Light fields were introduced a decade ago as a new high‐dimensional graphics rendering model. However, they have not been thoroughly used because their applications are very specific and their storage requirements are too high. Recently, spatial imaging devices have been related to light fields. These devices allow several users to see three‐dimensional (3D) images without using glasses or other intrusive elements. This paper presents a light‐field model that can be rendered in an autostereoscopic spatial device. The model is viewpoint‐independent and supports continuous multiresolution, foveal rendering, and integrating multiple light fields and geometric models in the same scene. We also show that it is possible to examine interactively a scene composed of several light fields and geometric models. Visibility is taken care of by the algorithm. Our goal is to apply our models to 3D TV and spatial imaging.     

The Convergence of Graphics and Imaging

Over twenty years ago a SIGGRAPH panel session addressed the convergence of computer graphics and image processing. At that time the emphasis was on low-level operations such as filtering to avoid anti-aliasing, and related psycho-physics issues. More recently, Graphics and Imaging are converging at a higher level as we move toward blending the synthetic world of computer-generated images with the real world of computer-captured images. In this talk we describe several research directions that relate to this convergence, and illustrate with specific examples of work at MERL – A Mitsubishi Electric Research Laboratory. These research directions are: Analyzing images of the human face to determine identity and orientation and ultimately to reconstruct the shape of the face. Reconstruction of static and dynamic 3D geometries from 2D images separated in time or space: here the objective is to take multiple images of a real-world scene and recreate the 3D geometry of the scene. If objects in the scene are moving, then the objective is extracting the dynamic geometry. Once the geometry has been reconstructed, editing and relighting of the scene becomes possible. Display of 3D scalar fields (also known as volume graphics) concerns 3D as opposed to 2D images, such as CT and MRI scans. These scans can be thought of as 3D images in that they are point samples of a 3D scalar field, just as a computer-captured image is a point sample of a 2D sample field. The objective of volume graphics is to create and display the 3D geometries that underly 3D images. An inexpensive yet real-time (30 fps for a 256 x 256 x 256 image) implementation of Pfister and Kaufman's Cube-4 rendering architecture will be described.     

加速概率存在场目标检测的改进算法

概率存在场（POM）算法是一种多视角目标检测算法,其根据各视角对应的二值前景图像,估计检测场景中所有3D位置对应地面上存在目标的概率。当检测场地面积过大时,POM算法估计所有3D位置上存在目标的概率会十分耗时,拖累算法速度。提出了一种加快POM算法速度的方法：根据二值前景图像和3D位置信息,大幅减少POM算法需要处理的3D位置数量,从而提高算法速度。实验结果表明：在对算法检测结果影响很小的情况下,对于单目标和多目标检测场景,算法速度都得到了较大的提升。