A method and device for bridge three-dimensional reconstruction based on laser radar point cloud

Abstract

The present application relates to the field of engineering surveying, in particular to a method and device for bridge three-dimensional reconstruction based on laser radar point cloud, which calculates the point cloud on the top of the bridge pier in the laser radar point cloud of the bridge, supplements the missing part of the point cloud, and makes the overall structure of the bridge point cloud more complete; meanwhile, a lightweight data model is used as the output, which greatly reduces the data size of the model.

Description

Technical Field

[0001] This invention relates to the field of engineering surveying technology, and in particular to a method and equipment for three-dimensional reconstruction of bridges based on lidar point clouds. Background Technology

[0002] Existing technologies utilize UAV LiDAR to acquire bridge point cloud data. However, due to limitations in the radar measurement angle, the point cloud distribution is uneven, resulting in missing data in some areas. Consequently, the 3D bridge models created using existing point cloud reconstruction methods are incomplete and contain significant gaps. Furthermore, the amount of bridge point cloud data acquired using UAV LiDAR is substantial, and the models reconstructed using traditional methods also require significant computer performance, making them inconvenient to use.

[0003] In summary, existing technologies suffer from incomplete bridge point clouds and massive amounts of point cloud data. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of incomplete bridge point clouds and large amount of point cloud data in the existing technology, and to provide a method and equipment for three-dimensional reconstruction of bridges based on lidar point clouds.

[0005] To achieve the above-mentioned objectives, the present invention adopts the following technical solution: A method for 3D reconstruction of bridges based on lidar point clouds includes the following steps: S1: Obtain the point cloud of the bridge to be modeled; extract the centerline points of the bridge point cloud from a top-down view according to the preset mileage interval, and generate a set of centerline points.

[0006] S2: Extract representative points of the beam cross-section based on the set of centerline points; construct a beam triangular network based on the adjacency relationship of the beam cross-sections and the representative points of the beam cross-sections.

[0007] S3: Extract representative points at the bottom and top of the piers based on the set of centerline points; construct a pier triangular network based on the representative points at the bottom and top of the piers.

[0008] S4: Combine the triangular network of the beam and the triangular network of the pier to construct an overall three-dimensional model of the bridge and complete the three-dimensional reconstruction of the bridge.

[0009] As a preferred embodiment of the present invention, step S1 includes the following steps: S11: Scan the area of ​​the bridge to be modeled using LiDAR and retain the point cloud of the bridge portion as the bridge point cloud.

[0010] S12: According to the preset mileage interval and avoiding the bridge piers, extract the centerline points from the bridge point cloud from the top view and generate a set of centerline points.

[0011] As a preferred embodiment of the present invention, step S2 includes the following steps: S21: Select a centerline point from the set of centerline points in the set of centerline points as a reference point according to the set order, and take the position of the next centerline point as the direction of movement; traverse and calculate the distance from the points in the bridge point cloud to the vertical plane where the reference point is located.

[0012] S22: Retain points whose distance is less than the preset threshold as beam cross-section points of the current reference point; and calculate the vertical distance from each beam cross-section point to the line connecting the current centerline point and the next centerline point.

[0013] S23: Divide the beam cross-section points vertically into sections according to a preset width, and extract the points with the largest elevation and compensation points in each section to obtain representative points of the beam cross-section.

[0014] The compensation points include a first compensation point and a second compensation point; the coordinates of the first compensation point and the second compensation point are obtained as follows: Extract the point with the smallest vertical distance among the points on the cross section of the beam. value, Value as the first compensation point value, Value, extract the minimum value among all points on the beam cross-section. Value as the first compensation point value; Extract the point with the largest vertical distance from the cross-section of the beam. value, Value as the second compensation point value, Value, extract the minimum value among all points on the beam cross-section. Value as the second compensation point value.

[0015] S24: Based on the forward direction, repeat S21-S23 to obtain the representative points of the beam cross section corresponding to all reference points in sequence.

[0016] S25: Connect the representative points of the beam cross sections in the corresponding partitions of adjacent sections in turn to obtain the beam triangular network.

[0017] As a preferred embodiment of the present invention, the cross-section of the beam corresponding to all reference points in S24 adopts the same number of partitions.

[0018] As a preferred embodiment of the present invention, step S3 includes the following steps: S31: Select a centerline point from the set of centerline points in the set of centerline points according to the set order. With the line connecting the current centerline point and the next centerline point as the diameter, draw a circle with the center point of the line connecting the diameter as the center. Traverse the bridge point cloud and extract the points located inside the circle.

[0019] S32: If there exist points inside the circle that satisfy... If a point is found within a circle, then a bridge pier exists within that circle, and the point within the circle is considered a candidate bridge pier point.

[0020] in, The lowest elevation of a point inside the circle; This represents the lowest elevation in the beam cross-section corresponding to the current centerline point and the next centerline point. This is the preset pier elevation compensation value.

[0021] S33: Sort the candidate pier points in ascending order of elevation, and calculate the elevation difference between two consecutive candidate pier points after sorting; determine the pier height based on the point corresponding to the largest elevation difference and the point with the largest elevation among the candidate pier points.

[0022] S34: Traverse the candidate points of the bridge piers and extract the representative points at the top and bottom of the bridge piers respectively.

[0023] S35: Based on the height of the pier, connect the representative point at the bottom of the pier and the representative point at the top of the pier to obtain the pier triangular network.

[0024] As a preferred embodiment of the present invention, step S34 includes the following steps: S341: Based on the relationship between the elevation and the judgment value among the candidate points of the pier, extract the candidate points at the top of the pier and the candidate points at the bottom of the pier respectively.

[0025] The determination value includes either the top determination value or the bottom determination value.

[0026] Points whose elevation is greater than the top determination value are extracted as candidate points for the top of the bridge pier; points whose elevation is less than the bottom determination value are extracted as candidate points for the bottom of the bridge pier.

[0027] S342: Calculate the average plane coordinates of all candidate points at the top and bottom of the pier as the center point, and convert all point coordinates into polar coordinates based on the center point.

[0028] S343: Based on the rotation angle and the preset number of partitions, the candidate points at the top of the pier and the candidate points at the bottom of the pier are divided into fan-shaped regions.

[0029] S344: Extract the contour points of each of the aforementioned sector regions, and supplement the contour points at the top of the pier to obtain representative points at the top and bottom of the pier.

[0030] Within any sector region: if the first Each point satisfies Then extract the first The point and the first The average value of each point is used as the contour point of the corresponding sector region; where... , The angle swept across the fan-shaped region.

[0031] As a preferred embodiment of the present invention, the supplementation of the top contour points of the bridge pier in S344 is achieved by calculating the top contour, and the calculation method is as follows: First, calculate the area of ​​the polygon enclosed by the candidate points at the top and bottom of the pier respectively; then, obtain the representative point at the top of the pier based on the ratio of the two areas, the candidate points at the bottom of the pier, and the center point of the bottom.

[0032] The color value of the top representative point is the same as that of the top outline point; the coordinate values ​​are calculated using the following expression:

[0033] in, , , These are the coordinates of the point represented by the top of the bridge pier; , The coordinates of the center point; The horizontal distance from the candidate point at the bottom of the bridge pier to the center point; The rotation angle among the candidate points at the bottom of the pier; The elevation of the candidate points at the bottom of the pier; This refers to the height of the bridge piers; It is the ratio of the area of ​​the polygon enclosed by the candidate points at the top of the pier to the area of ​​the polygon enclosed by the candidate points at the bottom of the pier.

[0034] As a preferred embodiment of the present invention, the method of connecting representative points is as follows: connect corresponding points in corresponding partitions of two surfaces to be connected to form a quadrilateral, and then connect one diagonal of the quadrilateral to form a triangular network.

[0035] As a preferred embodiment of the present invention, the overall three-dimensional diagram of the bridge in step S4 is constructed based on the coordinates, colors, and sequences of each point in the beam triangular network and the pier triangular network.

[0036] A device for 3D reconstruction of a bridge based on lidar point clouds includes at least one processor and a memory communicatively connected to the at least one processor; the memory stores instructions executable by the at least one processor, which, when executed by the at least one processor, enable the at least one processor to perform any of the above-described methods for 3D reconstruction of a bridge based on lidar point clouds.

[0037] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention extracts representative points from the beams and piers separately and constructs triangulation networks, making the final 3D model more complete and smooth. At the same time, it calculates and supplements the point cloud on the top of the piers, which cannot be accurately measured by lidar, making the overall bridge point cloud structure more complete. Finally, it outputs a lightweight 3D model, reducing the model data size. Attached Figure Description

[0038] Figure 1 This is a schematic diagram of the overall process of a method for three-dimensional reconstruction of a bridge based on lidar point clouds, as described in Embodiment 1 of the present invention.

[0039] Figure 2 This is a schematic diagram of centerline point extraction in a method for three-dimensional reconstruction of a bridge based on lidar point clouds, as described in Embodiment 2 of the present invention.

[0040] Figure 3 This is a schematic diagram of beam cross-section point extraction in a method for three-dimensional reconstruction of a bridge based on lidar point clouds, as described in Embodiment 2 of the present invention.

[0041] Figure 4 This is a schematic diagram of the cross-sectional point partitioning of the beam section in a method for three-dimensional reconstruction of a bridge based on lidar point clouds, as described in Embodiment 2 of the present invention.

[0042] Figure 5 This is a schematic diagram of the triangular network of the beam in a method for three-dimensional reconstruction of a bridge based on lidar point clouds, as described in Embodiment 2 of the present invention.

[0043] Figure 6 This is a schematic diagram of the extraction of candidate points for bridge piers in a method for three-dimensional reconstruction of bridges based on lidar point clouds, as described in Embodiment 2 of the present invention.

[0044] Figure 7 This is a distribution map of candidate points at the top and bottom of the bridge piers in a method for three-dimensional reconstruction of bridges based on lidar point clouds, as described in Embodiment 2 of the present invention.

[0045] Figure 8 This is a schematic diagram of the rotation angle of candidate points for bridge piers in a method for three-dimensional reconstruction of bridges based on lidar point clouds, as described in Embodiment 2 of the present invention.

[0046] Figure 9 This is a schematic diagram of the bridge pier triangulation in a method for three-dimensional reconstruction of bridges based on lidar point clouds, as described in Embodiment 2 of the present invention.

[0047] Figure 10 This is the point cloud map of the bridge to be rebuilt as described in Embodiment 3 of the present invention.

[0048] Figure 11 This is a diagram of a three-dimensional bridge reconstruction model using the Alpha shape method as described in Embodiment 3 of the present invention.

[0049] Figure 12 This is a bridge 3D reconstruction model diagram of a bridge 3D reconstruction method based on lidar point cloud as described in Embodiment 3 of the present invention.

[0050] Figure 13 This is a schematic diagram of a device for three-dimensional reconstruction of a bridge based on lidar point clouds, which utilizes any of the aforementioned methods for three-dimensional reconstruction of bridges based on lidar point clouds, as described in Embodiment 4 of the present invention. Detailed Implementation

[0051] The present invention will be further described in detail below with reference to experimental examples and specific embodiments. However, this should not be construed as limiting the scope of the above-mentioned subject matter of the present invention to the following embodiments; all technologies implemented based on the content of the present invention fall within the scope of the present invention.

[0052] Example 1 like Figure 1 As shown, a method for 3D reconstruction of bridges based on lidar point clouds includes the following steps: S1: Obtain the point cloud of the bridge to be modeled; extract the centerline points of the bridge point cloud from a top-down view according to the preset mileage interval, and generate a set of centerline points.

[0053] S2: Extract representative points of the beam cross-section based on the set of centerline points; construct a beam triangular network based on the adjacency relationship of the beam cross-sections and the representative points of the beam cross-sections.

[0054] S3: Extract representative points at the bottom and top of the piers based on the set of centerline points; construct a pier triangular network based on the representative points at the bottom and top of the piers.

[0055] S4: Combine the triangular network of the beam and the triangular network of the pier to construct an overall three-dimensional model of the bridge and complete the three-dimensional reconstruction of the bridge.

[0056] Example 2 This embodiment is a specific implementation of the method for three-dimensional reconstruction of bridges based on lidar point clouds described in Embodiment 1, including the following steps: S1: Obtain the point cloud of the bridge to be modeled; extract the centerline points from the bridge point cloud of the top view according to the preset mileage interval, and generate a set of centerline points.

[0057] S11: Scan the area of ​​the bridge to be modeled using LiDAR and retain the point cloud of the bridge portion, denoted as the bridge point cloud. ;in, , , These are coordinate values; , , This is the color value.

[0058] S12: As Figure 2 As shown, following preset mileage intervals and avoiding bridge piers, the centerline points are extracted from the bridge point cloud from a top-down perspective, generating a centerline point set. This operation can be performed in commonly used point cloud processing software, such as Lidar360 and DJI Terra, and is a standard function of such software.

[0059] S2: Extract representative points of the beam cross-section based on the set of centerline points; construct a beam triangular network based on the adjacency relationship of the beam cross-sections and the representative points of the beam cross-sections.

[0060] S21: As Figure 3 As shown, a centerline point is selected from the set of centerline points in a predetermined order as the reference point, and the location of the next centerline point is used as the direction of travel; the point cloud is traversed. The distance from a point in the bridge point cloud to the vertical plane containing the reference point is calculated. .

[0061] S22: For distances less than a preset threshold Point retention ( The value can be set according to the point cloud density; set it smaller when the density is high and larger when the density is low. The cross-sectional point of the beam is used as the current reference point; and the perpendicular distance from each cross-sectional point of the beam to the line connecting the current centerline point and the next centerline point is calculated. When the point is located to the left of the connecting line, It is a negative value; conversely, it is a positive value.

[0062] Create an array Store the extracted points, each row of data according to Sort by size from smallest to largest:

[0063] S23: In the middle, set The minimum value in the column containing the value is ,like Figure 4As shown, the beam cross-section is vertically divided into sections of a preset width (the section width is set with reference to the point cloud density; a smaller width can be set for a higher point cloud density, and vice versa). The total width of the cross-section is... , lower left corner point Coordinates are bottom right corner Coordinates are .

[0064] Then extract one point from each partition, and... , Together, these serve as points for constructing this cross-sectional shape. The method for extracting points within a partition is as follows: extract points from the partition... The point with the largest value. After extraction, the data is stored in an array. :

[0065] in, The data represents the number of points, and the sorting method for each row is as follows: Coordinates and color (color taken from) (First row of color values); The coordinates and colors of the partitions; Coordinates and color (color taken from) The Middle (Row color value).

[0066] S24: Based on the forward direction, repeat S21-S23 to obtain the representative points of the beam cross section corresponding to all reference points in sequence; The beam cross sections corresponding to all reference points use the same number of partitions.

[0067] S25: As Figure 5 As shown, the representative points of the beam cross sections in the corresponding partitions of adjacent sections are connected in sequence to obtain the beam triangular network.

[0068] S3: Extract representative points at the bottom and top of the bridge piers based on the set of centerline points; construct a triangulation network of the bridge piers based on these representative points. The specific steps are as follows: S31: The bridge center points mentioned above were extracted without considering the piers; therefore, the pier point cloud must be distributed between two adjacent center points. For example... Figure 6 As shown, a centerline point is selected from the set of centerline points in a predetermined order. The line connecting the current centerline point and the next centerline point is used as the diameter, and the center point of the line is used as the diameter. Draw a circle with the center as the center, traverse the bridge point cloud, extract the points located inside the circle, and store them in an array. middle. In the middle, the data in each row is arranged according to The expression to sort the values ​​from smallest to largest is:

[0069] S32: For In this case, if the circle includes bridge piers, then some points within it must have significantly lower elevations than points on the preceding and following cross-sections. That is, if points within the circle satisfy... If a point is found within a circle, then a bridge pier exists within that circle, and the point within the circle is considered a candidate bridge pier point.

[0070] in, The lowest elevation of a point inside the circle; This represents the lowest elevation in the beam cross-section corresponding to the current centerline point and the next centerline point. This is the preset pier elevation compensation value. Due to the angle of the lidar measurement, there will be missing point cloud data at the top of the piers. Based on the point cloud data, the following settings are configured: Value: The point cloud has a large missing portion. If the value is less than 3, then a larger value can be chosen; conversely, if the value is less than 4, then a smaller value can be chosen.

[0071] S33: After confirming the existence of bridge piers within the circle, the point cloud of the bridge piers needs to be extracted separately. Traverse... The data in the middle makes After traversing all elements, find the largest one. This is the point of elevation change. Assuming the largest... The corresponding row number is , then delete The front of the middle Okay. At the same time, the height of the bridge piers can be obtained as follows:

[0072] in, for The maximum elevation value in the middle; To the maximum The corresponding elevation.

[0073] S34: Traverse the candidate bridge piers The representative points at the top and bottom of the bridge piers were extracted separately. The specific steps are as follows: S341: Based on the relationship between the elevation and the judgment value among the candidate points of the pier, extract the candidate points at the top of the pier and the candidate points at the bottom of the pier, and store them in arrays respectively. and middle.

[0074] The determination value includes either the top determination value or the bottom determination value.

[0075] Points whose elevation is greater than the top determination value are extracted as candidate points for the top of the bridge pier; their expression is:

[0076] in, The elevation of the point being judged; for Minimum elevation in the range; The top determination value is when the top point cloud is relatively complete (the point cloud can fully display the top outline). The value can be smaller, and vice versa.

[0077] Points whose elevation is less than the bottom determination value are extracted as candidate points for the bottom of the bridge pier; their expression is:

[0078] in, The elevation of the point being judged; for The maximum elevation value in the middle; This is the bottom determination value; when there are enough bottom point clouds, The value can be smaller, and vice versa.

[0079] S342: Calculate the average plane coordinates of all candidate points at the top and bottom of the piers respectively, and use them as the center point. Based on the center point, convert the coordinates of all points to polar coordinates and store them in arrays respectively. and middle:

[0080] in, From this point to the center point Horizontal distance; Rotation angle .

[0081] like Figure 7 As shown (top view). and That is, the set of top candidate points and bottom candidate points, respectively, arranged clockwise around the center of the bridge pier.

[0082] S343: Due to the uneven distribution of the point cloud, extracting all points may result in an uneven contour. Therefore, only a portion of the points are extracted, and the candidate points at the top and bottom of the piers are divided into fan-shaped regions based on the rotation angle and the preset number of partitions.

[0083] S344: Extract the contour points of each of the aforementioned sector regions, and supplement the contour points of the pier top to obtain the representative points of the pier top. and the representative point at the bottom of the bridge pier .

[0084] Within any sector region: if the first Each point satisfies Then extract the first The point and the first The average value of each point is used as the contour point of the corresponding sector region; where... ,like Figure 8 As shown, The angle swept across the fan-shaped region.

[0085] The supplementation of the top contour points of the bridge piers is achieved by calculating the top contour, and the calculation method is as follows: First, calculate the area of ​​the polygon enclosed by the candidate points at the top and bottom of the pier respectively; then, obtain the representative point at the top of the pier based on the ratio of the two areas, the candidate points at the bottom of the pier, and the center point of the bottom.

[0086] The color value of the top representative point is the same as that of the top outline point; the coordinate values ​​are calculated using the following expression:

[0087] in, , , These are the coordinates of the point represented by the top of the bridge pier; , The coordinates of the center point; The horizontal distance from the candidate point at the bottom of the bridge pier to the center point; The rotation angle among the candidate points at the bottom of the pier; The elevation of the candidate points at the bottom of the pier; This refers to the height of the bridge piers; This is the ratio of the area of ​​the polygon enclosed by the candidate points at the top of the pier to the area of ​​the polygon enclosed by the candidate points at the bottom of the pier. This step starts from the unsupplemented pier top contour points. The supplemented representative point of the bridge pier top .

[0088] S35: At this time. and Having the same number of points, As the bottom point, As the top point, construct as follows, based on the height of the bridge pier. Figure 9 The diagram shows a triangular network of bridge piers. The method for connecting the representative points is as follows: connect corresponding points in corresponding sections of the two surfaces to be connected to form a quadrilateral, and then connect one diagonal of the quadrilateral to form a triangular network.

[0089] S4: Combine the triangular mesh of the beam and the triangular mesh of the pier, and construct an overall three-dimensional model of the bridge based on the coordinates, colors and sequences of each point, thus completing the three-dimensional reconstruction of the bridge.

[0090] Example 3 This embodiment is a comparative embodiment of the method for 3D reconstruction of bridges based on LiDAR point clouds described in Embodiment 2 and the method for 3D reconstruction using the Alpha shape method. The specific content is as follows: After scanning the bridge to be modeled using LiDAR and removing irrelevant environmental point clouds, the following results were obtained: Figure 10 The point cloud of the bridge to be rebuilt shown contains 80,089 points.

[0091] The 3D model of the bridge point cloud reconstructed using the Alpha shape method is shown below. Figure 11 As shown in the figure, the 3D model reconstructed by the Alpha shape method has many holes and missing parts due to uneven point cloud density and missing points, especially at the top of the bridge piers, making it impossible to provide a reliable 3D model. Furthermore, it increases the size of the original data; the model size is 5.8MB, while the original point cloud size is 1.98MB, which is 2.9 times the size of the point cloud data.

[0092] like Figure 12 As shown, the 3D model generated according to the method of this invention can accurately represent the overall position and shape, and the missing parts of the point cloud are also repaired. Compared with the aforementioned traditional model, the outline is clearer, the shape is more complete, and the lines are smoother. In addition, the original point cloud size is 1.98MB, while the model size is 56KB, which is only 2.8% of the point cloud size, meeting the requirement of lightweight design.

[0093] Example 4 like Figure 13 As shown, a device for 3D bridge reconstruction based on LiDAR point clouds includes at least one processor, a memory communicatively connected to the at least one processor, and at least one input / output interface communicatively connected to the at least one processor. The memory stores instructions executable by the at least one processor, which, when executed, enables the at least one processor to perform a method for 3D bridge reconstruction based on LiDAR point clouds as described in the foregoing embodiments. The input / output interface may include a display, keyboard, mouse, and USB interface for inputting and outputting data.

[0094] Furthermore, the device for 3D reconstruction of bridges based on LiDAR point clouds can be a desktop computer, mobile phone, tablet computer, wearable device, or any other device capable of depth information recognition for 3D reconstruction of bridges based on LiDAR point clouds.

[0095] Furthermore, the processor may include one or more processing cores. The processor connects various parts of the device for 3D bridge reconstruction based on LiDAR point clouds using various interfaces and lines. It executes various functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in memory, and by calling data stored in memory. Optionally, the processor may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor may integrate one or more of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the displayed content; and the modem handles wireless communication. It is understood that the modem may also be implemented separately as a communication chip, without being integrated into the processor.

[0096] The memory may include random access memory (RAM) or read-only memory (ROM). The memory can be used to store instructions, programs, code, code sets, or instruction sets, such as instructions or code sets used to implement the method for 3D bridge reconstruction based on LiDAR point clouds provided in this application embodiment. The memory may include a program storage area and a data storage area. The program storage area may store instructions for implementing an operating system, instructions for implementing at least one function, instructions for implementing the various method embodiments described above, etc. The data storage area may also store data created during the use of the device for 3D bridge reconstruction based on LiDAR point clouds (such as a mapping table of modulation sequences and depth, image data, spectrogram data, etc.).

[0097] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, read-only memory, magnetic disks, or optical disks.

[0098] When the integrated units of the present invention are implemented as software functional units and sold or used as independent products, they can also be stored in a computer-readable storage medium. The computer-readable storage medium stores program code, which can be called by a processor to execute the methods described in the above method embodiments. Based on this understanding, the technical solution of the embodiments of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer system (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes electronic memory such as flash memory, EEPROM (Electrically Erasable Programmable Read-Only Memory), EPROM, hard disk, or ROM. Optionally, the computer-readable storage medium includes a non-transitory computer-readable storage medium. The computer-readable storage medium has storage space for program code that executes any of the method steps described above. This program code can be read from or written to one or more computer program products. The program code can be compressed, for example, in an appropriate form.

[0099] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for three-dimensional reconstruction of bridges based on lidar point clouds, characterized in that, Includes the following steps: S1: Obtain the point cloud of the bridge to be modeled; according to the preset mileage interval, extract the centerline points of the bridge point cloud from the top view and generate a set of centerline points; S2: Extract representative points of the beam section cross-section based on the set of centerline points; construct a beam section triangulation based on the adjacency relationship of the beam section cross-sections and the representative points of the beam section cross-sections; S3: Extract representative points at the bottom and top of the piers based on the set of centerline points; construct a pier triangulation network based on the representative points at the bottom and top of the piers. S4: Combine the triangular network of the beam and the triangular network of the pier to construct an overall three-dimensional model of the bridge and complete the three-dimensional reconstruction of the bridge.

2. The method for three-dimensional reconstruction of bridges based on lidar point clouds according to claim 1, characterized in that, S1 includes the following steps: S11: Scan the area of ​​the bridge to be modeled using LiDAR and retain the point cloud of the bridge portion as the bridge point cloud; S12: According to the preset mileage interval and avoiding the bridge piers, extract the centerline points from the bridge point cloud from the top view and generate a set of centerline points.

3. The method for three-dimensional reconstruction of bridges based on lidar point clouds according to claim 1, characterized in that, S2 includes the following steps: S21: Select a centerline point from the set of centerline points in a set order as a reference point, and take the position of the next centerline point as the direction of movement; traverse and calculate the distance from the points in the bridge point cloud to the vertical plane where the reference point is located; S22: Retain points whose distance is less than a preset threshold as beam cross-section points of the current reference point; and calculate the perpendicular distance from each beam cross-section point to the line connecting the current centerline point and the next centerline point. S23: Divide the beam cross-section points vertically into sections according to a preset width, and extract the points with the largest elevation and compensation points in each section to obtain representative points of the beam cross-section; The compensation points include a first compensation point and a second compensation point; the coordinate extraction methods for the first compensation point and the second compensation point are as follows: Extract the point with the smallest vertical distance among the points on the cross section of the beam. value, Value as the first compensation point value, Value, extract the minimum value among all points on the beam cross-section. Value as the first compensation point value; Extract the point with the largest vertical distance from the cross-section of the beam. value, Value as the second compensation point value, Value, extract the minimum value among all points on the beam cross-section. Value as the second compensation point value; S24: Based on the forward direction, repeat S21-S23 to obtain the representative points of the beam cross section corresponding to all reference points in sequence; S25: Connect the representative points of the beam cross sections in the corresponding partitions of adjacent sections in turn to obtain the beam triangular network.

4. The method for three-dimensional reconstruction of bridges based on lidar point clouds according to claim 3, characterized in that, In S24, the cross-section of the beam corresponding to all reference points uses the same number of partitions.

5. The method for three-dimensional reconstruction of bridges based on lidar point clouds according to claim 1, characterized in that, S3 includes the following steps: S31: Select a centerline point from the set of centerline points in the set of centerline points according to the set order. With the line connecting the current centerline point and the next centerline point as the diameter, draw a circle with the center point of the line connecting the diameter as the center. Traverse the bridge point cloud and extract the points located inside the circle. S32: If there exist points inside the circle that satisfy... If a point is found within a circle, then a bridge pier exists within that circle, and the point within the circle is taken as a candidate bridge pier point. in, The lowest elevation of a point inside the circle; This represents the lowest elevation in the beam cross-section corresponding to the current centerline point and the next centerline point. This is the preset pier elevation compensation value; S33: Sort the candidate pier points according to their elevation from smallest to largest, and calculate the elevation difference between two consecutive points in the sorted candidate pier points; and determine the pier height by using the point corresponding to the largest elevation difference and the point with the largest elevation in the candidate pier points. S34: Traverse the candidate points of the bridge piers and extract the representative points at the top and bottom of the bridge piers respectively; S35: Based on the height of the pier, connect the representative point at the bottom of the pier and the representative point at the top of the pier to obtain the pier triangular network.

6. The method for three-dimensional reconstruction of bridges based on lidar point clouds according to claim 5, characterized in that, S34 includes the following steps: S341: Based on the relationship between the elevation and the judgment value among the candidate points of the pier, extract the candidate points at the top of the pier and the candidate points at the bottom of the pier respectively; The determination value includes a top determination value or a bottom determination value; Points whose elevation is greater than the top determination value are extracted as candidate points for the top of the bridge pier; points whose elevation is less than the bottom determination value are extracted as candidate points for the bottom of the bridge pier. S342: Calculate the average plane coordinates of all candidate points at the top and bottom of the pier as the center point, and convert the coordinates of all points into polar coordinates based on the center point. S343: Based on the rotation angle and the preset number of partitions, the candidate points at the top of the pier and the candidate points at the bottom of the pier are divided into fan-shaped regions. S344: Extract the contour points of each of the aforementioned sector regions, and supplement the contour points at the top of the pier to obtain representative points at the top and bottom of the pier. Within any sector region: if the first Each point satisfies Then extract the first The point and the first The average value of each point is used as the contour point of the corresponding sector region; where... , The angle swept across the fan-shaped region.

7. The method for three-dimensional reconstruction of bridges based on lidar point clouds according to claim 6, characterized in that, In S344, the supplementation of the top contour points of the bridge pier is achieved by calculating the top contour. The calculation method is as follows: First, calculate the area of ​​the polygon enclosed by the candidate points at the top and bottom of the pier respectively; then, based on the ratio of the two areas, the candidate points at the bottom of the pier, and the center point of the bottom, obtain the representative point at the top of the pier. The color value of the top representative point is the same as that of the top outline point; the coordinate values ​​are calculated using the following expression: in, , , These are the coordinates of the point represented by the top of the bridge pier; , The coordinates of the center point; The horizontal distance from the candidate point at the bottom of the bridge pier to the center point; The rotation angle among the candidate points at the bottom of the pier; The elevation of the candidate points at the bottom of the pier; This refers to the height of the bridge piers; It is the ratio of the area of ​​the polygon enclosed by the candidate points at the top of the pier to the area of ​​the polygon enclosed by the candidate points at the bottom of the pier.

8. A method for three-dimensional reconstruction of a bridge based on lidar point clouds according to any one of claims 3-7, characterized in that, The method for connecting representative points is as follows: connect corresponding points in corresponding partitions of two surfaces to be connected to form a quadrilateral, and then connect one diagonal of the quadrilateral to form a triangular network.

9. The method for three-dimensional reconstruction of bridges based on lidar point clouds according to claim 1, characterized in that, The overall three-dimensional diagram of the bridge in S4 is constructed based on the coordinates, colors, and sequences of each point in the beam triangular network and the pier triangular network.

10. A device for three-dimensional reconstruction of bridges based on lidar point clouds, characterized in that, The device includes at least one processor and a memory communicatively connected to the at least one processor; the memory stores instructions executable by the at least one processor, which, when executed by the at least one processor, enable the at least one processor to perform a method for three-dimensional reconstruction of a bridge based on lidar point clouds, as described in any one of claims 1 to 9.

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