CN116612242A - Urban road three-dimensional modeling method based on point cloud data - Google Patents

Abstract

The invention proposes a three-dimensional modeling method of urban roads based on point cloud data, and designs and completes the construction of three-dimensional models of urban roads and components. Firstly, the vehicle-mounted laser scanner is used to collect the road and the components on both sides of the road, and the full coverage of all the main roads in the pilot area is achieved, and the vehicle-mounted point cloud data collection is completed; then, the EPS mapping platform is used to collect the 3D vector data of the road and various components , using the collected 3D vector data as the data basis for urban 3D modeling; finally, use 3DSMax software to build a component template library and urban road surface model, and associate and fuse the 3D model and vector information to form an informationized single model. The method of the present invention can not only ensure the integrity and authenticity of the scene, but also reduce the operation time and cost, realize the seamless integration between various models, and the completed model has high precision and can fully express road and component information, which is beneficial to The refined management of 3D cities is of great significance, and it can be used as a certain technical support for my country's geographic information system.

Description

A 3D modeling method of urban roads based on point cloud data

technical field

The invention belongs to the technical field of three-dimensional reconstruction, and in particular relates to a three-dimensional modeling method for urban roads based on point cloud data.

Background technique

With the in-depth development of projects such as "Real 3D China" and "Smart City Construction", two-dimensional data can no longer meet the application needs of various sectors of society. It can only perform macroscopic and brief statistics and analysis, and it is difficult to analyze environmental details. Query, count, and analyze data. The full-element reality model is a high-definition, high-precision structured and materialized result. It has geographic elements in the same space and associated full-space, full-element, and real-scene 3D models, which can effectively describe the geometry, topology, and semantics of ground objects. And other features, realize the transformation from two-dimensional data to three-dimensional space, and provide an effective means for urban management and planning. Urban road modeling is one of the important contents of constructing urban 3D scenes. The traditional modeling method is to use topographic maps and topographic survey data files as data sources, and combine road details and texture information obtained by field personnel to model, but this Such data can only express discrete point and line features, and cannot completely and accurately reflect the actual road conditions.

Vehicle-mounted laser scanning technology is a new surveying and mapping product. With the movement of the vehicle body, it can obtain surface three-dimensional space and texture information of buildings, roads, vegetation, etc. It has irreplaceable advantages such as high precision, rich information, high efficiency and fast speed. An important means of holographic mapping. In this paper, the vehicle-mounted point cloud data is used as the data source for urban road real scene modeling, and the EPS three-dimensional mapping software is used to collect three-dimensional vector data, and the 3DS Max modeling software is used to construct the scene of the extracted three-dimensional vector data; and then the local point cloud data is used as the Refer to the model of the parts, and restore the parts based on the real texture and the size of the field survey; finally, use the 3DS Max software to merge the urban road and the urban part models on both sides of the road to complete the 3D real scene model of the road.

To sum up, in view of the low precision and time-consuming problems of traditional road modeling, the present invention models roads and components based on point cloud data, and obtains high-precision, real, and beautiful 3D model data, which is beneficial to the construction of smart cities in my country. There's important meaning.

Contents of the invention

Aiming at the low precision and time-consuming problems of traditional road modeling, the present invention proposes a 3D modeling method for urban roads based on point cloud data, which ensures the integrity and authenticity of 3D scenes, reduces operating time and costs, and realizes The seamless combination of various models solves the problems of low model accuracy and incomplete information.

To achieve the above object, the present invention comprises the following steps:

S1: Use the vehicle-mounted laser scanner based on the AS900HL multi-platform lidar measurement system to collect point cloud data, calculate and correct the point cloud data collected by the field, and obtain point cloud data that meets the model accuracy index. Cloud data is used as a data source for 3D modeling of urban roads;

S2: Based on the point cloud data obtained in S1, use the EPS three-dimensional mapping software to collect three-dimensional vector data of the road, and obtain the three-dimensional vector data of all elements of the road;

S3: Classify the 3D vector data obtained in S2 according to roads and components, and use 3DS Max software to build a component template library based on point cloud data and panoramic photos;

S4: Based on 3D vector data, use 3D feature lines to build road models;

S5: Based on the 3DS Max software, according to the position and direction of the parts in the 3D vector data, put the parts in the template library into the 3D scene of the road, carry out the vector-model attribute association, and perform quality inspection and modification on the model to complete the urban road and 3D modeling of components.

2. a kind of urban road three-dimensional modeling method based on point cloud data according to claim 1, is characterized in that, described step S1 comprises the following steps:

(1) Before data collection, according to the road terrain in the test area, make preparations for scanning route planning and parking area planning. According to the division results of the task area and the survey report, the base station positions are reasonably arranged and static observations are carried out. The layout and observation of control points for accuracy verification and correction can be done before data collection, or can be laid out and collected based on point cloud data after the preliminary calculation of point cloud data.

(2) After the preparatory work is completed, route planning is carried out unit by unit according to the divided task units, and when the vehicle data is collected, the navigation collection is carried out according to the planned route. During the actual collection, the route should be adjusted according to the road conditions, weather and other factors on the spot.

(3) Solve and correct the point cloud data collected by the field; create a new project in the Copre post-processing software, add the original data to the project, and use the original point cloud data and trajectory data to solve to obtain 3D points Cloud data, register point cloud data with panoramic photos to obtain color point cloud data.

3. a kind of urban road three-dimensional modeling method based on point cloud data according to claim 1, is characterized in that, described step S2 comprises the following steps:

(1) Extraction of linear elements mainly includes two categories: road markings and road edges. When extracting road markings, first select the corresponding element code according to the type of markings, extract the geometric center position of road markings in point cloud data, and add nodes in places with large arcs to ensure the plane position and The accuracy of the elevation position;

(2) The extraction of road sidelines needs to be collected in a free view, draw straight lines in flat areas, add nodes in places with large arcs, and shorten the interval of sampling points in places with large elevation changes. During the extraction process, the viewing angle should be adjusted according to the point cloud data. Is the elevation correct. After extracting a section of road, it is necessary to check the degree of fit between the linear elements and the point cloud in the plane position and elevation position in the state of the top view and the perspective view, and move or encrypt the sampling points in places with deviations to maximize the extracted linear elements The degree is consistent with the field;

(3) Point elements are extracted including rods, boxes, cards and other components. For example, when collecting poles, you should refer to the panoramic image, take the center of the pole as the plane position, and take the ground elevation next to the pole as the elevation, and use the corresponding symbols such as street lights, probes, traffic lights, and electric poles to indicate, and fill in the number and top of the pole. Attributes such as absolute elevation, and different viewing angles should be adjusted during the collection process to ensure that the location elevation information of the final collected point features is accurate. The rest of the urban components need to use the corresponding element codes to extract the geometric center of the connection between the road component and the ground;

(4) When extracting area features, the 3D feature lines of area features should be closed on the plane and elevation, and filled with areas.

4. a kind of urban road three-dimensional modeling method based on point cloud data according to claim 1, it is characterized in that, city common parts are divided into bar class, box class, card class, tree class etc., and parts template library construction Including the production of white film and texture map, combined with point cloud data and the actual size of the ground objects in the field, using 3DS Max software to make white film, the modeling method mainly adopts polygonal modeling, spline modeling and compound object building Then, combined with the panoramic image, select photos with bright colors, good angles, clear and unobstructed photos, cut them, and make them into texture maps. Select the corresponding surface in 3DS Max software, and use the uvw map to complete the process. Model texture mapping.

5. a kind of urban road three-dimensional modeling method based on point cloud data according to claim 1, it is characterized in that, the construction scope of urban pavement model is from the sidewalk outermost edge on one side of the road to the sidewalk outermost edge on the other side of the road. The outside edge, including sidewalks. Using the linear elements such as road edge, land type boundary, and outer range line extracted from 3D vector data, the main road surface, sidewalk, and green flower bed and other element models are constructed.

6. the three-dimensional modeling method of a kind of urban road based on point cloud data according to claim 1, is characterized in that, according to the kind, actual position and direction of each component model, the model in the template storehouse is combined by automatic and semi-automatic Implanted into the 3D scene in a 3D way, call the model of the urban component elements from the model library, and according to the position and orientation information of each component in the 3D vector data, move and rotate the model in the component template library in 3DS Max Put it into the exact position in the 3D scene; the quality check of the 3D road model includes naming check, precision check, geometric data check, texture data check, and attribute data check.

From the above, the present invention aims at the problem of low accuracy of traditional road three-dimensional modeling, and proposes a three-dimensional modeling method of urban roads based on point cloud data, which improves the accuracy of the model, is beneficial to practical application, and provides my country's geographic information system with Some technical support is provided.

Description of drawings

The description of the summary of the present invention will become apparent and easily understood when taken in conjunction with the following drawings, in which:

Fig. 1 is a flow chart of an urban road modeling method based on point cloud data in the present invention.

Figure 2 is a colored point cloud data map.

Figure 3 is the rendering of the urban component model.

Figure 4 is the rendering of the urban pavement model.

Detailed ways

According to the steps shown in Figure 1, a method for modeling urban roads based on point cloud data in the present invention will be described in detail.

Step 1: Use the vehicle-mounted laser scanner based on the AS900HL multi-platform lidar measurement system to collect point cloud data. Include the following steps:

(1) Before data collection, according to the road terrain in the test area, make preparations for scanning route planning and parking area planning. According to the division results of the task area and the survey report, the base station positions are reasonably arranged and static observations are carried out. The layout and observation of control points for accuracy verification and correction can be done before data collection, or can be laid out and collected based on point cloud data after the preliminary calculation of point cloud data.

(2) After the preparatory work is completed, route planning is carried out unit by unit according to the divided task units, and when the vehicle data is collected, the navigation collection is carried out according to the planned route. During the actual collection, the route should be adjusted according to the road conditions, weather and other factors on the spot.

(3) Solve and correct the point cloud data collected by the field; create a new project in the Copre post-processing software, add the original data to the project, and use the original point cloud data and trajectory data to solve to obtain 3D points Cloud data, register point cloud data with panoramic photos to obtain color point cloud data.

Step 2: Based on the point cloud data obtained in S1, use the EPS three-dimensional mapping software to collect three-dimensional vector data of the road, and obtain the three-dimensional vector data of all elements of the road. The specific operation steps are as follows:

(1) Extraction of linear elements mainly includes two categories: road markings and road edges. When extracting road markings, first select the corresponding element code according to the type of markings, extract the geometric center position of road markings in point cloud data, and add nodes in places with large arcs to ensure the plane position and The accuracy of the elevation position;

(2) The extraction of road sidelines needs to be collected in a free view, draw straight lines in flat areas, add nodes in places with large arcs, and shorten the interval of sampling points in places with large elevation changes. During the extraction process, the viewing angle should be adjusted according to the point cloud data. Is the elevation correct. After extracting a section of road, it is necessary to check the degree of fit between the linear elements and the point cloud in the plane position and elevation position in the state of the top view and the perspective view, and move or encrypt the sampling points in places with deviations to maximize the extracted linear elements The degree is consistent with the field;

(3) Point elements are extracted including rods, boxes, cards and other components. For example, when collecting poles, you should refer to the panoramic image, take the center of the pole as the plane position, and take the ground elevation next to the pole as the elevation, and use the corresponding symbols such as street lights, probes, traffic lights, and electric poles to indicate, and fill in the number and top of the pole. Attributes such as absolute elevation, and different viewing angles should be adjusted during the collection process to ensure that the location elevation information of the final collected point features is accurate. The rest of the urban components need to use the corresponding element codes to extract the geometric center of the connection between the road component and the ground;

(4) When extracting area features, the 3D feature lines of area features should be closed on the plane and elevation, and filled with areas.

Step 3: Use 3DS Max software to build a part template library based on point cloud data and panoramic photos. The specific operation steps are as follows:

(1) According to the analysis of the structural characteristics of urban components, most of the poles, boxes and cards of urban components belong to polyhedral component modeling. This type of model is the most covered structure of urban components, which is composed of polyhedron structure or multiple facets. The main component models include traffic lights, green lights, fire hydrants, various signs, etc. In order to avoid occupying computer memory, ensure that the model and Under the premise of consistent physical objects, the amount of data of model points, lines, and surfaces should be reduced as much as possible.

(2) Manhole covers are one of the most types and quantities in urban components. According to their uses, they can be divided into drainage manhole covers, rainwater manhole covers, electric manhole covers, sewage manhole covers, gas manhole covers, etc., and can be divided into nodular cast iron manhole covers and cement manhole covers according to their materials. Manhole covers, resin composite manhole covers, etc. Since most urban manhole covers are round or square in shape, in order to save memory and simplify the component template library, the construction of the experimental manhole cover model in this chapter is based on the function of the manhole cover. In 3DS Max, the standard basic body modeling tool is used to make them according to the field survey and drawing size. There are two shapes of white film, round and square. The above two white films are used as the standard for manhole cover model production. The corresponding type of material is sufficient.

(3) Tree modeling is a model with a relatively complex modeling method in urban 3D real scene modeling. In order to reduce the point, line, surface and texture data of the model and reduce memory loss, binary surfaces are used in street tree modeling Technology, build the model in the way of patch tree. In the 3DS Max software, create two intersecting surfaces, convert the photo of the tree with a black background processed by PhotoShop into a PNG format, process the transparent map in 3DS Max, add an alpha channel to the original image, and set the texture map format For tga, the tree is used as the main body to perform two textures to realize the background transparency of the tree. The completed model can be scaled, rotated, copied and other functions to change the size of the tree or increase the number of patches of the tree.

Step 4: Based on the 3D vector data, use the 3D feature lines to construct the road model. The specific operation steps are as follows:

(1) Load the linear elements such as the road edge, roadside edge, green flower bed edge, and outer range line extracted from the 3D vector data into the 3DS Max software. After the data is imported, all the points on the spline are welded, and then used The polygonal modeling method is used to make road surfaces, sidewalks, greening and other element models.

(2) Import the 3D vector data of traffic markings on the main road, such as lane lines, guiding arrows, and pedestrian crossing lines, into 3DS Max software, and use the polygonal modeling method to make models according to the width information provided by the vector data. Surface objects such as bridges, guardrails, isolation belts, gantry frames, and safety islands are integrated with polygonal modeling and spline modeling.

(3) According to the tilt model and panoramic photos, and refer to the color information extracted during vectorization of linear elements such as lane lines and crosswalk lines, select the corresponding material in the material library for texture mapping. When mapping the regular model, select the uvw texture, and the texture parameters are set according to the real object model. When the model is irregular or the texture is complex, the uvw expansion method can be used to perform operations such as rotation, translation, and scaling on the texture to make the texture effect more realistic and finer.

Step 5: Perform merge check on the 3D model of the road. The specific operation steps are as follows:

(1) For 3D model baking, first select all points of the model, set the spot welding threshold to 0.01m, and then select the automatic smoothing tool in the modifier drop-down list. When baking the model, you need to use the frame as the baking unit. That is, a map frame is a MAX file, and the number of sides of each baking unit should be less than 6000. In case of special circumstances, when the number of sides of the baking unit far exceeds 6000, the baking unit should be split, and the split unit should still be Follow one bake unit for one max file.

(2) Post-process the model, split and merge the model, use the 3D data post-processing tool to reset and transform the model, optimize the material, and clean the shader ball.

(3) The quality inspection of the road 3D model includes naming inspection; checking whether the naming of model files, models and textures meets the requirements of technical standards. Accuracy check; check the plane position and elevation position accuracy of the model. Geometry data check; check model completeness, correctness, model overlapping faces and wrong faces. Texture data inspection; check the integrity, correctness, coordination, texture resolution, texture size, and transparent texture of the model texture map. Attribute data checks; checks on attribute fields, field types, attribute integrity, and attribute table relationships. Effect check; check the model brightness and model baking after the model baking and post-processing are completed.

The invention discloses a three-dimensional modeling method of urban roads based on vehicle-mounted point cloud data, which designs and completes the construction of three-dimensional models of urban roads and components. Firstly, the vehicle-mounted laser scanner is used to collect the road and the components on both sides of the road, and the full coverage of all the main roads in the pilot area is achieved, and the vehicle-mounted point cloud data collection is completed; then, the EPS mapping platform is used to collect the 3D vector data of the road and various components , using the collected 3D vector data as the data basis for urban 3D modeling; finally, using 3DS Max software to build a component template library and urban pavement model, and correlating and fusing the 3D model and vector information to form an informationized single model. The method of the present invention can not only ensure the integrity and authenticity of the scene, but also reduce the operation time and cost, and realize the seamless integration between various models. The refined management of 3D cities is of great significance, and it can be used as a certain technical support for my country's geographic information system.

The above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the protection of the present invention. within range.

Claims (6)

1. A three-dimensional modeling method for urban roads based on point cloud data, is characterized in that, comprises the steps: S1: Use the vehicle-mounted laser scanner based on the AS900HL multi-platform lidar measurement system to collect point cloud data, calculate and correct the point cloud data collected by the field, and obtain point cloud data that meets the model accuracy index. Cloud data is used as a data source for 3D modeling of urban roads; S2: Based on the point cloud data obtained in S1, use the EPS three-dimensional mapping software to collect three-dimensional vector data of the road, and obtain the three-dimensional vector data of all elements of the road; S3: Classify the 3D vector data obtained in S2 according to roads and components, and use 3DS Max software to build a component template library based on point cloud data and panoramic photos; S4: Based on 3D vector data, use 3D feature lines to build road models; S5: Based on the 3DS Max software, according to the position and direction of the parts in the 3D vector data, put the parts in the template library into the 3D scene of the road, carry out the vector-model attribute association, and perform quality inspection and modification on the model to complete the urban road and 3D modeling of components. 2. a kind of urban road three-dimensional modeling method based on point cloud data according to claim 1, is characterized in that, described step S1 comprises the following steps: (1) Before data collection, according to the road terrain in the test area, prepare for scanning route planning and parking area planning. The layout and observation of the verified and corrected control points can be laid out before data collection, or can be laid out and collected based on the point cloud data after the preliminary calculation of the point cloud data; (2) After the preparatory work is completed, route planning is carried out unit by unit according to the divided task units. When vehicle data is collected, navigation is collected according to the planned route. During actual collection, the route should be adjusted according to the road conditions, weather and other factors on the spot; (3) Calculate and correct the point cloud data collected by the field, create a new project in the Copre post-processing software, add the original data to the project, and use the original point cloud data and trajectory data to solve to obtain 3D points Cloud data, register point cloud data with panoramic photos to obtain color point cloud data. 3. a kind of urban road three-dimensional modeling method based on point cloud data according to claim 1, is characterized in that, described step S2 comprises the following steps: (1) The extraction of linear elements mainly includes road markings and road sidelines. When extracting road markings, first select the corresponding element code according to the marking type, and extract the geometric center position of the road markings in the point cloud data. Nodes should be added in places with large radians to ensure the accuracy of the plane position and elevation position of the 3D vector data; (2) The extraction of road sidelines needs to be collected in a free view, draw straight lines in flat areas, add nodes in places with large arcs, and shorten the interval of sampling points in places with large elevation changes. During the extraction process, the viewing angle should be adjusted according to the point cloud data. Whether the elevation is correct, after extracting a section of road, it is necessary to check the degree of fit between the linear elements and the point cloud in the plane position and elevation position in the state of top view and perspective view, and move or encrypt the sampling points where there is deviation, so that the extracted Linear elements are consistent with the field to the greatest extent; (3) Extract point elements including poles, boxes, signs and other components. For example, when collecting poles, refer to the panoramic image. , probes, traffic lights, electric poles and other symbols, fill in the number of the pole and the absolute elevation of the top and other attributes, and adjust different angles of view during the collection process to ensure that the location and elevation information of the final collected point elements are accurate. When extracting other urban components All need to use the corresponding feature code to extract the geometric center of the connection between the road component and the ground; (4) When extracting area features, the 3D feature lines of area features should be closed on the plane and elevation, and filled with areas. 4. a kind of urban road three-dimensional modeling method based on point cloud data according to claim 1, it is characterized in that, city common parts are divided into bar class, box class, card class, tree class etc., and parts template library construction Including the production of white film and texture map, combined with point cloud data and the actual size of the ground objects in the field, using 3DS Max software to make white film, the modeling method mainly adopts polygonal modeling, spline modeling and compound object building Model to achieve 1:1 restoration of the model and the real object; then combined with the panoramic image, select photos with bright colors, good angles, clear and unobstructed photos, perform cropping processing, and make them into texture maps. Select the corresponding surface in 3DSMax software, and use the uvw map to make the model Texture mapping. 5. a kind of urban road three-dimensional modeling method based on point cloud data according to claim 1, it is characterized in that, the construction scope of urban pavement model is from the sidewalk outermost edge on one side of the road to the sidewalk outermost edge on the other side of the road. The outer edge, including the sidewalks on both sides, uses linear elements such as the road edge, land type boundary, and outer range line extracted from the 3D vector data to construct element models such as the main road surface, sidewalks, and green flower beds. 6. a kind of urban road three-dimensional modeling method based on point cloud data according to claim 1, it is characterized in that, according to the kind, actual position and direction of each component model, the model in the template storehouse is passed through automatic and semi-automatic combination The method is implanted into the 3D scene, and the model of the urban component elements is called from the model library. According to the position and orientation information of each component in the 3D vector data, the model in the component template library is placed in 3DS Max through operations such as movement and rotation. The accurate position in the 3D scene; the quality check of the road 3D model includes name check, precision check, geometric data check, texture data check, and attribute data check.