CN114119902A - Building extraction method based on unmanned aerial vehicle inclined three-dimensional model - Google Patents

Building extraction method based on unmanned aerial vehicle inclined three-dimensional model Download PDF

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CN114119902A
CN114119902A CN202111394175.1A CN202111394175A CN114119902A CN 114119902 A CN114119902 A CN 114119902A CN 202111394175 A CN202111394175 A CN 202111394175A CN 114119902 A CN114119902 A CN 114119902A
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building
point cloud
cloud data
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李德贵
尚永衡
陈钢
沈正伟
尹建伟
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Deqing Institute Of Advanced Technology And Industry Zhejiang University
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Deqing Institute Of Advanced Technology And Industry Zhejiang University
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    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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    • G06T17/10Constructive solid geometry [CSG] using solid primitives, e.g. cylinders, cubes
    • GPHYSICS
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    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T19/00Manipulating three-dimensional [3D] models or images for computer graphics
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    • G06T2207/10Image acquisition modality
    • G06T2207/10028Range image; Depth image; 3D point clouds
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30181Earth observation
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Abstract

The invention provides a building extraction method based on an unmanned aerial vehicle inclined three-dimensional model, which comprises the following steps: step 1: firstly, acquiring a high-precision real-scene three-dimensional image and forming a three-dimensional model by utilizing unmanned aerial vehicle oblique photogrammetry; step 2: classifying and filtering the point cloud data; and step 3: carrying out image conversion on the classified and filtered point cloud data; and 4, step 4: deleting the building wall surface composition nodes and reserving the building main body top surface composition nodes; and 5: connecting the rest main body nodes in the step 4 end to end and forming a building characteristic outline; step 6: and (5) overlapping and reducing the building characteristic contour in the step (5) in a coordinate system of the three-dimensional model, and finally obtaining the contour of the target building. The method has high automation degree, the whole process can be completed only by one person, the extracted building has high precision and low cost, and the technical problem that the existing building cannot be in an inclined three-dimensional scene can be solved.

Description

Building extraction method based on unmanned aerial vehicle inclined three-dimensional model
Technical Field
The invention belongs to the technical field of unmanned aerial vehicle inclination three-dimensional models, and particularly relates to a building extraction method based on an unmanned aerial vehicle inclination three-dimensional model.
Background
With the continuous development of computer technology and low-altitude inclined three-dimensional system platform technology, a brand-new method for acquiring three-dimensional reconstruction of urban scenes appears: oblique three-dimensional photography; the oblique photography is that a plurality of sensors are carried on the same aircraft platform, images are collected from five different angles such as one vertical angle, four oblique angles and the like, the three-dimensional structure of a target object is recovered based on a three-dimensional modeling method of multi-view images, and meanwhile, the surface texture information of a three-dimensional model is obtained. In recent years, with the increasing maturity of unmanned aerial vehicle technology, the cost of acquiring aerial image data is also greatly reduced. Therefore, the construction of urban three-dimensional scenes based on multi-view oblique images becomes more extensive.
The existing building outline extraction method based on the aerial image of the common unmanned aerial vehicle comprises the steps of generating three-dimensional point cloud by using a space-three combined dense matching method, filtering the point cloud, and detecting a building from the point cloud. And after the wall surface of the detected building is deleted, extracting the rough outline of the building from the top surface information of the building. And (3) on the building rough contour serving as a buffer area overlapped and spliced image, utilizing the building rough contour as shape prior information, and carrying out evolution in the buffer area by using a level set algorithm to finally obtain the building contour.
The building precision that prior art obtained through the mode that ordinary unmanned aerial vehicle aerial photograph image drawed the building profile is low, has reduced the precision that the building profile was drawed to be difficult for using widely.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention aims to provide a building extraction method based on an unmanned aerial vehicle inclined three-dimensional model, which can obtain a high-precision three-dimensional model and then extract high-precision building contour information, and the method improves the precision of building contour extraction; the invention solves the problems that the information precision of the image obtained by the existing method for extracting the outline of the building is low, and the precision of extracting the outline of the building is reduced, so that the method is not easy to popularize.
In order to achieve the purpose, the invention adopts the technical scheme that:
a building extraction method based on an unmanned aerial vehicle inclined three-dimensional model comprises the following steps:
step 1: firstly, acquiring a high-precision live-action three-dimensional image by utilizing unmanned aerial vehicle oblique photogrammetry, forming a live-action three-dimensional model through processing, then automatically extracting point cloud data of a building outline according to the live-action three-dimensional model, giving the point cloud data to a coordinate system, and cutting the point cloud data with coordinates into a plurality of small slices;
step two 2: classifying and filtering interference sundries in the point cloud data obtained in the step 1, wherein the interference sundries comprise trees, water bodies and cables, and finally obtaining the point cloud data of the building;
and step 3: carrying out image conversion on the classified and filtered building point cloud data, converting all the point cloud data obtained in the step 2 into images one by one, and obtaining an image corresponding to each slice;
and 4, step 4: deleting the building wall surface composition nodes and the highest points and the lowest points of the bulges or the depressions on the top surface of the building; reserving the top surface of the building main body to form a node;
and 5: connecting the building body nodes reserved in the step 4 end to end and forming a building characteristic outline;
step 6: and (5) overlapping and reducing the building characteristic contour in the step (5) in a coordinate system of the three-dimensional model, and finally obtaining the contour of the target building.
In the step 1, a coordinate system is given to the point cloud data: firstly, defining three directions of a building as length (X), width (Y) and height (Z) respectively, and carrying out a plurality of slicing treatments on the building in the three directions respectively; respectively connecting points in three directions of each small slice; and correspondingly processing the small slice connecting points on each surface of the building to finally obtain the point cloud data of the building.
The step 2 adopts a uniform sampling filtering mode, firstly, a seed grid is constructed, and critical points of buildings and interference impurities are marked into a plurality of seed points; and then, point cloud data is extracted, and when the extracted seed points coincide with the point positions of the building in the process of lifting the point cloud data, the point cloud is automatically shielded by a filtering algorithm, otherwise, the point cloud data is regarded as the building point cloud data.
Deleting the wall surface of the building by adopting a partition method in the steps 3, 4, 5 and 6; connecting the point cloud data by adopting a jump type connecting method; and beautifying the finally extracted building outline.
Compared with the prior art, the invention has the following beneficial effects:
the method has the advantages that the automation degree is high, a large amount of manual intervention is not needed, the whole process can be completed only by one person, the building extracted by the method is high in precision and low in cost, and the technical problem that the existing building cannot be in an inclined three-dimensional scene can be solved.
Drawings
Fig. 1 is a flowchart of a building extraction method based on an unmanned aerial vehicle inclined three-dimensional model according to an embodiment of the present invention.
Fig. 2 is a diagram of a live-action three-dimensional model.
Fig. 3 is a sectional view of a live-action three-dimensional model.
Fig. 4 is a building roof profile.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more clearly understood, the following further describes in detail a building extraction method based on an unmanned aerial vehicle tilted three-dimensional model by using an implementation case and with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, the invention provides a building extraction method based on an unmanned aerial vehicle inclined three-dimensional model, comprising the following steps:
step 1: firstly, a high-precision live-action three-dimensional image obtained by oblique photogrammetry of an unmanned aerial vehicle is utilized to form a live-action three-dimensional model; the high precision three-dimensional image processing generation is shown in fig. 2.
Step 2: and classifying and filtering the point cloud data.
And step 3: and (4) carrying out image conversion on the classified and filtered point cloud data, and finally generating a real-scene three-dimensional model tangent plane diagram as shown in fig. 3.
And 4, step 4: and deleting the building wall surface composition nodes and reserving the building main body top surface composition nodes.
And 5: and (4) connecting the rest body nodes in the step (4) end to end and forming a building characteristic outline.
Step 6: and (5) overlapping and reducing the building characteristic contour in the step (5) in a coordinate system of the three-dimensional model, and finally obtaining the contour of the target building. Finally, the contour diagram of the top surface of the building shown in fig. 4 is obtained.
The embodiments in the above description can be further combined or replaced, and the embodiments are only described as preferred examples of the present invention, and do not limit the concept and scope of the present invention, and various changes and modifications made to the technical solution of the present invention by those skilled in the art without departing from the design concept of the present invention belong to the protection scope of the present invention. The scope of the invention is given by the appended claims and any equivalents thereof.

Claims (4)

1.一种基于无人机倾斜三维模型的建筑物提取方法,其特征在于,包括以下步骤:1. a building extraction method based on UAV tilting three-dimensional model, is characterized in that, comprises the following steps: 步骤1:首先利用无人机倾斜摄影测量获取高精度实景三维图像,经过处理形成实景三维模型,然后根据实景三维模型自动提取建筑轮廓的点云数据并赋予坐标系,并将带坐标的点云数据切成为若干个小切片;Step 1: First, use the UAV oblique photogrammetry to obtain high-precision 3D images of the real scene, and then form a 3D model of the real scene after processing. Then, according to the 3D model of the real scene, the point cloud data of the building outline is automatically extracted and given a coordinate system, and the point cloud with the coordinates is automatically extracted. The data is cut into several small slices; 步骤二2:对步骤1中得到的点云数据对干扰杂物进行分类和滤波处理,所述的干扰杂物包括树木、水体和电缆,最终得到建筑物的点云数据;Step 2 2: Classify and filter the interfering debris on the point cloud data obtained in step 1, and the interfering debris includes trees, water bodies and cables, and finally obtain the point cloud data of the building; 步骤3:对经过分类和滤波后的建筑物点云数据进行图像转换,将步骤2中获得的全部点云数据逐个转换成图像,并获得每个切片所对应的图像;Step 3: Perform image conversion on the classified and filtered building point cloud data, convert all the point cloud data obtained in step 2 into images one by one, and obtain the image corresponding to each slice; 步骤4:删除建筑物墙体面组成节点及建筑物的顶面凸起或者凹陷的最高点和最低点;保留建筑物主体顶面组成节点;Step 4: Delete the highest and lowest points of the building wall surface and the highest and lowest points of the convex or concave top surface of the building; keep the main top surface of the building to form the nodes; 步骤5:将步骤4中保留的建筑物主体节点进行首尾连接并形成建筑物特征轮廓;Step 5: Connect the main node of the building retained in Step 4 to the end to form the building feature outline; 步骤6:将步骤5中的建筑物特征轮廓在三维模型的坐标系统中进行叠加和还原,最终获得目标建筑物的轮廓。Step 6: Superimpose and restore the feature contour of the building in step 5 in the coordinate system of the three-dimensional model, and finally obtain the contour of the target building. 2.根据权利要求1所述的一种基于无人机倾斜三维模型的建筑物提取方法,其特征在于:所述步骤1中对点云数据赋予坐标系:首先将建筑物的三个方向分别定义为长(X)、宽(Y)、高(Z);分别对三个方向上的建筑物进行若干个切片处理;分别对每一个小切片的三个方向上进行做连接点;在对建筑物每个面上的小切片连接点做相应的处理,最终得到建筑物的点云数据。2. a kind of building extraction method based on UAV tilting three-dimensional model according to claim 1, is characterized in that: in described step 1, point cloud data is given coordinate system: first, three directions of building are respectively Defined as length (X), width (Y), height (Z); several slices are processed for buildings in three directions; connection points are made in three directions of each small slice; The small slice connection points on each surface of the building are processed accordingly, and finally the point cloud data of the building is obtained. 3.根据权利要求1所述的一种基于无人机倾斜三维模型的建筑物提取方法,其特征在于:所述步骤2中采用的是均匀采样滤波方式,首先构建种子网格,将建筑物和干扰杂物的临界点标记呈若干个种子点;接下来就是提取点云数据,在提起点云数据的过程中,当提取的种子点与建筑物的点位置相重合时,滤波算法自动屏蔽此点云,反之就认为是建筑物点云数据。3. a kind of building extraction method based on UAV tilting three-dimensional model according to claim 1, is characterized in that: what adopts in described step 2 is the uniform sampling filtering mode, first constructs seed grid, and building And the critical point mark of interfering debris is a number of seed points; the next step is to extract the point cloud data, in the process of picking up the point cloud data, when the extracted seed point coincides with the point position of the building, the filtering algorithm automatically shields This point cloud, on the contrary, is considered as building point cloud data. 4.根据权利要求1所述的一种基于无人机倾斜三维模型的建筑物提取方法,其特征在于:所述步骤3、步骤4、步骤5、步骤6中采用分割法删除建筑物墙面;采用跳跃式的连接方法对点云数据进行连接;对最终提取到的建筑物轮廓进行美化处理。4. a kind of building extraction method based on UAV tilting three-dimensional model according to claim 1, is characterized in that: in described step 3, step 4, step 5, step 6, adopt segmentation method to delete building wall surface ; Use the jump connection method to connect the point cloud data; beautify the final extracted building outline.
CN202111394175.1A 2021-11-23 2021-11-23 Building extraction method based on unmanned aerial vehicle inclined three-dimensional model Pending CN114119902A (en)

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Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114926602A (en) * 2022-04-13 2022-08-19 湖北省国土测绘院 Building single-body method and system based on three-dimensional point cloud
CN115019007A (en) * 2022-08-05 2022-09-06 烟台市地理信息中心 Three-dimensional model making method and system based on unmanned aerial vehicle intelligent air route planning
CN115272864A (en) * 2022-08-16 2022-11-01 安徽大学 Real-scene three-dimensional building intelligent extraction method based on unmanned aerial vehicle aerial photography
CN117272491A (en) * 2023-11-21 2023-12-22 广东广宇科技发展有限公司 Rapid modeling method, equipment and medium based on AI drawing model

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110879978A (en) * 2019-11-13 2020-03-13 广西中煤地质有限责任公司 Building contour line automatic extraction method of unmanned aerial vehicle oblique photography three-dimensional model

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110879978A (en) * 2019-11-13 2020-03-13 广西中煤地质有限责任公司 Building contour line automatic extraction method of unmanned aerial vehicle oblique photography three-dimensional model

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114926602A (en) * 2022-04-13 2022-08-19 湖北省国土测绘院 Building single-body method and system based on three-dimensional point cloud
CN114926602B (en) * 2022-04-13 2023-03-31 湖北省国土测绘院 Building singleization method and system based on three-dimensional point cloud
CN115019007A (en) * 2022-08-05 2022-09-06 烟台市地理信息中心 Three-dimensional model making method and system based on unmanned aerial vehicle intelligent air route planning
CN115272864A (en) * 2022-08-16 2022-11-01 安徽大学 Real-scene three-dimensional building intelligent extraction method based on unmanned aerial vehicle aerial photography
CN117272491A (en) * 2023-11-21 2023-12-22 广东广宇科技发展有限公司 Rapid modeling method, equipment and medium based on AI drawing model
CN117272491B (en) * 2023-11-21 2024-05-31 广东广宇科技发展有限公司 Rapid modeling method, equipment and medium based on AI drawing model

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Application publication date: 20220301