城市轨道列车视景仿真的光照效果研究

利用三维建模工具Multigencreator和三维模型驱动工具Multigen Vega制造光照效果,实现了对列车行驶三维视景仿真的光照效果模拟。     

基于PC机群的多通道视景仿真技术研究

使用PC机群实现多通道视景仿真,可以在给用户带来强烈的沉浸感和较大的视野的同时得到很高的性能价格比。讨论了包含用户交互控制下的静态场景和独立数据驱动下的动态实体的的多通道视景仿真系统的体系结构,提出了在该结构下的视景同步方法和动态实体的运动平滑算法。实验结果表明两种技术实现了基于PC机群的大规模场景、多运动实体的视景仿真中多通道视景的同步和运动实体的平滑,在保持画面流畅的同时满足了用户的交互要求。     

多水下机器人视景仿真系统技术研究

该文介绍了多水下机器人群体分佰式智能控制软件的视景仿真系统。以MultiGen Creator建模,利用实时视景开发软件包OpenGL Performer,采用POSIX Thread多线程技术,在Linux环境下开发了分布式多水下机器人三维视景仿真平台。实现了多水下机器人分布式智能控制软件系统的实时视景仿真,保证了整个系统的信息共享与时间同步。同时该文讨论了该视景仿真软件的开发过程以及整个系统的体系结构和信息流程。试验结果表明,该视景系统可逼真演示多水下机器人编队水下航行、作业等过程,并满足系统仿真的实时性要求。     

采用重要性面片采样的实时全局光照

提出了一种实时全局光照的计算方法。该方法支持任意视点下动态光源的一次间接光照计算,并且物体表面材质可实时编辑,该算法预计算了各面片上的形状因子来解决遮挡问题,并记录形状因子较大的重要性面片作为间接光源。渲染时先从光源方向对场景记录了一个扩展的阴影图,包含了光源照射到的面片ID和其光通量,再根据采样好的间接光源来计算间接光照。使用CUDA,整个光照计算过程在GPU中完成,可以对静态场景进行实时渲染,并能达到逼真的渲染效果。     

卧室光源亮度的自动优化算法

室内光源亮度调节得好坏对室内设计及最终渲染效果会产生重要的影响,通常需要专业人士费时费力地手工调整.为此,提出了一种卧室光源亮度的自动调优算法.首先,在二维图像灰度熵的基础上进一步给出了三维光照熵的定义,以此作为评价三维卧室光源亮度优劣的数学模型;然后,利用模拟退火算法来求解卧室的最大光照熵值,从而得到光源的最优亮度值;最后,借助于GoogleAI采用的神经图谱(NIMA)图像美观度评估算法,验证了所提算法的正确性与有效性.该基于最大光照熵的光源的亮度自动调优算法也适用于客厅、餐厅等室内场景灯光亮度的设定与自动调优.     

虚拟现实在多目标水下作业中的应用

基于软件平台Vega和Creator软件开发出多目标水下作业的视景仿真系统。文中详细描述了开发本仿真系统的意义、硬件系统的组成、系统软件的选择、模型的建立、虚拟海洋环境的生成,以及软件系统的设计与实现。仿真结果表明,该系统能逼真地演示出多目标水下作业的整个过程,能实现从多个视角有效地观察整个水下作业过程中各个物体的运动情况,并且满足不同情况下的仿真需要。该文最终建立一个基于水下作业的多目标动态的视景仿真系统,生成三维视景效果场景,做出视景仿真管理界面。     

交互式自行车模拟器视景仿真系统开发

视景仿真系统是交互式自行车模拟器的重要组成部分。其给骑车者提供逼真的虚拟三维漫游场景。开发的视景仿真系统硬件上采用PowerWall虚拟现实系统，软件上基于自主开发的虚拟现实通用应用开发平台VR Flier，提高了开发的效率。VR Flier采用面向对象方法设计，能够全面地支持小同领域和不同规模的VR应用开发。视景仿真系统通过优化以及动态调度三维场景模型的方法提高了大范围漫游场景的渲染帧率；并对场景路面坡度及视景转向信号进行平滑处理，获得很好的视景仿真效果。     

基于分形几何的动态云模拟

云是一种重要的自然景观。对云彩的模拟在视景仿真系统、计算机游戏、三维动画中有着广泛的应用。该文针对目前一些云彩模拟方法中存在的实现复杂、计算耗时、图像分辨力不高且只能生成静态云等问题,提出了一种在分形几何的Diamond—Square算法中采用改良的随机数发生器和顶点扰动、纹理运动结合模拟实现动态云的方法。基本思想是通过运用二次随机法构造改良的随机数发生器,并把它应用到分形几何的Diamond—Square算法中生成逼真的静态云图,然后通过顶点扰动、纹理运动结合模拟实现动态云。最后运用VC＋＋和OpenGL开发工具实现了云的动态模拟。结果表明,该方法实现简单,可获得实时、逼真的动态云效果。     

地面站视景仿真系统的设计与优化

为了能更直观形象地展现无人机的飞行状态及攻击目标的效果,提高地面站操纵人员的操作效率,开发了无人机地面站三维视景仿真系统.论述了无人机地面站三维视景系统的设计方法,给出了系统总体结构图,研究了基于Vega Prime视景仿真软件的三维视景系统开发流程,以及如何采用大地形动态分页调度、独立通信线程等先进技术,重点解决了大场景下视景仿真刷新率低的难点.软件设计中引入多线程编程思想,详述了每个线程的具体实现,极大优化了程序性能.     

装配式实时飞行视景仿真平台研究

介绍了基于装配式数据结构的视景平台的开发背景及其意义,给出了装配式飞行视景仿真数据结构的思想,其中包括视景资源的装配式结构,以及三维模型及其特效等驱动数据的装配。并基于SBS实时网络实时从网上接收仿真数据,驱动三维模型运动。采用Vtree视景引擎,通过Vc＋＋6.0平台建立了实时飞行视景仿真软件平台。     

Multiscale facial structure representation for face recognition under varying illumination

Facial structure of face image under lighting lies in multiscale space. In order to detect and eliminate illumination effect, a wavelet-based face recognition method is proposed in this paper. In this work, the effect of illuminations is effectively reduced by wavelet-based denoising techniques, and meanwhile the multiscale facial structure is generated. Among others, the proposed method has the following advantages: (1) it can be directly applied to single face image, without any prior information of 3D shape or light sources, nor many training samples; (2) due to the multiscale nature of wavelet transform, it has better edge-preserving ability in low frequency illumination fields; and (3) the parameter selection process is computationally feasible and fast. Experiments are carried out upon the Yale B and CMU PIE face databases, and the results demonstrate that the proposed method achieves satisfactory recognition rates under varying illumination conditions.     

基于图像的三维光照效果的动态重现

传统图像纹理可以给虚拟物体增加丰富的细节,但由于纹理是在特定光照条件下获取的照片,当虚拟光照条件变化时,纹理细节缺少随之动态变化的真实感。凹凸纹理通过扰动法向量可以实现细节的基本阴影变化,但生成一张真实照片的凹凸纹理是困难的。文中介绍了BRDF和BTF的概念和理论,提出了一种基于图像的适用于漫反射物体表面细节动态重现的方法,可以使映射后的纹理在不同虚拟光照条件下呈现动态变化的效果。     

Homomorphic filtering based illumination normalization method for face recognition

The appearance of a face image is severely affected by illumination conditions that will hinder the automatic face recognition process. To recognize faces under varying lighting conditions, a homomorphic filtering-based illumination normalization method is proposed in this paper. In this work, the effect of illumination is effectively reduced by a modified implementation of homomorphic filtering whose key component is a Difference of Gaussian (DoG) filter, and the contrast is enhanced by histogram equalization. The resulted face image is not only reduced illumination effect but also preserved edges and details that will facilitate the further face recognition task. Among others, our method has the following advantages: (1) neither does it need any prior information of 3D shape or light sources, nor many training samples thus can be directly applied to single training image per person condition; and (2) it is simple and computationally fast because there are mature and fast algorithms for the Fourier transform used in homomorphic filter. The Eigenfaces method is chosen to recognize the normalized face images. Experimental results on the Yale face database B and the CMU PIE face database demonstrate the significant performance improvement of the proposed method in the face recognition system for the face images with large illumination variations.     

Exploring the effect of illumination on automatic expression recognition using the ICT-3DRFE database

One of the main challenges in facial expression recognition is illumination invariance. Our long-term goal is to develop a system for automatic facial expression recognition that is robust to light variations. In this paper, we introduce a novel 3D Relightable Facial Expression (ICT-3DRFE) database that enables experimentation in the fields of both computer graphics and computer vision. The database contains 3D models for 23 subjects and 15 expressions, as well as photometric information that allow for photorealistic rendering. It is also facial action units annotated, using FACS standards. Using the ICT-3DRFE database we create an image set of different expressions/illuminations to study the effect of illumination on automatic expression recognition. We compared the output scores from automatic recognition with expert FACS annotations and found that they agree when the illumination is uniform. Our results show that the output distribution of the automatic recognition can change significantly with light variations and sometimes causes the discrimination of two different expressions to be diminished. We propose a ratio-based light transfer method, to factor out unwanted illuminations from given images and show that it reduces the effect of illumination on expression recognition.     

基于USB和DALI的LED智能照明控制系统

本文研究了DALI协议在照明控制系统中的应用,与正在兴起的LED照明相结合,实现智能照明。利用USB技术,使用户可以操作PC机实现对智能照明系统的控制,大大增加了操作的便利性。     

Extraction of illumination invariant facial features from a single image using nonsubsampled contourlet transform

Face recognition under varying lighting conditions is challenging, especially for single image based recognition system. Exacting illumination invariant features is an effective approach to solve this problem. However, existing methods are hard to extract both multi-scale and multi-directivity geometrical structures at the same time, which is important for capturing the intrinsic features of a face image. In this paper, we propose to utilize the logarithmic nonsubsampled contourlet transform (LNSCT) to estimate the reflectance component from a single face image and refer it as the illumination invariant feature for face recognition, where NSCT is a fully shift-invariant, multi-scale, and multi-direction transform. LNSCT can extract strong edges, weak edges, and noise from a face image using NSCT in the logarithm domain. We analyze that in the logarithm domain the low-pass subband of a face image and the low frequency part of strong edges can be regarded as the illumination effects, while the weak edges and the high frequency part of strong edges can be considered as the reflectance component. Moreover, even though a face image is polluted by noise (in particular the multiplicative noise), the reflectance component can still be well estimated and meanwhile the noise is removed. The LNSCT can be applied flexibly as neither assumption on lighting condition nor information about 3D shape is required. Experimental results show the promising performance of LNSCT for face recognition on Extended Yale B and CMU-PIE databases.     

Face recognition under varying illumination based on a 2D face shape model

This paper proposes a novel illumination compensation algorithm, which can compensate for the uneven illuminations on human faces and reconstruct face images in normal lighting conditions. A simple yet effective local contrast enhancement method, namely block-based histogram equalization (BHE), is first proposed. The resulting image processed using BHE is then compared with the original face image processed using histogram equalization (HE) to estimate the category of its light source. In our scheme, we divide the light source for a human face into 65 categories. Based on the category identified, a corresponding lighting compensation model is used to reconstruct an image that will visually be under normal illumination. In order to eliminate the influence of uneven illumination while retaining the shape information about a human face, a 2D face shape model is used. Experimental results show that, with the use of principal component analysis for face recognition, the recognition rate can be improved by 53.3% to 62.6% when our proposed algorithm for lighting compensation is used.     

基于OpenGL的LED灯光仿真系统

主要介绍在OpenGL支持下的LED照明系统的实时仿真，照明实施人员可以通过计算机看到照明系统的光照效果，并探讨了光线追踪算法下预览动态光照效果的可能性。     

基于动力学模型的汽车制动稳定性虚拟展示

现有3D引擎的物理模型不能真实反映车辆制动时的运动状态。为此,提出一种汽车制动稳定性虚拟展示系统。建立汽车动力学模型,包括四轮车辆模型和车轮轮胎模型,利用上层仿真软件对动力学模型进行运算和虚拟场景渲染,给出车轮状态和虚拟仪表的展现方法,并基于3D引擎设计虚拟展现系统。实验结果表明,该系统能同时观测整车及车轮的运行状态,实时再现制动过程中车轮抱死、车身横摆侧滑的行为,其动力学模型能够满足虚拟展现对画面渲染的实时性、连续性要求。