Learned Fitting of Spatially Varying BRDFs

The use of spatially varying reflectance models (SVBRDF) is the state of the art in physically based rendering and the ultimate goal is to acquire them from real world samples. Recently several promising deep learning approaches have emerged that create such models from a few uncalibrated photos, after being trained on synthetic SVBRDF datasets. While the achieved results are already very impressive, the reconstruction accuracy that is achieved by these approaches is still far from that of specialized devices. On the other hand, fitting SVBRDF parameter maps to the gibabytes of calibrated HDR images per material acquired by state of the art high quality material scanners takes on the order of several hours for realistic spatial resolutions. In this paper, we present a first deep learning approach that is capable of producing SVBRDF parameter maps more than two orders of magnitude faster than state of the art approaches, while still providing results of equal quality and generalizing to new materials unseen during the training. This is made possible by training our network on a large‐scale database of material scans that we have gathered with a commercially available SVBRDF scanner. In particular, we train a convolutional neural network to map calibrated input images to the 13 parameter maps of an anisotropic Ward BRDF, modified to account for Fresnel reflections, and evaluate the results by comparing the measured images against re‐renderings from our SVBRDF predictions. The novel approach is extensively validated on real world data taken from our material database, which we make publicly available under https://cg.cs.uni‐bonn.de/svbrdfs/ .     

Gamut Mapping Spatially Varying Reflectance with an Improved BRDF Similarity Metric

Recent spatially varying reflectance (svBRDF) printing systems can reproduce an input document as a combination of matte, glossy and metallic inks. Due to the limited number of inks, this reproduction process incurs some distortion. In this work, we present an svBRDF gamut mapping algorithm that minimizes distortions in the angular and spatial domains. To preserve a material's perceived variation with lighting and view, we introduce an improved BRDF similarity metric that builds on both experimental results on reflectance perception and on the statistics of natural lighting environments. Our experiments show better preservation of object color and highlights, as validated quantitatively as well as through a perceptual study. As for the spatial domain, we show how to adapt traditional color gamut mapping methods to svBRDFs. Our solution takes into account the contrast between regions, achieving better preservation of textures and edges.     

无所不在的传感与机器人感知

传感技术是信息时代信息获取、处理和传输的源头,是"最高意义上的自动化"的技术基础.文中通过概述当今世界上传感器技术的发展与现状,回顾我国机器人传感技术的发展历程,揭示我国在该领域与发达国家的主要差距和发展方向,希望能为促进我国传感技术水平的提高出力.     

立体显示中双目视差模型和深度感知研究

为在平面幕上建立立体视觉,通过模拟真实世界中人眼获取图像过程,介绍计算机绘制双眼视差图像的方法。给出虚拟场景中 2种放置双眼视见体的模型,通过投影分析可以得出内束模型会引入垂直视差,且水平视差不恒定,从而引起同一深度面的物体被感知深度变形。离轴模型符合人眼建立立体视觉的习惯,可以正确反映出物理屏幕前后不同深度的物体,且比单眼图像的视野范围大。     

遥感道路的场景感知与分类检测

基于人类视觉的感知组织和分类融合的基本原理,对遥感图像道路目标的感知模型进行了改进,改进模型分为像素、基元、结构和目标4个处理层次,比传统模型增加了道路场景的自动分类和多类型道路的整合连通2个子过程.基于该模型,提出了一种遥感图像道路检测算法,根据不同的道路场景定义了块状和线状2种不同的道路基元,并分别利用不同方法加以提取、度量和连接.2种基元的连接都采用了显著度驱动的层次性搜索策略.所有连接的路段最终都以中心主线的形式统一描述,并被整合为平滑的全局道路曲线.实验结果表明,该算法能从实际的卫星图像中检测出多种类型的道路,并具有较好的适用能力和有效性.     

Effects of Depth Perception on Performance of Simulated Materials Handling Tasks

Abstract

A series of experiments were performed using ft laboratory simulation of a fork-lift truck setting task. In general, the same effects were observed as found in an another study using fork-lift trucks except that the direction of errors was reversed, showing a reversal of movement relationships in the simulator. The visual angle between the drivers' direction of motion and his line of sight to the target had a large effect on performance times and error rates. When this angle was less than 12°, both times and errors increased sharply. Performance times at different movement amplitudes and target widths were a linear function of an Index of Difficulty except for target widths of less than 2% of the amplitude. Subject age and experience of fork-lift truck driving had a significant effect of performance. Augmentation of vision using a closed circuit television display was beneficial to performance, reducing times by 14% and errors by 52% showing that this is an economic proposition for materials handling vehicles.     

京津冀冬季气溶胶光学厚度遥感反演

针对传统的暗像元算法难以满足植被稀疏陆表气溶胶遥感监测需求的问题,提出了冬季植被稀疏的京津冀地区气溶胶光学厚度的遥感反演方法。以2016—2018年连续3年1—2月的AQUA/MODIS L1B数据为数据源,采用暗像元算法与深蓝算法结合的方法对冬季京津冀地区的气溶胶光学厚度进行了遥感监测。使用AERONET数据对结果进行了验证,并与MODIS MYD04_L2暗像元-深蓝气溶胶产品进行了对比。结果表明,该算法在冬季京津冀地区的气溶胶监测效果远好于暗像元算法,并与MODIS气溶胶产品表现出了显著的相关性,且有效监测范围更大、空间分辨率更高。根据连续监测结果,分析了京津冀地区冬季气溶胶光学厚度空间分布特征及其影响因素。     

Observability-based Optimization of Coordinated Sampling Trajectories for Recursive Estimation of a Strong, Spatially Varying Flowfield

Autonomous vehicles are effective environmental sampling platforms whose sampling performance can be optimized by path-planning algorithms that drive vehicles to specific regions of the operational domain containing the most informative data. In this paper, we apply tools from nonlinear observability, nonlinear control, and Bayesian estimation to derive a multi-vehicle control algorithm that steers vehicles to an optimal sampling formation in an estimated flowfield. Sampling trajectories are optimized using the empirical observability gramian, which quantifies the sensitivity of output measurements to variations of the flowfield parameters. We reconstruct the parameters of the flowfield from noisy flow measurements collected along the sampling trajectories using a recursive Bayesian filter.     

Error Analysis of Change Detection based on Land Cover in High Resolution Remote Sensing Images in Urban Areas

Land use/land cover change detection using high spatial resolution remote sensing image is an important content in land monitoring.However,the problems of shadow,image registration,threshold selection,detection method selection and image post-processing are more prominent in high-resolution images compared with that in medium and low resolution images,which result in more difficulties and uncertainties.Change detection of land cover was carried out base on aerial color images between 2009 and 2012 in Xianlin District of Nanjing,and the errors were analyzed in terms of intra-class and inter-class.The results show that the inter-class error accounted for 97.6% in the omission error,and the intra-class error accounted for 87.1% in the commission error.According to the error sources,72.6% of the false negative pixels are derived from the detection method,43.6% of the false positive pixels are come from detection method while 39.7% from radiation inconsistent.The analysis results in the paper provided reference for the development of new change detection algorithm.     

仿真转台误差分析及误差建模

该文针对某型三轴仿真转台的结构和工作原理，探讨了影响系统空间误差的各个误差源，总结出三轴转台的全部几何运动误差。基于多体系统运动学的基本原理，阐述了系统的拓扑结构，分析了多体系统有误差运动的基本规律，推导出特征矩阵构建方法，研究了根据特征矩阵得到三轴转台的综合空间误差。此空间误差包括了系统的空间指向误差和空间位置误差，为转台的误差补偿和精度分配提供了理论依据。该方法也可为其他类型的多自由度运动系统的误差建模及误差补偿提供理论参考。     

平均紧性约束下的最坏分离空间平滑判别分析

空间平滑的线性判别分析(SLDA)和基于空间平滑欧氏距离的线性判别分析(IMEDA)是目前结合图像特有的空间结构信息进行图像判别降维的两种主要方法,具有比线性判别分析(LDA)更显著的分类效果.与SLDA和IMEDA不同,文中通过参数化投影方向,约束平均类内散度(或紧性)上界和最大化最坏类间散度(或分离度),产生的降维算法分别称为WSLDA和WIMEDA.它们的求解最终可归结为简单的特征值优化问题,避免使用完整特征值分解的缺点.在Yale、AR和FERET标准人脸集上的实验验证它们的有效性.     

基于误差修正的位移传感控制系统设计

为满足工业控制设备的精度定位要求,设计一种基于步进电机和PLC的X-Y-Z三维位移传感控制系统。并针对步进电机容易出现丢步或过冲的现象,提出一种基于时间细分的梯形误差修正算法。试验表明,该系统可以提高位移控制的精度和可靠性。     

利用被动微波遥感数据反演我国积雪深度及其精度评

考虑到我国西部地区使用SSM/I全球算法将高估积雪深度,故以东经105°为界将我国分为东部和西部。在西部地区采用修正后的雪深算法,东部地区沿用全球算法。对散射系数较高,容易和积雪相混淆的降雨、寒漠和冻土地表类型,通过积雪分类树进行剔除,进而发展了一套适用于全国积雪深度的业务化反演方案。最后利用MODIS积雪产品对冬季90天的结果进行了精度评价,总体精度平均达到86.4%,最高精度达到95.5%,Kappa系数均值为65.5%,最大值达到86.2%。     

考虑频谱感知错误的多载波认知无线电资源分配算法

认知无线电(CR)资源分配中二级用户对主用户造成的干扰源于两方面,即带外频谱泄露和频谱感知错误。滤波器组多载波(FBMC)技术和正交频分复用(OFDM)技术相比,FBMC带外泄露较小,频谱利用率较高。FBMC技术考虑干扰来源,可以降低二级用户对主用户的干扰,提高CR系统吞吐量。为此,提出考虑频谱感知错误的CR资源分配算法,建立干扰模型,将资源分配分步简化为载波分配和功率分配,在干扰约束和功率约束条件下对二级用户进行功率分配。基于FBMC和OFDM系统的仿真结果表明,该算法对主用户造成的干扰更小,CR系统可以获得更大的吞吐量,FBMC的干扰和吞吐量性能均优于OFDM。     

基于改进PCA的软测量数据过失误差侦破

为提高软测量的模型精度,剔除建模数据中的过失误差,提出采用Bagging-PCA方法进行误差侦破。利用Bagging算法的集成思想,改善单变量大误差对经典PCA的影响,提高算法稳定性,实现数据的过失误差侦破。用该方法对丙烯浓度的软测量进行过失误差侦破,取得了良好的效果。     

具有时变时滞的递归神经网络的渐近稳定性分析

当神经网络应用于最优化计算时,理想的情形是只有一个全局渐近稳定的平衡点,并且以指数速度趋近于平衡点,从而减少神经网络所需计算时间.研究了带时变时滞的递归神经网络的全局渐近稳定性.首先将要研究的模型转化为描述系统模型,然后利用Lyapunov-Krasovskii稳定性定理、线性矩阵不等式(LMI)技术、S过程和代数不等式方法,得到了确保时变时滞递归神经网络渐近稳定性的新的充分条件,并将它应用于常时滞神经网络和时滞细胞神经网络模型,分别得到了相应的全局渐近稳定性条件.理论分析和数值模拟显示,所得结果为时滞递归神经网络提供了新的稳定性判定准则.     

水体污染时空分布遥感影像要素深度提取方法

针对现有方法影像要素提取精准度不高,易丢失细节信息,不能有效提供全面水体信息的问题,提出水体污染时空分布影像要素深度提取方法.借助ArcGIS水文分析模块生成水系图,建立逐步迭代提取流程,利用主成分变换方法对影像块实行最小化重构,提取影像的主要特征.通过NSCT变换对原始图像进行采样分解,使用卷积计算方式构建自适应池化模型,提取污染水体的纹理特征.基于数学形态学细化水体图像的主要特征与纹理特征结构,构建反演函数进行大气校正,从而完成水污染遥感影像的深度提取.实验结果证明,所提方法提取的遥感影像具有较高精度,同时包含较多细节信息,实用性强,可在水污染检测中推广应用.     

星载遥感图像压缩系统容错技术研究

较强鲁棒性的压缩技术成为主流，压缩系统的容错性能变得越来越重要。本文分析了图像压缩中的几种常见容错技术，针对星载遥感图像的特点结合JPEG2000的相关容错技术，提出了适合硬件实现的容错方案。该方案采用Verilog语言设计并在FPGA上经过验证，最后应用在某型压缩平台上，效果良好。     

软件中的错误传播分析

错误传播是分析可靠性系统不确定性中的一基本问题,可用于发现系统中最易受到错误攻击的部分及各部分之间的相互影响.分别在信号和模块级别上研究了错误在软件中的传播过程,并定义了描述此过程的参数及其计算方法,其中首次提出了模块泄漏率和活动率的概念并给出了计算方法;然后把该错误传播分析框架应用于某卫星光纤陀螺捷联航姿控制系统上.通过故障注入实验确定了其中的分析参数,验证了提出的错误传播框架的可行性与正确性.