基于图像精确过分割的虚拟现实场景构建

在分析了以往所采用的改进图像过分割方法的基础上,提出了一种新的虚拟场景构建算法.利用单场景建模,把图像分割成超像素,接着为超像素增加类别标志从而形成集群,然后由集群确定几何类别,最后剪切和折叠不同标志的图像,输出三维场景.该算法利用VMRL对一张图片进行建模,在虚拟漫游系统中无需用户直接参与,可以高效地构建虚拟现实场景.     

虚拟实验软件的建模方法与实现技术

虚拟现实型实验教学软件从真实实验抽象出场景、仪器对象及元器件对象，采用面向对象方法对它们进行数值建模与图像建模，完成物理实验的虚拟、本文总结了该软件开发过程中的各种仿真建模方法和实现技术，包括数学模，型的建立、静态和动态三维图像模型的建立、数学模型与图像模型的协调工作等。该虚拟物理实验实现了可设计性、操作的任意性和具有真实感的交互功能，使学生能像操作真实实验一样操作它，产生浓厚的兴趣，达到良好的教学效果。     

基于力反馈的桌面立体显示与交互系统研究

针对人体对真实空间中三维立体虚拟图像的成像和直接交互问题,提出了包含虚拟立体成像和基于线绳的力反馈设备的立体交互系统设计方法。立体图像的产生方法是通过编程建立一个VC工程,实现了三维对象模型的导入和左右视差图像的产生;人手指末端位置的检测是通过电机的增量式光电编码器测量出线绳长度,进而利用线绳的空间几何关系求出的;根据手指末端位置与虚拟图像的位置关系,利用空间几何关系来合成线绳拉力。在系统中导入对象模型并且进行交互的实验表明:系统具有良好的成像效果和交互效果。     

基于Virtools的虚拟校园在线交互设计与实现

在虚拟校园中,人性化的人机交互设计可提高系统的可用性和用户友好性。本系统在线展示了校园的仿真模型,并提供了可供用户操作的虚拟人物及其交互功能,使用户能尽可能真实地了解校园。为了使用户在浏览虚拟校园时获得更好的在线交互体验,提出并实现了虚拟校园系统需要解决的几个主要交互功能:人物及其视角交互、场景链接交互、信息链接交互、信息提示交互以及虚拟场景中物体的交互。该系统采用了多场景建模方法,以大化小、分而治之,避免使用过大的场景,缩短了系统的在线响应时间;使用Virtools自带的VSL脚本语言实现系统较复杂的交互功能,提高了程序的可重用性和可维护性,同时减少了系统占用的内存空间,提高了运行速度,并且实现了一些Virtools内置的BB不能实现的功能。     

虚拟拉伸实验的设计和实现

利用虚拟现实技术开发了虚拟拉伸实验,阐述了该虚拟实验的功能特点、结构模式以及设计原理,分析了其实现流程及方法,包括三维场景建模、虚拟场景动态生成以及交互式虚拟场景的开发。提出了利用可视化编程语言VB开发一个实现复杂交互动作功能的平台,该平台提供了友好界面,使用户能够直观地组成虚拟三维实验场景,利用键盘或鼠标来控制三维试验机在虚拟场景中运动,并根据用户的指令实现从静态界面对虚拟场景的调用及虚拟场景中试验仪器、工具及其事件的交互,从而控制虚拟模型的动作进行实验。     

基于多幅图像的场景交互建模系统

以普通相机自由运动拍摄得到的多幅非广角照片作为输入，提供给用户一系列简单易用的交互工具，从而恢复出真实场景的几何模型和表面纹理，最终得到具有高度真实感的三维模型．在技术路线上，文中系统采用按照几何空间层次分级重建的方法，并充分利用场景中存在的几何约束信息对重建结果进行优化．实验结果表明，利用该系统生成的三维模型准确真实，能够满足虚拟现实和可视化等应用的要求．     

利用深度图像的虚实物体碰撞交互研究与实现

对传统增强现实系统中虚拟物体与真实物体难以进行碰撞交互的问题,提出一种对深度图像中的场景进行分割,并基于分割结果构建代理几何体的方法来实现虚、实物体的碰撞交互。采用Kinect等深度获取设备获取当前真实场景的彩色图像信息和深度图像信息;通过深度图像的法向聚类及平面拟合技术来识别出场景中的主平面区域;对除去主平面区域的其他聚类点云区域进行融合处理,得到场景中的其他主要物体区域;为识别出的主平面构建虚拟平面作为该平面的代理几何体,为分割出的物体构建包围盒来作为其代理几何体。将这些代理几何体叠加到真实物体上,并对之赋予物理属性,即可模拟实现虚拟物体与真实物体的碰撞交互。实验结果表明,该方法可有效分割简单场景,从而实现虚实交互。     

边界光场

提出一种新的基于图像的绘制方法——边界光场．该方法基于3D全光函数的思想，并使之与场景几何相结合．该方法克服了已有的IBR漫游系统的一些缺陷，利用自适应的的全光采样模式，根据场景复杂度或用户要求组织采样数据，降低了场景数据量；由于场景几何的参与，纠正了较大的深度变形；新的采样数据组织模式去除了对漫游范围的限制．文中方法可有效地应用于虚拟或真实场景漫游系统中．     

真实感云的快速建模

快速云建模便于真实的三维室外场景规划,提出概率场参数控制的元胞自动机方法近似模拟云生成的物理过程,生成云密度体数据,引入符合粒子运动规律的不规则布朗运动随机模型创建概率场,生成的云具有真实云的外形特征.所有建模过程在可编程图形硬件卡上实现,模拟速度满足交互式系统要求.引入考虑了太阳光和背景光的单次散射光照模型,利用光线投射直接体绘制渲染出三维真实感强的云图像.应用到三维虚拟地理环境中增强了场景真实感,建模绘制速度满足交互要求.     

基于图形图像的三维建模技术探讨

现代的工程建筑设计、产品设计和地理信息研究等方面离不开三维建模技术。虚拟场景的构建是虚拟技术的重点和难点,同时,在产品设计中也要应用图像图形的融合技术来构建三维模型。本文对基于图形的三维建模、基于图形的三维建模和图形图像混合建模进行了探讨,为三维建模提出了新的思路。     

虚拟环境建模及实时性改善方法

提出了虚拟现实软件实现方法的概念,利用交互方式的,比较,阐明了虚拟现实与仿真的区别,通过计算机三维实体造型和真实感环境泻染技术,实现了虚拟环境建模,通过融入增强现实的思想,把握虚实结合尺度,将基于图象的方法与基于建模的相结合,从而改善了眯拟环境下交互的实时性。     

Lighting virtual objects in a single image via coarse scene understanding

Achieving convincing visual consistency between virtual objects and a real scene mainly relies on the lighting effects of virtual-real composition scenes. The problem becomes more challenging in lighting virtual objects in a single real image. Recently,scene understanding from a single image has made great progress. The estimated geometry,semantic labels and intrinsic components provide mostly coarse information,and are not accurate enough to re-render the whole scene. However,carefully integrating the estimated coarse information can lead to an estimate of the illumination parameters of the real scene. We present a novel method that uses the coarse information estimated by current scene understanding technology to estimate the parameters of a ray-based illumination model to light virtual objects in a real scene. Our key idea is to estimate the illumination via a sparse set of small 3D surfaces using normal and semantic constraints. The coarse shading image obtained by intrinsic image decomposition is considered as the irradiance of the selected small surfaces. The virtual objects are illuminated by the estimated illumination parameters. Experimental results show that our method can convincingly light virtual objects in a single real image,without any pre-recorded 3D geometry,reflectance,illumination acquisition equipment or imaging information of the image.     

Outlier deletion based improvement on the StOMP algorithm for sparse solution of large-scale underdetermined problems

StOMP algorithm is well suited to large-scale underdetermined applications in sparse vector estimations. It can reduce computation complexity and has some attractive asymptotical statistical properties.However,the estimation speed is at the cost of accuracy violation. This paper suggests an improvement on the StOMP algorithm that is more efficient in finding a sparse solution to the large-scale underdetermined problems. Also,compared with StOMP,this modified algorithm can not only more accurately estimate parameters for the distribution of matched filter coefficients,but also improve estimation accuracy for the sparse vector itself. Theoretical success boundary is provided based on a large-system limit for approximate recovery of sparse vector by modified algorithm,which validates that the modified algorithm is more efficient than StOMP. Actual computations with simulated data show that without significant increment in computation time,the proposed algorithm can greatly improve the estimation accuracy.     

基于互联网图像集的室外场景建模技术综述

目前在互联网上有海量的室外场景照片,它们不仅内容覆盖面广,对同一场景有大量不同视点和光照条件下的采样,而且获取成本很低.如何利用这些照片中包含的丰富场景信息,快速、方便地构造各种逼真的虚拟场景,是互联网迅猛发展给虚拟现实、计算机图形学和计算机视觉带来的新的研究课题之一.文中分析、总结了近年来国内外互联网图像的真实场景几何建模、自然光照建模和材质反射属性建模的最新研究进展,并对其未来的发展趋势提出了一些看法.     

基于时空连贯性和几何简化技术的复杂场景快速消隐绘制算法

提出了一个结合层次遮挡图像缓存的快速消隐绘制算法,本算法首先利用空间连贯性对场景实行快速保守的消隐,对可能可见的近景、中景使用几何绘制,对可能可见的远景实现了基于图像和几何混合的加速绘制,实验表明,由于充分利用了空间连贯性和图像简化技术,本算法效果良好,可适合各种复杂度场景的快速绘制。     

高度复杂植物场景的构造和真实感绘制

绘制高度真实感的自然场景是计算机图形学研究领域的一个富有挑战性的难题,植物对象比如草地和树木是虚拟自然场景的重要组成部分,植物类繁多,形态各异,复杂的结构使其无论在造形、存储还是在绘制上都存在相当的困难,为了解决这个难题,根据植在特点,分别采用多边形,纹元和体纹理作为工餐来构成了不同的植物,并且分别给出了不同植物场景的简单构造方法,绘制的结果证明了这些构造和绘制方法是有效可行的。     

Output-SensitiveVisibility Algorithms for Dynamic Scenes with Applications to Virtual Reality

An output-sensitive visibility algorithm is one whose runtime is proportional to the number of visible graphic primitives in a scene model—not to the total number of primitives, which can be much greater. The known practical output-sensitive visibility algorithms are suitable only for static scenes, because they include a heavy preprocessing stage that constructs a spatial data structure which relies on the model objects’ positions. Any changes to the scene geometry might cause significant modifications to this data structure. We show how these algorithms may be adapted to dynamic scenes. Two main ideas are used: first, update the spatial data structure to reflect the dynamic objects’ current positions; make this update efficient by restricting it to a small part of the data structure. Second, use temporal bounding volumes (TBVs) to avoid having to consider every dynamic object in each frame. The combination of these techniques yields efficient, output-sensitive visibility algorithms for scenes with multiple dynamic objects. The performance of our methods is shown to be significantly better than previous output-sensitive algorithms, intended for static scenes. TBVs can be adapted to applications where no prior knowledge of the objects’ trajectories is available, such as virtual reality (VR), simulations etc. Furthermore, they save updates of the scene model itself; notjust of the auxiliary data structure used by the visibility algorithm. They can therefore be used to greatly reduce the communications overhead in client-server VR systems, as well as in general distributed virtual environments.     

Basis image decomposition of outdoor time-lapse videos

In augmented reality, it is essential that the rendered virtual objects are embedded harmonically into the view of the background scenes and their appearance should reflect the changing lighting condition of the real scene to ensure illumination consistency. In this paper, we propose a novel method to solve for the sunlight and skylight basis images of static outdoor scenes from a time-lapse image sequence. It is proved that the resulted basis images encapsulate the geometry and material reflectivity of the scene, correspond to the global illumination effects of the outdoor scene under a unit intensity of the sunlight and skylight. Our method is fully automatic. Unlike previous methods, it gets rid of the constraints that the reflectance of all objects in scenes should be ideal diffuse, or the weather condition should be overcast or sunshine. During decomposition, we first detect shadowed pixels by analyzing the time-lapse curve of each pixel through k-means clustering, the basis images of sunlight and skylight are then solved by an iterative procedure with the decomposition equation. The basis images are further optimized by exploiting their constraints and priors. Experimental results demonstrate the effectiveness and flexibility of the proposed method. Our method can also be applied in image understanding and compressing.