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1.
提出了顾及多面片建筑物模型拓扑关系的边界提取方法。针对多面片建筑物的特点并基于最小二乘法,设计了一套适合多面片建筑物的边界规则化方法,并生成了3维建筑物模型。实验证明,本文方法对于多面片建筑物模型的3维自动重建都是可行和有效的。  相似文献   

2.
数字表面模型的建筑物容积率提取   总被引:1,自引:0,他引:1  
针对阴影长度和阴影面积法计算建筑物容积率误差较大的情况,该文利用航空影像密集匹配生成的点云数据逐点内插生成数字表面模型,提取建筑物三维信息,同时对于复杂建筑物屋顶,利用坡度滤波将其分割成为高度不同的面片,计算每一块屋顶的层数,从而得到较为准确的建筑总面积。实验证明,利用本文方法得到的建筑物容积率准确率高,且具有较高鲁棒性和使用价值。  相似文献   

3.
针对已分割出的建筑物立面,提出了以基尼系数作为损毁指数对倾斜航空影像中建筑物立面损毁检测的方法。该方法首先通过改进的k-means算法分割出建筑物立面的门窗和墙面,然后利用Canny算法对分割影像进行边缘检测提取统计特征,最后利用经济学中的基尼系数来判断建筑物立面是否损毁。实验结果表明,本文方法在没有先验信息的情况下仅利用单时相倾斜航空影像就能简单高效地判定建筑物立面损毁。  相似文献   

4.
针对航空影像中目标提取的困难,提出了一种基于可变模板的航空影像中建筑物提取方法,并针对几种比较典型的建筑物,详细讨论了模板的设计、目标初始参数的获取及模板最优参数求解等几个关键性的问题。采用这种方法进行航空影像中目标的提取时,可以将影像中的多种信息和人的识别能力进行有效的融合,因而能够达到可靠地提取影像中目标的目的。作为一种有效的优化求解方法,模拟退火被用于目标提取的优化过程。为了验证这种方法提取航空影像中目标的能力,给出了利用可变模板提取航空影像中几种不同类型的建筑物的例子  相似文献   

5.
许浩  程亮  伍阳 《测绘通报》2020,(6):104-110
面向数字城市和智慧城市建设急需城市建筑三维模型支撑的需要,本文基于机载LiDAR数据,以“顾及平整性的屋顶面片分割—屋顶层间连接—三维模型重建”为脉络,提出了一种采用层间连接和平滑策略的建筑屋顶三维模型重建方法。在屋顶面片提取过程中,充分顾及了屋顶面片的平整性;并在屋顶面片平整基础上,提出层间连接点的概念,以实现高效、快速的模型重建工作。试验部分,本文从屋顶面片重建完整率与正确率、重建几何精度及建筑物高程对于重建的影响3个方面作了较为详尽的评价与分析,并在国际摄影测量与遥感学会标准数据集支撑下,与国际同行进行试验对比。试验结果表明,建筑屋顶重建的完整率和正确率分别达到90%和95%;在偏移距离评价方面,平均偏移距离和标准差最优分别达0.05 m和0.18 m。因此,本文方法可有效完成建筑屋顶三维模型重建,重建模型准确度高、完整性好。  相似文献   

6.
李乐林  江万寿 《测绘通报》2013,(10):23-25,29
针对传统LiDAR点云建筑物三维重建方法中基于平面假设的面片提取思想的局限性,基于建筑物等高线特性,研究建筑物等高线分族过程,通过对等高线形状的识别达到对建筑物屋顶模型的识别,使得重建的屋顶类型不再局限于平面屋顶形式,提高了重建的自动化程度。  相似文献   

7.
对于某些复杂的物体而言,由于纹理简单、结构复杂,通常很难采用匹配密集点云或基于模型库的方法进行重建。介绍主要基于序列影像和积分的思想进行重建,可以利用尽可能多的相似多边形面片叠加实现对复杂物体的形体趋近。通过在复杂物体周围布设一定数量的控制点,可以利用自标定算法获取精确的相机内参数和影像方位元素,从而实现复杂物体的高精度重建。  相似文献   

8.
提出一种结合点云分割和扫描光线重建的建筑物立面遮挡部分点云恢复方法。该方法首先分割建筑面片,然后通过重建的扫描光线探测遮挡物点,并求其与建筑物面片的交点,从而在保持原始采样间隔的情况下自动恢复遮挡部分点云。试验结果表明,该方法能较好地恢复遮挡部位点云。  相似文献   

9.
LiDAR数据与正射影像结合的三维屋顶模型重建方法   总被引:1,自引:0,他引:1  
为提高三维屋顶模型重建的准确性与定位精度,本文集成机载LiDAR数据与正射影像,以“屋顶面片提取-屋脊线生成-三维屋顶重建”为框架,提出了三角形簇和三角形动态传播相结合的屋顶面片提取策略.基于LiDAR数据和影像的屋脊线精确提取算法,有效挖掘影像高分辨率特性和LiDAR数据高程点云特性的互补优势,实验证明了算法的优越性.  相似文献   

10.
高分辨率遥感影像建筑物提取是摄影测量与遥感领域的一个热门研究主题。本文综合利用影像分割、基于图的数学形态学top-hat重建技术,提出了面向对象的形态学建筑物指数OBMBI,并将其应用于高分辨率遥感影像建筑物提取。首先,建立像素-对象-图节点的双向映射关系;然后,基于图的白top-hat重建和上述映射关系来构建OBMBI图像;接着,对该OBMBI图像二值化、矢量化以获取建筑物多边形;最后,对结果进行后处理优化。使用一景航空、一景卫星全色影像对本文方法和PanTex方法进行性能测试。试验表明,本文方法的建筑物提取精度显著的优于PanTex方法。其中,本文方法平均比PanTex方法的正确率高9.49%、完整率高11.26%、质量高14.11%。  相似文献   

11.
基于多源数据的拼接型房屋三维重建方法研究   总被引:2,自引:0,他引:2  
提出了结合房屋矢量数据、航空影像和点云数据的拼接型房屋(由平顶房、人字型和四坡型房屋组成)自动三维重建算法。算法重点研究了基于点云数据和影像特征提取的拼接型房屋屋脊线检测,并利用其对拼接型房屋组成的模型进行拆分;对于人字型和四坡型房屋组成模型,结合矢量数据和屋脊线,利用几何约束条件自动寻找房屋组成模型的屋檐线,从而获得拼接型房屋组成模型的完整分割;最后通过点云数据的屋顶平面解算其组成房屋模型的参数,最终实现整个拼接型房屋的三维重建。实验数据证明,该方法能较好地实现拼接型房屋的几何模型自动重建。  相似文献   

12.
李鹏程  邢帅  徐青  周杨  刘志青  张艳  耿迅 《遥感学报》2014,18(6):1237-1246
利用机载LiDAR点云数据进行建筑物重建是当今摄影测量与遥感领域的一个热点问题,特别是复杂形状建筑物模型的精确自动构建一直是一个难题。本文提出一种基于关键点检测的复杂建筑物模型自动重建方法,采用RANSAC法与距离法相结合的分割方法自动提取建筑物屋顶各个平面的点云,并利用Alpha Shape算法提取出各个平面的精确轮廓,根据屋顶平面之间的空间拓扑关系分析建筑物的公共交线特征,在此特征约束下对提取的初始关键点进行修正,最终重建出精确的建筑物3维模型。选取不同类型复杂建筑物与包含复杂建筑物的城市区域点云进行实验,结果表明该算法具有较强实用价值。  相似文献   

13.
This paper presents a method for extracting building roof contours from digital images collected over urban landscapes. The proposed method utilizes an energy function based on snakes that represents building roof contours in digital images and is optimized with a dynamic programming (DP) algorithm. Because most building roof contours are characterized by rectilinear sides that intercept at right angles, appropriate geometric constraints are enforced in the previously reported snake-based energy function. The main advantage of using the DP algorithm for optimizing the proposed snake-based energy function is its better radius of convergence compared to that typically obtained in the original solution based on variational approaches. Experimental evaluation, which included visual inspections and numerical analyses, was performed using real data, and the obtained results demonstrated that the proposed method has significant potential for successfully extracting building roof contours from digital images.  相似文献   

14.
Highly detailed 3D urban terrain models are the base for quick response tasks with indispensable human participation, e.g., disaster management. Thus, it is important to automate and accelerate the process of urban terrain modeling from sensor data such that the resulting 3D model is semantic, compact, recognizable, and easily usable for training and simulation purposes. To provide essential geometric attributes, buildings and trees must be identified among elevated objects in digital surface models. After building ground-plan estimation and roof details analysis, images from oblique airborne imagery are used to cover building faces with up-to-date texture thus achieving a better recognizability of the model. The three steps of the texturing procedure are sensor pose estimation, assessment of polygons projected into the images, and texture synthesis. Free geographic data, providing additional information about streets, forest areas, and other topographic object types, suppress false alarms and enrich the reconstruction results.  相似文献   

15.
Photorealistic visualization combines 3-D geometric models with their texture images to render the virtual world. This paper points out that the texture images should be radiometrically corrected to achieve a true realistic appearance. Such a correction should include not only the color adjustment among images of the same object, but also the shade variation caused by the illumination change. The objective of this study is to correct the input texture images such that their shade varies when being rendered under different illumination directions. To achieve this goal we first apply the specular-to-diffuse mechanism based on the dichromatic reflection model to remove the specular component from the texture image. The resultant diffusion-only image then undergoes a shade correction to produce a normalized shade-free texture image. In the final step, shades under any illumination are produced to achieve a true photorealistic effect. Presented in the paper are the principles and methods for such corrections, along with a performance evaluation based on the graphic and numerical results for roof texture images.  相似文献   

16.
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   

17.
The purpose of this study is to derive vectoral 3D roof planes from the LIDAR point cloud of the detected buildings. For segmentation of the LIDAR point cloud, the RANSAC algorithm has been used. Because the RANSAC algorithm is sensitive to the used parameters, and results in over- or under-segmentation of the clusters, a refinement method has been proposed. The detection of roof planes has been improved with use of the refinement method. Therefore, similar plane surfaces have been combined, followed by the region-growing algorithm, to split the under-segmented plane surfaces. The digitization of the roof boundaries is performed using the alpha-shapes algorithm, followed by line fitting to generalize the roof edges. The quality assessment has been done using the reference vector dataset with comparison using four different criteria.  相似文献   

18.
赵传  张保明  陈小卫  郭海涛  卢俊 《测绘学报》2017,46(9):1123-1134
从LiDAR数据中高精度地提取建筑物屋顶面是构建屋顶面拓扑关系、实现建筑物三维模型重建的关键。本文针对现有算法提取复杂建筑物屋顶面适应性较差、精度较低等问题,提出了一种利用点云邻域信息的建筑物屋顶面高精度自动提取方法。通过主成分分析计算点云特征,构建特征直方图,选取可靠种子点;利用提出的局部点云法向量分布密度聚类算法聚类种子点,快速准确地提取初始屋顶面片;构建基于邻域信息的投票模型,有效地解决屋顶面竞争现象。试验结果表明,本文方法可自动、高精度地提取屋顶面,对不同复杂程度的建筑物具有较好的适应性,能为建筑物三维模型重建提供可靠的屋顶面信息。  相似文献   

19.
Roof plane segmentation is a complex task since point cloud data carry no connection information and do not provide any semantic characteristics of the underlying scanned surfaces. Point cloud density, complex roof profiles, and occlusion add another layer of complexity which often encounter in practice. In this article, we present a new technique that provides a better interpolation of roof regions where multiple surfaces intersect creating non-manifold points. As a result, these geometric features are preserved to achieve automated identification and segmentation of the roof planes from unstructured laser data. The proposed technique has been tested using the International Society for Photogrammetry and Remote Sensing benchmark and three Australian datasets, which differ in terrain, point density, building sizes, and vegetation. The qualitative and quantitative results show the robustness of the methodology and indicate that the proposed technique can eliminate vegetation and extract buildings as well as their non-occluding parts from the complex scenes at a high success rate for building detection (between 83.9% and 100% per-object completeness) and roof plane extraction (between 73.9% and 96% per-object completeness). The proposed method works more robustly than some existing methods in the presence of occlusion and low point sampling as indicated by the correctness of above 95% for all the datasets.  相似文献   

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