数字孪生水下三维实景数据底板获取技术研究

为了获取高精度的水下三维模型细节纹理结构,满足数字孪生建设对水下三维实景数据底板获取的需求,实现对水下构筑物的实时可视化动态监测,基于GNSS技术、USBL技术研究构建了水陆一体化定位技术,融合水陆一体化定位技术、有缆ROV和水下摄影测量设备等研发了水下摄影测量系统,实现了数字孪生水下三维实景数据底板的获取,并采用多波束测深系统、水下三维全景成像声纳系统等对水下摄影测量系统获取的三维实景模型数据成果精度进行了验证,结果表明：水下摄影测量系统获取的三维实景模型精度满足规范要求,可用于数字孪生流域、工程等水下基础数据底板的建设,也可为水下高精度三维场景重构再现和水利工程水下构筑物实时动态监测提供技术支撑。     

数字近景摄影测量技术在矿山地表沉陷监测中的应用研究

为了解决传统的矿山地表沉陷监测方法存在的劳动强度大、不能实时观测、难以获得瞬时3维移动变形信息等缺陷,提出了一种利用基于非量测数相机的数字近景摄影测量技术进行塌陷区沉陷监测的方法。该方法首先利用标定过的高分辨率数字相机获取塌陷区的数字立体影像像对;然后采用相对定向、影像匹配等摄影测量解析处理技术提取塌陷区地表的数字高程模型;最后通过与该区域开采前数字高程模型对比分析来完成塌陷区沉陷范围、深度、体积等沉陷参数计算。应用研究结果表明,数字近景摄影测量的测定精度基本可以满足这次应用条件下沉陷监测的精度要求。该方法为矿山地表塌陷区的沉陷监测提供了一条可行的途径。     

机载倾斜摄影数据在三维建模及单斜片测量中的应用

机载倾斜摄影测量系统是对常规摄影测量系统的改进和发展,它能够获取常规摄影无法得到的地物立面的纹理信息和几何信息,在数字城市构建中具有重要的意义.本文利用机载倾斜摄影数据进行了三维建模和单斜片测量的应用研究与实验,初步实验表明,倾斜摄影数据应用于三维建模单斜片测量是可行的,具有较好的应用前景.     

基于集群计算机的海量航空数码影像并行处理 ——并行计算在航空数字摄影测量中的应用

航空数码影像的获取频率越来越快,同时数据量也越来越大,传统的基于串行计算的影像处理方式已很难满足高效率的生产需求和快速响应,因此必需采用并行计算来提高数据处理的效率。论述了一种基于集群计算机系统的海量航空数码影像并行处理方法,介绍了并行计算在航空数字摄影测量中的应用,并结合数字摄影测量原理和并行处理技术,提出了一种可满足快速响应需求的无控制影像镶嵌图快速制作方法。生产实践验证了并行方法的可行性和高效性,生产效率比传统数字摄影测量工作站提高了3-10倍。     

数字与解析摄影测量系统的集成应用初探

结合生产与开发实践,就城市大比例尺情况下,应用数字和解析摄影测量系统进行摄影测量生产的有关问题进行了初步分析,并讨论了数字与解析系统生产流程的优化与集成方式。     

全数字摄影测量技术在莫高窟崖面保护中的应用

随着计算机技术和测绘技术的不断发展,摄影测量发展到了全数字摄影测量阶段。作为摄影测量学的一门分支学科--近景摄影测量在建筑物的变形观测,动态监测、文物保护等工作中起着很重要的作用。通过对敦煌莫高窟崖面进行数字近景摄影测量,着重介绍利用全数字近景摄影测量技术获取大范围复杂地貌崖面的高精度立面地理空间数据的方法及在文物的维护、修复中的应用。     

无人机遥感技术在河湖岸线监管中的应用

为提高河湖管理效率,针对无人机遥感技术观测范围广、获取空间信息速度快等优点,在分析无人机遥感技术工作原理基础上,根据河湖水域岸线监管不同需求,从目前无人机的多种监测方式入手,结合岸线监管应用,分析适用于河湖监管的 3 种监测方式。具体应用结果表明：1)低空摄影技术适合于小面积河湖岸线日常巡察,获取航拍照片。2)常规摄影测量技术是将外业获取的影像、POS、控制点数据,采用 PhotoScan 软件生成高分辨率正射影像和数字表面模型,结合 GIS 软件,快速生成一些专题图,适合于中小型涉水侵占行为监测。3)倾斜摄影测量技术适合于大型涉水建筑监测,对涉水建筑构建真三维模型,精准获取违建区域面积、侵占防洪库容等几何信息。无人机遥感技术用于河湖岸线监测,能够有效制止侵占岸线的行为,为河湖岸线安澜提供技术支撑。     

多视影像的城市实景三维生产关键技术

鉴于传统的航空和卫星遥感手段主要针对城市建筑物顶部进行模型重建,而对地物侧面的三维重建一直缺少有效的解决方法,该文提出一套自动化实景三维模型生产流程和成果质量检测方法。利用倾斜摄影倾直两用低空相机技术,分别研究大区域高精度多视影像的获取、提高空中三角测量精度、城市实景三维模型构建等关键技术环节,并据此对全市数据成果进行了相应的分析,为倾斜摄影城市实景三维模型的生产提供参考和借鉴。     

JX4C DPS中IKONOS立体像对的一体化处理

本文简要介绍了IKONOS遥感卫星系统及其立体影像数据的特点,给出了IKONOS影像立体模型的构建原理与方法,探讨了IKONOS影像的区域网平差方案,对少控制或无控制测图做了初步分析。随后,描述了JX4C数字摄影测量工作站中对IKONOS立体影像从数据预处理、单模型定向、区域网平差到区域DLG、DEM/DSM、DOM等测绘产品生产的一体化处理流程。文章最后指出,以IKONOS为代表的高分辨率遥感影像在测绘领域的广泛应用标志着卫星摄影测量与制图时代的开始。     

无人机数字摄影测量系统的设计和应用

无人机数字摄影测量系统为适应城市规模化测绘生产需要而设计开发,项目从机体设计、航线设计、通讯设计、监控设计、数据处理等各个层面,对航空摄影的原理、方法及相关参数进行了深入探讨和简要总结;项目进行了自动驾驶实验、超视距飞行实验、控制飞行实验、发动机空中停车紧急处理实验、干扰实验等常规实验,完成了数百平方公里摄影任务,实现了无人机摄影测量一体化的整合集成;应用结果表明,该系统具有“三高一低”的重要特性（高机动性、高分辨率、高度集成、低成本）,而且更加适应城市规模化测绘生产需要.     

Complete classification of raw LIDAR data and 3D reconstruction of buildings

LIDAR (LIght Detection And Ranging) data are a primary data source for digital terrain model (DTM) generation and 3D city models. This paper presents a three-stage framework for a robust automatic classification of raw LIDAR data as buildings, ground and vegetation, followed by a reconstruction of 3D models of the buildings. In the first stage the raw data are filtered and interpolated over a grid. In the second stage, first a double raw data segmentation is performed and then geometric and topological relationships among regions resulting from segmentation are computed and stored in a knowledge base. In the third stage, a rule-based scheme is applied for the classification of the regions. Finally, polyhedral building models are reconstructed by analysing the topology of building outlines, building roof slopes and eaves lines. Results obtained on data sets with different ground point density, gathered over the town of Pavia (Italy) with Toposys and Optech airborne laser scanning systems, are shown to illustrate the effectiveness of the proposed approach.     

基于扫描激光测距数据的建筑物三维重建

建筑物的三维信息是重要的基础地理信息,可以应用于城市的规划、管理等方面,而机载激光扫描测距系统在城市建筑物的三维重建方面具有重要的应用价值。针对我国自行研制的机载激光扫描测距数据提出了一套利用稀疏激光测距数据自动提取建筑物三维信息的方法。首先根据测量的激光距离和相应的姿态、位置信息计算出激光采样点的三维位置,进而可以生成城市的数字表面模型(DSM)和城市的数字地面模型(DTM),依据它们能准确地提取出建筑物的轮廓信息,最后根据建筑物具有规则的形状这个特点来对建筑物的轮廓线进行规则化处理而最终恢复建筑物的三维信息。通过对北京城市北部地区的实际处理,说明了该方法的可行性。     

图形图像融合的海量建筑绘制

目的 城市3维模型数据海量且结构复杂,缺乏一个高效完善的可视化系统往往是影响数字城市应用的瓶颈之一。通常利用多层次细节（LOD）与调度算法减少每一帧绘制的数据量来提高绘制效率,当场景规模足够大时,即使采用复杂的优化算法也难以取得较好的效果。为此,本文在传统算法基础上,提出一种图形图像融合的海量建筑物场景绘制方法。方法 提出并采用视域分级绘制策略,将视椎体平行分割为感兴趣区域、次感兴趣区域和非感兴趣区域,感兴趣区域采用图形实时绘制方法,使用离屏渲染技术将次感兴趣和非感兴趣区域绘制在纹理图像中,每一帧绘制完成后将二者进行顾及深度信息的融合,实现完整场景渲染。结果 使用公开的纽约市区CityGML文件作为实验数据,数据包含了118 195个LOD1和LOD2级别的建筑物模型。分别构建多组不同建筑数量的场景进行帧率统计实验,绘制帧率都达到20帧/s以上。算法实现了视觉无损失的场景完整渲染,并与Cesium平台进行对比实验,证明算法有效且系统运行流畅。结论 图形图像融合的绘制方法,既保持了图形渲染的漫游连续性,同时也具有图像渲染的场景复杂度无关的优点。实验结果表明,针对大规模的低分辨率建筑模型场景,算法可以有效提高系统的渲染能力,在性能相对较低的硬件条件下也能实现海量建筑物实体模型的流畅漫游,并达到视觉无损失的场景完整绘制。     

城市建筑物框架轮廓三维自动重构研究

建筑物是城市景观中一个重要组成部分,因此快速自动实现城市建筑物的三维可视化对于建立数码城市具有重大意义。针对传统三维建模人工劳动强度大、自动化程度低和花费高等问题,提出了一套自动化程度较高的基于线、面信息的城市建筑物框架轮廓快速三维重构方法。通过普通数码相机获取影像数据大大降低了实际应用成本,而且采用线面基元进行三维重构相比于经典的点云重构方法不仅提高了效率,而且获得了清晰的三维边缘轮廓。通过实验验证了方法的有效性和可行性。     

An automated vision-based method for rapid 3D energy performance modeling of existing buildings using thermal and digital imagery

Modeling the energy performance of existing buildings enables quick identification and reporting of potential areas for building retrofit. However, current modeling practices of using energy simulation tools do not model the energy performance of buildings at their element level. As a result, potential retrofit candidates caused by construction defects and degradations are not represented. Furthermore, due to manual modeling and calibration processes, their application is often time-consuming. Current application of 2D thermography for building diagnostics is also facing several challenges due to a large number of unordered and non-geo-tagged images. To address these limitations, this paper presents a new computer vision-based method for automated 3D energy performance modeling of existing buildings using thermal and digital imagery captured by a single thermal camera. First, using a new image-based 3D reconstruction pipeline which consists of Graphic Processing Unit (GPU)-based Structure-from-Motion (SfM) and Multi-View Stereo (MVS) algorithms, the geometrical conditions of an existing building is reconstructed in 3D. Next, a 3D thermal point cloud model of the building is generated by using a new 3D thermal modeling algorithm. This algorithm involves a one-time thermal camera calibration, deriving the relative transformation by forming the Epipolar geometry between thermal and digital images, and the MVS algorithm for dense reconstruction. By automatically superimposing the 3D building and thermal point cloud models, 3D spatio-thermal models are formed, which enable the users to visualize, query, and analyze temperatures at the level of 3D points. The underlying algorithms for generating and visualizing the 3D spatio-thermal models and the 3D-registered digital and thermal images are presented in detail. The proposed method is validated for several interior and exterior locations of a typical residential building and an instructional facility. The experimental results show that inexpensive digital and thermal imagery can be converted into ubiquitous reporters of the actual energy performance of existing buildings. The proposed method expedites the modeling process and has the potential to be used as a rapid and robust building diagnostic tool.     

Virtual 3D City Model for Navigation in Urban Areas

In this paper, we propose to study the integration of a new source of a priori information, which is the virtual 3D city model. We study this integration for two tasks: vehicles geo-localization and obstacles detection. A virtual 3D city model is a realistic representation of the evolution environment of a vehicle. It is a database of geographical and textured 3D data. We describe an ego-localization method that combines measurements of a GPS (Global Positioning System) receiver, odometers, a gyrometer, a video camera and a virtual 3D city model. GPS is often consider as the main sensor for localization of vehicles. But, in urban areas, GPS is not precise or even can be unavailable. So, GPS data are fused with odometers and gyrometer measurements using an Unscented Kalman Filter (UKF). However, during long GPS unavailability, localization with only odometers and gyrometer drift. Thus, we propose a new observation of the location of the vehicle. This observation is based on the matching between the current image acquired by an on-board camera and the virtual 3D city model of the environment. We also propose an obstacle detection method based on the comparison between the image acquired by the on-board camera and the image extracted from the 3D model. The following principle is used: the image acquired by the on-board camera contains the possible dynamic obstacles whereas they are absent from the 3D model. The two proposed concepts are tested on real data.     

基于结构信息的城市建筑物测量方法

提高城市建筑物测量过程的自动化程度是航空摄像测量研究的主要问题之一。文中提出了一种基于结构信息的城市建筑物测量方法。首先根据城市建筑物的结构信息,用几个相互独立的参数来描述建筑物的理想模型,并定义能推导出模型参数的图像变量,然后组合利用左右图像中各种信息获得图像变量的初始值,最后在一定准则下寻求城市建筑物的最佳测量位置。该文以平顶矩形建筑物为例详细讨论了它的一种实现算法。实验结果表明,这种方法与传统方法相比较,有较高的自动化程度,且测量精度能满足现有航空摄影测量的要求,有较大的发展和应用潜力。     

基于高空间分辨率与立体像对遥感数据的建筑物三维信息提取

准确获取建筑的三维分布信息对于城市规划与管理、灾害风险评估与防范以及灾后救助等都具有非常重要的意义。针对目前建筑物信息提取研究集中于二维平面信息提取,三维信息提取研究较少,且方法自动化程度较低,实用性和和推广性不足,提出了综合立体像对和高空间分辨率两种遥感数据进行建筑物三维信息提取的方法。首先,基于小波变换融合方法对GeoEye\|1高空间分辨率全色和多光谱影像进行融合,然后运用面向对象方法对融合后的高空间分辨率遥感影像进行建筑物基底轮廓提取,再利用IRS\|P5立体像对反演地物高度,最后通过数据整合获得研究区建筑物的三维空间分布。研究结果表明:该方法可以充分利用不同遥感数据的优势,获得较高的提取精度;研究所需数据容易获取,方法具有较好的可操作性和推广性。     

面向智慧城市的3维城市在线可视化

目的 3维城市可视化是智慧城市信息显示的基础,对城市信息的实时准确传递起着重要作用。而现有的3维城市可视化方法和系统存在两点局限性:一是数据模型不适合于海量建筑物显示;二是对整个城市采用单一绘制方式,而建筑物的纹理、结构、高度等特征相似,绘制结果容易引起视觉混淆,为此提出一种基于人类感知理论的3维城市在线可视化技术。方法在预处理阶段,系统采用建筑综合算法建立3维城市建筑物的多分辨率表示;在运行时刻,系统根据用户交互,自适应选择建筑物相应的层次进行显示。结果采用几个3维城市数据对系统进行了测试,实验结果证明,该系统有效地提高了3维城市绘制效率。Leverkusen城市的5 530座建筑物,绘制效率达到19.4帧/s。结论基于感知的3维城市多分辨率表示,有效提高了3维城市系统的显示效率以及用户获取信息的效率,同时提高了用户的交互效率。     

Automatic detection of building roofs from point clouds produced by the dense image matching technique

Three-dimensional (3D) spatial information of object points is a vital requirement for many disciplines. Laser scanning technology and techniques based on image matching have been used extensively to produce 3D dense point clouds. These data are used frequently in various applications, such as the generation of digital surface model (DSM)/digital terrain model (DTM), extracting objects (e.g., buildings, trees, and roads), 3D modelling, and detecting changes. The aim of this study was to extract the building roof points automatically from the 3D point cloud data created via the image matching techniques with optical aerial images (with red, green, and blue band (RGB) and infrared (IR)). In the first stage of the study, as an alternative to laser scanning technology, which is more expensive than optical imaging systems, the 3D point clouds were produced by matching high-resolution images using a Semi Global Matching algorithm. The normalized difference vegetation index (NDVI) values for each point were calculated using the spectral information (RGB + IR) in the 3D point cloud data, and the points that represented the vegetation cover were determined using these values. In the second stage, existing ground and non-ground points that were free of vegetation cover were determined within the point cloud. Subsequently, only the points on the roof of the building were detected automatically using the proposed algorithm. Thus, points of the roofs of buildings located in areas with different topographic characteristics were detected automatically detected using only images. It was determined that the average values of correctness (Corr), completeness (Comp), and quality (Q) of the pixel-based accuracy analysis metrics were 95%, 98%, and 93%, respectively, in the selected test areas. According to the results of the accuracy analysis, it is clear that the proposed algorithm is very successful in automatic extraction of building roof points.