Path‐space Motion Estimation and Decomposition for Robust Animation Filtering

Renderings of animation sequences with physics‐based Monte Carlo light transport simulations are exceedingly costly to generate frame‐by‐frame, yet much of this computation is highly redundant due to the strong coherence in space, time and among samples. A promising approach pursued in prior work entails subsampling the sequence in space, time, and number of samples, followed by image‐based spatio‐temporal upsampling and denoising. These methods can provide significant performance gains, though major issues remain: firstly, in a multiple scattering simulation, the final pixel color is the composite of many different light transport phenomena, and this conflicting information causes artifacts in image‐based methods. Secondly, motion vectors are needed to establish correspondence between the pixels in different frames, but it is unclear how to obtain them for most kinds of light paths (e.g. an object seen through a curved glass panel). To reduce these ambiguities, we propose a general decomposition framework, where the final pixel color is separated into components corresponding to disjoint subsets of the space of light paths. Each component is accompanied by motion vectors and other auxiliary features such as reflectance and surface normals. The motion vectors of specular paths are computed using a temporal extension of manifold exploration and the remaining components use a specialized variant of optical flow. Our experiments show that this decomposition leads to significant improvements in three image‐based applications: denoising, spatial upsampling, and temporal interpolation.     

Designing Camera Networks by Convex Quadratic Programming

In this paper, we study the problem of automatic camera placement for computer graphics and computer vision applications. We extend the problem formulations of previous work by proposing a novel way to incorporate visibility constraints and camera‐to‐camera relationships. For example, the placement solution can be encouraged to have cameras that image the same important locations from different viewing directions, which can enable reconstruction and surveillance tasks to perform better. We show that the general camera placement problem can be formulated mathematically as a convex binary quadratic program (BQP) under linear constraints. Moreover, we propose an optimization strategy with a favorable trade‐off between speed and solution quality. Our solution is almost as fast as a greedy treatment of the problem, but the quality is significantly higher, so much so that it is comparable to exact solutions that take orders of magnitude more computation time. Because it is computationally attractive, our method also allows users to explore the space of solutions for variations in input parameters. To evaluate its effectiveness, we show a range of 3D results on real‐world floorplans (garage, hotel, mall, and airport).     

Terrain Modelling from Feature Primitives

We introduce a compact hierarchical procedural model that combines feature‐based primitives to describe complex terrains with varying level of detail. Our model is inspired by skeletal implicit surfaces and defines the terrain elevation function by using a construction tree. Leaves represent terrain features and they are generic parametrized skeletal primitives, such as mountains, ridges, valleys, rivers, lakes or roads. Inner nodes combine the leaves and subtrees by carving, blending or warping operators. The elevation of the terrain at a given point is evaluated by traversing the tree and by combining the contributions of the primitives. The definition of the tree leaves and operators guarantees that the resulting elevation function is Lipschitz, which speeds up the sphere tracing used to render the terrain. Our model is compact and allows for the creation of large terrains with a high level o detail using a reduced set of primitives. We show the creation of different kinds of landscapes and demonstrate that our model allows to efficiently control the shape and distribution of landform features.     

试验训练使能体系结构(TENA)的进展与应用情况

未来的作战与训练概念高度依赖于以网络为中心的作战能力,美国国防部认为迫切需要在试验与训练领域建立一种能克服当前“烟囱式”设计、实现靶场资源之间互操作、重用和可组合的新技术。美军借鉴了多种体系结构的研究和应用成果,构建了试验训练使能体系结构(TENA)。本文对TENA的进展、在美军靶场中的最新应用情况及未来发展方向进行阐述,并描述了针对我国靶场资源现状所带来的启示。该体系结构将为未来开发精细强大的试验和训练系统提供必要的支撑。     

基于GA-BP的移动通信设备故障诊断

针对通信设备故障发生随机性强,影响因素多,对应的故障诊断有高度非线性和不确定性的特点,采用BP神经网络算法,优化的GA-BP神经网络算法和POS-BP神经网络算法分别搭建基站设备故障诊断模型,提取设备故障历史数据进行MATLAB仿真,准确预测设备故障类型,帮助提高代维公司调度管理的智能化水平,提高基站设备运维的执行效率。仿真结果表明：本文的BP,GA-BP和POS-BP神经网络算法都能够实现设备故障类别的预测,且GA-BP神经网络算法相比BP和POS-BP神经网络算法对通信设备故障诊断有更好的适应性。     

基于STM32的建筑物接地电阻检测仪的研制

针对目前建筑物接地电阻检测装置存在的缺陷,提出一种基于STM32的建筑物接地电阻检测的系统方案。该方案根据三极补偿原理,采用嵌入式系统控制的主从机软硬件实现接地电阻的精确测量。检测系统包括交流合成、信号采集和数据处理三部分。检测系统由STM32控制产生频率精度高、波形稳定的交流电流注入接地网,对地网中的电压电流信号经带通滤波、差分放大、同步AD转换、FFT处理得到精确地接地电阻值。本检测系统能够提高检测精度以及检测效率,实现检测工作的智能化。     

C波段无线网络通信技术及在飞行试验遥测中应用构想

在分析国内外C波段无线网络通信研究进展基础上,结合现行飞行试验遥测中遇到的技术瓶颈,提出了将C波段无线网络通信技术应用于飞行试验遥测中的构想,建立基于C波段的无线网络的空地一体化遥测网络体系。C波段空地网络化遥测链路的建立,扩展遥测数据传输可用频段的同时增加上行通道,建立机载网络系统与地面监控网络的网络通信链路,为未来空天地一体化遥测网络的建立建立技术基础;同时利用通用的网络管理流程,对整个测试资源动态配比,提高试飞效率。     

经验模态分解与样本熵在并网型光伏逆变器故障诊断中的应用

摘要：针对光伏并网逆变器电路中故障信号的非线性、非平稳特点,提出一种基于经验模态分解(EMD)和样本熵(SampEn)的故障诊断方法。首先,利用经验模态分解对逆变器的三相输出电压进行分解,得到有限个本征模式分量(IMF),从中选取包含故障主要信息的前几个本征模式分量提取故障信息。然后,计算本征模式分量的样本熵,从而得到用于故障诊断的特征向量;最后,将逆变器开路故障进行分类和编码,将故障特征向量输入BP神经网络进行模式识别,从而达到故障诊断的目的。在Matlab环境下对光伏并网逆变器的故障诊断进行了实验,实验结果证明了文中方法能实现对光伏并网逆变器的故障诊断,且与小波包变换相比,该方法具有诊断效率高和准确度高等特点。     

基于CMAC和PID复合控制的电动伺服加载算法研究

针对直升机在海上执行搜救、探测任务时,海浪噪声会干扰高度信息的测量,引起直升机高度波动的问题,提出一种有效的用于处理海浪噪声的卡尔曼滤波方案。通过建立海浪模型,分析无线电高度表和垂直加速度计测量信号的特点,给出了融合两种高度传感器信息的海浪滤波算法,并应用于直升机高度控制系统进行检验。仿真结果表明,根据海况调整滤波器参数,用所提出的算法可以有效滤除海浪噪声,给出满意的高度信息。将此滤波方案应用于直升机高度控制系统,可以明显改善飞机高度的稳定效果。     

学习“魏书生”,提高信息技术课堂的有效性

＂民主与科学＂是魏书生老师工作事业中致胜的法宝,把魏老师的具有个人特色的＂民主＂与＂科学＂融合进信息技术课堂,学会把课堂看作一个宏大的世界,从多方位激发学生的上课兴趣,培养学生良好的学习习惯,使＂事事有人做,人人有事做＂,呈现一个充满勃勃生机的课堂。