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.     

Stabilization of Coupled ODE‐PDE System with Intermediate Point and Spatially Varying Effects Interconnection

In this paper, the stabilization analysis problem of a bi‐directional coupled ODE‐PDE system is proposed. The spatially varying coefficient and the intermediate point interaction between the subsystems makes the coupled system more representative. An invertible infinite‐dimensional backstepping transformation is introducted to bring the original system into an exponentially stable target system. By employing the backstepping method, the kernel functions in the transformations are worked out under some assumptions of the spatially varying coefficient. Then, an explicit state‐feedback law is designed and the exponential stability of the transformed closed‐loop system has been also discussed. Finally, numerical simulation is provided to illustrate the effectiveness of the proposed design.     

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。     

光纤法珀应变传感器波长检测量化误差理论分析

介绍了光纤法珀应变传感器的基本原理,通过钢衍梁连续加载实验发现了应变误差有规律的跳动现象,并在误差理论的基础上深入分析了影响传感器精度的因素,提出了光探测器件本身波长感知的不连续性是造成传感器误差的重要原因,并对此进行了实验仿真,验证了我们的分析,对于进一步提高传感器的精度有较强的实际意义。     

基于深度信息的压缩感知人脸检测跟踪

传统的压缩感知跟踪是基于彩色视频图像序列中的目标跟踪, 但在跟踪过程中可能会受到光照变化和旋转遮挡因素的影响, 从而导致复杂环境下跟踪结果的鲁棒性不足. 为了获得稳定的跟踪结果, 提出了一种基于深度信息的压缩感知人脸检测跟踪算法. 首先, 根据改进的质心分割算法确定首帧深度图中人脸的跟踪位置. 其次, 根据深度信息计算出深度图中每一点对应的平均曲率并形成平均曲率图. 然后, 基于平均曲率图随机提取压缩特征; 最后, 通过压缩降维, 目标邻域搜索, 迭代更新特征模板, 计算出平均曲率图中下一帧人脸的最优跟踪位置, 实现人脸跟踪. 实验结果表明, 将人脸的深度信息和压缩感知特征相结合在光照变化和旋转遮挡情况下具有很好的鲁棒性, 能更好的实现复杂背景下对多姿态人脸的跟踪.     

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.     

水色水温遥感产品真实性检验误差分析

真实性检验是利用现场观测数据或其他高质量遥感产品来获取待检验遥感产品精度的技术,是遥感产品制作及其应用的前提。通过分析均方根误差、平均绝对误差和平均相对误差等多种遥感产品精度评价统计量的适用性,确定了一套水色、水温遥感产品真实性检验流程。以中分辨率成像光谱仪(MODIS)海表温度(SST)遥感产品的真实性检验实例展示了文中确定的水色水温遥感产品真实性检验流程的可行性。分析结果表明待检验产品的分布规律(样本均值和标准偏差)对检验结果的统计量会产生一定的影响,平均值对平均相对误差的影响呈现高相关性。     

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.     

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.     

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。     

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.     

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。     

新型电磁敏感系统的误差校正方法研究

对电磁敏感系统的随机误差校正进行了研究,提出了一种新的处理方法,该方法将原有的三维正交环形天线旋转变换为非正交三维环形天线,并进行了算法的相应改进。数值结果表明了在同等条件下,与原方法相比,当θ处于大角度区域时,该算法能将系统的误差降低到5°以下,当θ处于其它区域时,误差可降低到0°左右。     

气溶胶光学厚度遥感反演查找表的快速构建*

传统的查找表通常以文本形式存储,其构建过程中需要在辐射传输软件中计算大量参数组合,因此其生成过程相当耗时,不利于生成大规模的查找表文件,也不利于遥感反演程序的快速计算。针对查找表的创建过程相当耗时这一问题进行了研究,利用6S辐射传输模型在异构GPU集群环境下进行气溶胶光学厚度遥感反演查找表的快速构建。采取异构GPU集群任务调度机制,提高计算效率,为查找表提供一个稳定的构建环境,有效提高了查找表的构建速率及气溶胶光学厚度遥感反演算法的加速比。     

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%。