共查询到19条相似文献，搜索用时 93 毫秒
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刘金辉 《测绘与空间地理信息》2013,(12):142-145
地面3维激光扫描仪是一种可进行全自动高精度立体扫描的先进仪器。其特点是可大面积高分辨率地快速获取被测对象表面的3维坐标数据,且所获取的数据具有实时、动态、高密度、高精度等优点。因而,激光扫描测量仪器的精度对工程应用的影响以及对3维点云模型的建立和精度影响至关重要。文章针对瑞格公司所生产的VZ400扫描仪在测量时,距离、入射角度、目标颜色几个因素对精度产生的影响进行研究。利用平面拟合的方法分析精度,得出了随着距离的增加,入射角的增大,会导致地面3维激光扫描仪测量精度降低的定性分析结论． 相似文献
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地面3维激光扫描仪是通过高速激光扫描测量的方法,大面积、高分辨率地快速获取被测对象表面的3维坐标数据,根据3维数据可以构建3维模型,为古建筑保护等提供数据依据。本文对地面3维激光扫描技术进行了简单探讨,通过具体实例研究分析其在古建筑保护中的应用。 相似文献
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3维激光扫描仪的全站化实现方法 总被引：4，自引：1，他引：3
3维激光扫描仪扫描得到的是目标点的相对坐标,无法直接满足需要大地坐标的工程应用的要求,且不同扫描站间点云数据的拼接非常麻烦.对这些问题,让3维激光扫描仪如全站仪一样能够直接获得大地坐标是一种理想的解决办法.分析了3维激光扫描仪的工作原理,介绍了扫描仪的极坐标系和直角坐标系并推导了其转换关系;在扫描仪中引入旋转平台和平台坐标系,推导了平台坐标系与扫描坐标系及大地坐标系之间的转换模型.在此基础上将扫描坐标转化为大地坐标,实现3维激光扫描仪的全站化. 相似文献
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采用地面激光扫描仪技术,分站式获取地铁盾构区间的3维点云数据,实现了盾构区间的3维模型重建。首先在盾构区间布设精密控制网,使用高精度全站仪和水准仪测量控制点的3维坐标;然后对盾构区间采用分段、自由设站的方式进行扫描,同时使用设站在精密控制点上的全站仪无棱镜模式测量标靶中心坐标。最后对每一扫描站的3维点云进行纠正,通过标靶的绝对空间坐标,实现多视点拼接,重建具有规则几何结构的盾构区间实体模型。结果表明,3维激光点云能够重建精细的地铁盾构区间模型,可用于地铁的设计方案展示、变形监测、轨道几何状态检测、调线调坡测量等。 相似文献
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由于树木生长的不规则性,造成对其各部分组件的测定与建模具有复杂性与挑战性。本文利用3维激光扫描仪获得树木的点云数据,对树干进行分离提取与3维建模研究。通过对四棵树的树干点云进行分离与提取、3维建模并计算其体积,得出由于遮挡等问题,全部提取树干点云难以实现。在提取主要树干点云的基础上,采用最大距离封装树干表面效果较好,封装表面采用网格修补可建立树干3维立体模型,实现体积计算。 相似文献
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3维激光扫描是基于近景扫描获取物体3维景观模型的一种新的激光测量技术,但在应用其扫描所得的点云数据使用配套软件Cyclone建立3维空间模型中又遇到了许多技术性问题,本文就此问题进行了探讨,并提出点云数据在MicroStation下处理的一些参考性方法。 相似文献
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3维激光扫描仪目前已成为空间数据获取的一种技术手段。针对输气管线隧道在运营中的形变情况,使用3维激光扫描仪定期对输气管线隧道的移动变形进行观测,并对采集的隧道内表面数据进行内业处理与分析,快速获得隧道管片变形量。开发输气管线隧道收敛变形监测系统,探讨内业处理时隧道断面点云切割厚度对分析精度的影响。为输气管线隧道的安全运营提供了技术保障和决策支持,同时也为其它相同类型隧道的收敛变形监测提供了经验。 相似文献
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建筑物的三维建模是城市三维建模和可视化的重要组成部分。本文提出一种基于点云数据与遥感图像的建筑物三维模型快速建模方法。首先,运用改进的RANSAC法从点云数据中提取建筑立面,根据立面区分平顶建筑与人字形屋顶建筑;在此基础上,进一步对建筑物的高度进行提取;之后,利用区域增长法从遥感图像中提取建筑物屋顶轮廓,利用形态学方法对提取出的轮廓进行规则化处理,并基于Freeman链码提取轮廓角点,得到规整的轮廓;最后,根据提取出的建筑高度属性对屋顶轮廓拉伸并进行纹理映射,实现对建筑物的三维重建。通过实例证明,提出的方法能快速、高效地实现建筑物三维模型的重建。 相似文献
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The accuracy of vertical position information can be degraded by various sources of error in digital aerial photogrammetry (DAP) based point clouds. To address this issue, we propose a relatively straightforward method for automated correction of such point clouds. This method can be used in conjunction with any 3D reconstruction method in which a point cloud is generated from a pair of aerial images. The crux of the method involves separately co-registering each DAP point cloud (formed by the overlap of two or more images) to a common airborne laser scanning (ALS) based digital terrain model. The proposed method has the following essential steps: (1) Ground surface patches are identified in the normalized DAP point clouds by selecting areas in which standard deviation of vertical height is low, (2) height differences between the DAP and ALS point clouds are calculated at these patches, and (3) a correction surface is interpolated from these height differences and is then used to rectify the entire DAP point cloud. The performance of the proposed method is verified using plot data (n = 250) from a forested study area in Eastern Finland. We observed that DAP data from the area corrected using our proposed method resulted in significant increases in prediction accuracy of key forest variables. Specifically, the root mean squared error (RMSE) values for dominant height predictions decreased by up to 23.2%, while the associated model R2 values increased by 16.9%. As for stem volume, RMSEs dropped by 20.6%, while the model R2 improved by 14.6%, respectively. Hence, prediction accuracies were almost as good as with ALS data. The results suggest that vertically misaligned DAP data, if rectified using an algorithm such as the one presented here, could deliver near ALS data quality at a fraction of the cost. 相似文献
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Automatic change detection and geo-database updating in the urban environment are difficult tasks. There has been much research on detecting changes with satellite and aerial images, but studies have rarely been performed at the street level, which is complex in its 3D geometry. Contemporary geo-databases include 3D street-level objects, which demand frequent data updating. Terrestrial images provides rich texture information for change detection, but the change detection with terrestrial images from different epochs sometimes faces problems with illumination changes, perspective distortions and unreliable 3D geometry caused by the lack of performance of automatic image matchers, while mobile laser scanning (MLS) data acquired from different epochs provides accurate 3D geometry for change detection, but is very expensive for periodical acquisition. This paper proposes a new method for change detection at street level by using combination of MLS point clouds and terrestrial images: the accurate but expensive MLS data acquired from an early epoch serves as the reference, and terrestrial images or photogrammetric images captured from an image-based mobile mapping system (MMS) at a later epoch are used to detect the geometrical changes between different epochs. The method will automatically mark the possible changes in each view, which provides a cost-efficient method for frequent data updating. The methodology is divided into several steps. In the first step, the point clouds are recorded by the MLS system and processed, with data cleaned and classified by semi-automatic means. In the second step, terrestrial images or mobile mapping images at a later epoch are taken and registered to the point cloud, and then point clouds are projected on each image by a weighted window based z-buffering method for view dependent 2D triangulation. In the next step, stereo pairs of the terrestrial images are rectified and re-projected between each other to check the geometrical consistency between point clouds and stereo images. Finally, an over-segmentation based graph cut optimization is carried out, taking into account the color, depth and class information to compute the changed area in the image space. The proposed method is invariant to light changes, robust to small co-registration errors between images and point clouds, and can be applied straightforwardly to 3D polyhedral models. This method can be used for 3D street data updating, city infrastructure management and damage monitoring in complex urban scenes. 相似文献
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Accurate 3D road information is important for applications such as road maintenance and virtual 3D modeling. Mobile laser scanning (MLS) is an efficient technique for capturing dense point clouds that can be used to construct detailed road models for large areas. This paper presents a method for extracting and delineating roads from large-scale MLS point clouds. The proposed method partitions MLS point clouds into a set of consecutive “scanning lines”, which each consists of a road cross section. A moving window operator is used to filter out non-ground points line by line, and curb points are detected based on curb patterns. The detected curb points are tracked and refined so that they are both globally consistent and locally similar. To evaluate the validity of the proposed method, experiments were conducted using two types of street-scene point clouds captured by Optech’s Lynx Mobile Mapper System. The completeness, correctness, and quality of the extracted roads are over 94.42%, 91.13%, and 91.3%, respectively, which proves the proposed method is a promising solution for extracting 3D roads from MLS point clouds. 相似文献
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利用点云切片提取技术分析桥梁形变 总被引：1，自引：1，他引：0
三维激光扫描技术作为近年来发展迅速的测绘手段,在桥梁健康监测中,已经成为监测技术的重要组成部分。本文以武汉市某跨江大桥为例,首先采用Trimble SX10三维激光扫描仪对桥梁进行长期监测扫描,并对桥梁钢结构和桥墩的点云进行切片;然后在Trimble Business Center 和 Trimble RealWorks软件的帮助下对每期的扫描点云进行处理,提取桥拱断面点坐标并对桥墩切片点云进行最佳垂直圆柱体拟合,获取拟合平面中心点坐标;最后对比分析每期特征点平面坐标的偏差和三维偏移量。本文研究成果验证了三维激光扫描仪在桥梁变形监测中的可行性,丰富了桥梁监测数据的表现形式,可以为相关研究提供依据和参考。 相似文献
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纹理映射技术作为获取具有丰富纹理信息的真彩色点云的有效手段，正以其独特的优势广泛地应用于众多行业领域。研究了一种利用三维激光扫描仪与外置数码相机联合标定解算多张影像位姿并获取全景真彩色点云的方法。其基本思想是利用摄像机与激光扫描仪固有的相对位置姿态，通过对首张影像进行标定得到其位置姿态后，利用摄像机空间旋转的几何特性，根据首张影像的位姿获取其余影像的位姿，继而完成多张影像的纹理映射，获取全景彩色点云。对比目前主流的全景影像纹理映射算法，该算法在精度与效率上均有一定提高。对多种点云数据进行纹理映射实验，结果表明，该方法能够快速准确地获取真三维全景彩色点云，为三维精细化建模提供了数据基础。 相似文献
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With the wide use of laser scanning technology, point cloud data collected from airborne sensors and terrestrial sensors are often integrated to depict a complete scenario from the top and ground views, even though points from different platforms and sensors have quite different densities. These massive point clouds with various structures create many problems for both data management and visualization. In this article, a hybrid spatial index method is proposed and implemented to manage and visualize integrated point cloud data from airborne and terrestrial scanners. This hybrid spatial index structure combines an extended quad‐tree model at the global level to manage large area airborne sensor data, with a 3‐D R‐tree to organize high density local area terrestrial point clouds. These massive point clouds from different platforms have diverse densities, but this hybrid spatial index system has the capability to organize the data adaptively and query efficiently, satisfying the requirements for fast visualization. Experiments using point cloud data collected from the Dunhuang area were conducted to evaluate the efficiency of our proposed method. 相似文献
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针对现有三维点云模型重建对象化和结构化信息缺失的问题,提出一种基于图模型的二维图像语义到三维点云语义传递的算法。该算法利用扩展全卷积神经网络提取2D图像的室内空间布局和对象语义,基于以2D图像超像素和3D点云为结点构建融合图像间一致性和图像内一致性的图模型,实现2D语义到3D语义的传递。基于点云分类实验的结果表明,该方法能够得到精度较高的室内三维点云语义分类结果,点云分类的精度可达到73.875 2%,且分类效果较好。 相似文献