A three-dimensional modeling method

Abstract

The present invention relates to the technical field of three-dimensional modeling, and in particular to a three-dimensional modeling method. The present invention controls the movement of an acquisition terminal to obtain preliminary modeling data and environmental data of objects in various regions in an actual scene, determines a frame area and frame area parameters on the surface of the object based on the preliminary modeling data, calculates environmental interference modeling characterization parameters for the object based on the frame area parameters combined with environmental data, divides the environmental interference modeling complexity categories of the object, adaptively adjusts the modeling data acquisition method and constructs a three-dimensional model of the object in a virtual space, thereby reducing the impact of environmental factors on the quality of the acquired modeling data and improving the reliability of the acquired modeling data. At the same time, the present invention well adapts to scene changes, reasonably allocates computing resources, and reduces the waste of computing resources.

Description

Technical Field

[0001] The present invention relates to the technical field of three-dimensional modeling, and in particular to a three-dimensional modeling method. Background Art

[0002] With the advancement of technology, the improvement of computing power, the innovation of software tools and the demand for interdisciplinary applications, the development of 3D modeling has been promoted. Among them, when collecting entity model data for virtual space rendering, it is necessary to comprehensively consider the accuracy of data collection, the efficiency of processing algorithms, the quality of rendering technology and the needs of the final application. Automated and intelligent tools are constantly simplifying this process, making 3D modeling and rendering more efficient and easy to operate.

[0003] Chinese patent publication number: CN109978758A, discloses a 3D modeling method based on computer graphics images, including: selecting 7-10 staff members to use cameras to take photos of objects to be 3D modeled from multiple angles, multiple staff members collect information about the objects to be 3D modeled, and take photos of the objects every 40 degrees to ensure that the same feature of the object to be modeled can be found in adjacent photos, and the obtained pictures are processed by a computer, the coordinates of the two-dimensional graphics are calculated, and the relevant data obtained by combining with an ultrasonic scanner, and then the top view data of the object to be 3D modeled taken by the aerial camera is combined with the previous data to obtain the 3D graphics of the object.

[0004] However, the following problems still exist in the prior art. When collecting point cloud data of objects, it will be affected by environmental factors, such as noise and vibration, which will reduce the accuracy of the collected data and damage the data integrity, thereby affecting the 3D modeling process and reducing the accuracy and quality of 3D modeling. At the same time, it does not take into account the different complexities of different objects in the same area and the different demands for point cloud data. Computing resources are not allocated in a targeted manner, resulting in unreasonable allocation of computing resources and waste of resources. Summary of the invention

[0005] To this end, the present invention provides a three-dimensional modeling method to overcome the impact of environmental vibration on the accuracy and integrity of the collected point cloud data in the prior art and the unreasonable allocation of computing resources and waste of resources in the three-dimensional modeling process.

[0006] To achieve the above object, the present invention provides a three-dimensional modeling method, which comprises:

[0007] Step S1, controlling the acquisition end to move and acquire preliminary modeling data and environmental data of objects in various regions in the actual scene, wherein the preliminary modeling data includes surface point cloud data acquired with a preset low point cloud interval standard for the object, and the environmental data includes vibration amplitude and vibration frequency of the object setting region;

[0008] Step S2, determining the frame area and frame area parameters of the object surface according to the preliminary modeling data, calculating the environmental interference modeling characterization parameters for the object according to the frame area parameters combined with the environmental data, and classifying the environmental interference modeling complexity category of the object;

[0009] Step S3, adjusting the modeling data acquisition method and constructing a three-dimensional model of the object in a virtual space according to the complexity category of the environmental interference modeling of the object, including:

[0010] Controlling the acquisition end to scan the point cloud data of the surface area of ​​the object with a preset high point cloud interval standard, determining the specific area according to the frame area parameters of each local area of ​​the surface of the object during scanning, adjusting the scanning frequency for the specific area, and constructing the three-dimensional model of the object with the corresponding modeling parameters in the virtual space after adjusting the modeling parameters based on the environmental interference modeling characterization parameters;

[0011] Alternatively, the point cloud interval is adjusted according to the environmental interference modeling characterization parameter, and the point cloud data of the surface area of ​​the object is scanned with the corresponding point cloud interval to construct a three-dimensional model of the object in the virtual space.

[0012] Furthermore, in step S2, determining the frame area and frame area parameters of each surface area of ​​the object according to the preliminary modeling data includes:

[0013] Determine the plane curvature of each local area on the surface of the object based on the preliminary modeling data;

[0014] Determine a local area whose plane curvature is greater than a predetermined plane curvature threshold as a frame area;

[0015] The number of frame regions and the frame region average planar curvature are determined as frame region parameters.

[0016] Furthermore, in step S2, the environmental interference modeling characterization parameter for the object is calculated according to formula (1):

[0017] (1)

[0018] In formula (1), H represents the environmental interference modeling characterization parameter, N represents the number of frame areas, N0 represents the preset standard threshold of the number of frame areas, S represents the average plane curvature of the frame area, S0 represents the preset standard threshold of the average plane curvature of the frame area, A represents the vibration amplitude of the object setting area, A0 represents the preset standard threshold of the vibration amplitude of the object setting area, F represents the vibration frequency of the object setting area, and F0 represents the preset standard threshold of the vibration frequency of the object setting area.

[0019] Furthermore, in step S2, the environmental interference modeling complexity categories of the object are divided into:

[0020] If the environmental interference modeling characterization parameter is greater than or equal to a preset environmental interference modeling characterization standard threshold, the environmental interference modeling complexity category is determined to be an environmental interference modeling high complexity category;

[0021] If the environmental interference modeling characterization parameter is less than a preset environmental interference modeling characterization standard threshold, the environmental interference modeling complexity category is determined to be an environmental interference modeling low complexity category.

[0022] Furthermore, in step S3, adjusting the modeling data acquisition method and constructing the three-dimensional model of the object in the virtual space includes:

[0023] If the environmental interference modeling complexity category is the environmental interference modeling high complexity category, the acquisition end is controlled to scan the point cloud data of the surface area of ​​the object with a preset high point cloud interval standard, and when scanning, a specific area is determined according to the frame area of ​​each local area of ​​the surface of the object, and the scanning frequency for the specific area is adjusted, so as to adjust the modeling parameters based on the environmental interference modeling characterization parameters, and then construct the three-dimensional model of the object with the corresponding rendering parameters in the virtual space;

[0024] If the environmental interference modeling complexity category is the environmental interference modeling low complexity category, the point cloud interval is adjusted according to the environmental interference modeling characterization parameter, and the point cloud data of the surface area of ​​the object is scanned with the corresponding point cloud interval to construct a three-dimensional model of the object in the virtual space.

[0025] Furthermore, in step S3, the specific area is determined according to the frame area parameters of each local area of ​​the object surface during scanning.

[0026] If the number of frame areas is greater than a preset standard threshold of the number of frame areas and the average plane curvature of the frame areas is greater than a preset standard threshold of the average plane curvature of the frame areas, the local area is determined to be a specific area.

[0027] Furthermore, in step S3, adjusting the scanning frequency for the specific area includes:

[0028] The scanning frequency for specific areas was increased, and the increase was positively correlated with the number of frame areas.

[0029] Furthermore, in step S3, adjusting the modeling parameters based on the environmental interference modeling characterization parameters includes:

[0030] The adjusted modeling parameters are positively correlated with the environmental interference modeling characterization parameters;

[0031] The modeling parameters include the number of grids and texture resolution.

[0032] Furthermore, in step S3, adjusting the point cloud interval according to the environmental interference modeling characterization parameter includes:

[0033] The distance between the adjusted point clouds is negatively correlated with the environmental interference modeling characterization parameter.

[0034] Furthermore, in step S1, the process of moving and acquiring the environmental data of objects in each area of ​​the actual scene includes:

[0035] Determine key points within the object setting area;

[0036] Collect the vibration amplitude and frequency of key points;

[0037] The distance between the key point and the edge contour of the bottom surface of the object must be less than a predetermined distance threshold.

[0038] Compared with the prior art, the present invention obtains preliminary modeling data and environmental data of objects in various areas of the actual scene by controlling the movement of the acquisition end, determines the frame area and frame area parameters of the object surface according to the preliminary modeling data, calculates the environmental interference modeling characterization parameters for the object according to the frame area parameters combined with the environmental data, divides the complex category of the environmental interference modeling of the object, adaptively adjusts the modeling data acquisition method and constructs a three-dimensional model of the object in the virtual space, thereby reducing the impact of environmental factors on the quality of the collected modeling data and improving the reliability of the acquired modeling data. At the same time, it adapts well to scene changes, reasonably allocates computing resources, and reduces the waste of computing resources.

[0039] In particular, the present invention calculates the environmental interference modeling characterization parameters for the object by combining the framework area parameters with the environmental data. When the acquisition end moves to different areas in the actual scene, the morphological characteristics of the object are different, and the environmental influences in different areas are different. Then, the present invention acquires the surface point cloud data with a lower point cloud interval standard, analyzes the morphological characteristics of the object with a smaller amount of data, and characterizes the complexity of the object and the number of detailed features through the framework area parameters of the object. In actual situations, the larger the object framework area parameters, the more detailed features of the object, and the amount of point cloud data required to reflect the corresponding features is different. Especially under the interference of environmental data, the higher the vibration frequency means the more unstable the acquisition process is, which will amplify the influence of the above factors. Then, the environmental interference modeling characterization parameters are calculated by combining the framework area parameters with the environmental data, and the modeling complexity of each object under the influence of the environment is characterized, providing data support for the subsequent classification of the complex category of environmental interference modeling of the object, and then, it is convenient to adaptively adjust the modeling data acquisition method and build a three-dimensional model of the object in the virtual space, and then, reduce the influence of environmental factors on the quality of the collected modeling data, improve the reliability of the acquired modeling data, and at the same time, well adapt to scene changes, reasonably allocate computing resources, and reduce the waste of computing resources.

[0040] In particular, the present invention determines the specific area through the framework area parameters of each local area on the surface of the object. In actual situations, the higher the complexity of the local object, the more details the structure of the object has, and the higher the demand for point cloud data, so as to ensure that the details of the object can be accurately captured and reproduced. Therefore, the present application determines the specific area through the framework area parameters of the local area, and adjusts the scanning frequency of the specific area to ensure that the influence of movement, environmental factors and the morphological differences of the object itself on the three-dimensional model acquisition process is reduced in the process of continuous movement and construction of the three-dimensional model at the acquisition end. At the same time, after adjusting the modeling parameters based on the environmental interference modeling characterization parameters, the three-dimensional model of the object is constructed in the virtual space with the corresponding modeling parameters, so as to maintain the smoothness of continuous modeling in the virtual space, flexibly allocate computing power resources, and thus reduce the influence of environmental factors on the quality of the collected modeling data, improve the reliability of the acquired modeling data, and at the same time, well adapt to scene changes, reasonably allocate computing power resources, and reduce the waste of computing power resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 A schematic diagram of the steps of a three-dimensional modeling method according to an embodiment of the invention;

[0042] Figure 2 A logical decision diagram for classifying complex categories of environmental interference modeling for embodiments of the invention;

[0043] Figure 3 A logical decision diagram for adjusting the modeling data acquisition method for the embodiment of the invention;

[0044] Figure 4 Logic decision diagram for determining unique regions for embodiments of the invention. DETAILED DESCRIPTION

[0045] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0046] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0047] See also Figures 1 to 4 As shown, Figure 1 A schematic diagram of the steps of the three-dimensional modeling method of an embodiment of the invention is shown. Figure 2 A logical decision diagram for classifying complex categories of environmental interference modeling for embodiments of the invention, Figure 3 A logical decision diagram for adjusting the modeling data acquisition method for the embodiment of the invention, Figure 4To determine a logical decision diagram for a specific region in an embodiment of the invention, a three-dimensional modeling method in an embodiment of the invention includes:

[0048] Step S1, controlling the acquisition end to move and acquire preliminary modeling data and environmental data of objects in various regions in the actual scene, wherein the preliminary modeling data includes surface point cloud data acquired with a preset low point cloud interval standard for the object, and the environmental data includes vibration amplitude and vibration frequency of the object setting region;

[0049] Step S2, determining the frame area and frame area parameters of the object surface according to the preliminary modeling data, calculating the environmental interference modeling characterization parameters for the object according to the frame area parameters combined with the environmental data, and classifying the environmental interference modeling complexity category of the object;

[0050] Step S3, adjusting the modeling data acquisition method and constructing a three-dimensional model of the object in a virtual space according to the complexity category of the environmental interference modeling of the object, including:

[0051] Controlling the acquisition end to scan the point cloud data of the surface area of ​​the object with a preset high point cloud interval standard, determining the specific area according to the frame area parameters of each local area of ​​the surface of the object during scanning, adjusting the scanning frequency for the specific area, and constructing the three-dimensional model of the object with the corresponding modeling parameters in the virtual space after adjusting the modeling parameters based on the environmental interference modeling characterization parameters;

[0052] Alternatively, the point cloud interval is adjusted according to the environmental interference modeling characterization parameter, and the point cloud data of the surface area of ​​the object is scanned with the corresponding point cloud interval to construct a three-dimensional model of the object in the virtual space.

[0053] Specifically, it can be understood that the three-dimensional model is constructed based on the collected point cloud data. The purpose of setting the low point cloud interval standard is to preliminarily construct a three-dimensional model through a lower point cloud interval to preliminarily characterize the object shape. The low point cloud interval standard is that the point cloud interval of the acquired point cloud data is within the preset low point cloud interval range, and the low point cloud interval range is [5cm, 20cm].

[0054] Similarly, the high point cloud interval standard is that the point cloud interval of the acquired point cloud data is within the high point cloud interval range, and the high point cloud interval range is determined based on the low point cloud interval range, preferably, between 0.2 and 0.3 times the low point cloud interval range.

[0055] Specifically, the collection end is a movable collection device for collecting modeling data. For example, a scanning device can be mounted on a remote-controlled vehicle. The scanning device can be set on a device that can adjust the scanning direction, such as a robotic arm, to meet the needs of scanning objects at different positions in the actual scene. Of course, other forms can also be used, which will not be repeated here.

[0056] Specifically, there is no limitation on the specific method of obtaining the surface point cloud data of the object. Preferably, a laser scanner can be used to determine the surface point cloud data of the object. Of course, other forms can also be used. This is the existing technology and will not be described in detail.

[0057] Specifically, there is no limitation on the equipment for collecting environmental data. It is only necessary to provide an instrument for obtaining the environmental vibration amplitude and vibration frequency. For example, a laser vibration sensor is used to obtain the environmental vibration amplitude and vibration frequency of key points in the object setting area. The same laser vibration sensor can be mounted on a device that can adjust the detection direction, such as a robotic arm, to meet the function of obtaining the vibration amplitude and vibration frequency at different key points. I will not go into details here.

[0058] Specifically, in step S2, determining the frame area and frame area parameters of each surface area of ​​the object according to the preliminary modeling data includes:

[0059] Determine the plane curvature of each local area on the surface of the object based on the preliminary modeling data;

[0060] Determine a local area whose plane curvature is greater than a predetermined plane curvature threshold as a frame area;

[0061] determining the number of frame regions and the average planar curvature of the frame regions as frame region parameters;

[0062] Specifically, the plane curvature is the average of the Gaussian curvatures corresponding to several points in the local area.

[0063] The plane curvature threshold M0 is obtained in advance by obtaining a number of preliminary modeling data samples, solving the mean plane curvature ΔM of each local area, and setting M0=ΔM×m, 0.7<m<0.8, and m represents the offset coefficient.

[0064] Specifically, in step S2, the environmental interference modeling characterization parameter for the object is calculated according to formula (1):

[0065] (1)

[0066] In formula (1), H represents the environmental interference modeling characterization parameter, N represents the number of frame areas, N0 represents the preset standard threshold of the number of frame areas, S represents the average plane curvature of the frame area, S0 represents the preset standard threshold of the average plane curvature of the frame area, A represents the vibration amplitude of the object setting area, A0 represents the preset standard threshold of the vibration amplitude of the object setting area, F represents the vibration frequency of the object setting area, and F0 represents the preset standard threshold of the vibration frequency of the object setting area.

[0067] Specifically, in this embodiment, the standard threshold value N0 for the number of frame areas, the standard threshold value S0 for the average plane curvature of the frame areas, the standard threshold value A0 for the vibration amplitude of the object setting area, and the standard threshold value F0 for the vibration frequency of the object setting area are pre-set, object modeling data of several areas and environmental vibration conditions of the object setting areas are obtained, and the average value ∆N0 for the number of frame areas, the average value ∆S0 for the average plane curvature of the frame areas, the average value ∆A0 for the vibration amplitude of the object setting area, and the average value ∆F0 for the vibration frequency of the object setting area are solved, and N0=r1×∆N0, S0=r1×∆S0, A0=r2×∆A0, F0=r2×∆F0 are set, wherein r1 represents the first precision coefficient, r2 represents the second precision coefficient, 1.1<r1<1.15, 1.15<r2<1.25.

[0068] Specifically, the present invention calculates the environmental interference modeling characterization parameters for the object by combining the framework area parameters with the environmental data. When the acquisition end moves to different areas in the actual scene, the morphological characteristics of the object are different, and the environmental influences in different areas are different. Then, the present invention acquires the surface point cloud data with a lower point cloud interval standard, analyzes the morphological characteristics of the object with a smaller amount of data, and characterizes the complexity of the object and the number of detailed features through the framework area parameters of the object. In actual situations, the larger the object framework area parameters, the more detailed features of the object, and the amount of point cloud data required to reflect the corresponding features is different. Especially under the interference of environmental data, the higher the vibration frequency means the more unstable the acquisition process is, which will amplify the influence of the above factors. Then, the environmental interference modeling characterization parameters are calculated by combining the framework area parameters with the environmental data, and the modeling complexity of each object under the influence of the environment is characterized, providing data support for the subsequent classification of the complex category of environmental interference modeling of the object, and then, it is convenient to adaptively adjust the modeling data acquisition method and build a three-dimensional model of the object in the virtual space, and then, reduce the influence of environmental factors on the quality of the collected modeling data, improve the reliability of the acquired modeling data, and at the same time, well adapt to scene changes, reasonably allocate computing resources, and reduce the waste of computing resources.

[0069] Specifically, in step S2, the complex categories of environmental interference modeling of the object are divided into:

[0070] If the environmental interference modeling characterization parameter is greater than or equal to a preset environmental interference modeling characterization standard threshold, the environmental interference modeling complexity category is determined to be an environmental interference modeling high complexity category;

[0071] If the environmental interference modeling characterization parameter is less than a preset environmental interference modeling characterization standard threshold, the environmental interference modeling complexity category is determined to be an environmental interference modeling low complexity category.

[0072] Specifically, in step S3, adjusting the modeling data acquisition method and constructing the three-dimensional model of the object in the virtual space includes:

[0073] If the environmental interference modeling complexity category is the environmental interference modeling high complexity category, the acquisition end is controlled to scan the point cloud data of the surface area of ​​the object with a preset high point cloud interval standard, and when scanning, a specific area is determined according to the frame area of ​​each local area of ​​the surface of the object, and the scanning frequency for the specific area is adjusted, so as to adjust the modeling parameters based on the environmental interference modeling characterization parameters, and then construct the three-dimensional model of the object with the corresponding rendering parameters in the virtual space;

[0074] If the environmental interference modeling complexity category is the environmental interference modeling low complexity category, the point cloud interval is adjusted according to the environmental interference modeling characterization parameter, and the point cloud data of the surface area of ​​the object is scanned with the corresponding point cloud interval to construct a three-dimensional model of the object in the virtual space.

[0075] Specifically, in step S3, the specific area is determined according to the frame area parameters of each local area on the surface of the object during scanning.

[0076] If the number of frame areas is greater than a preset standard threshold of the number of frame areas and the average plane curvature of the frame areas is greater than a preset standard threshold of the average plane curvature of the frame areas, the local area is determined to be a specific area.

[0077] Specifically, the present invention determines the specific area through the framework area parameters of each local area on the surface of the object. In actual situations, the higher the complexity of the local object, the more details the structure of the object has, and the higher the demand for point cloud data, so as to ensure that the details of the object can be accurately captured and reproduced. Therefore, the present application determines the specific area through the framework area parameters of the local area, and adjusts the scanning frequency of the specific area to ensure that the influence of movement, environmental factors and the morphological differences of the object itself on the three-dimensional model acquisition process is reduced in the process of continuous movement and construction of the three-dimensional model at the acquisition end. At the same time, after adjusting the modeling parameters based on the environmental interference modeling characterization parameters, the three-dimensional model of the object is constructed in the virtual space with the corresponding modeling parameters, so as to maintain the smoothness of continuous modeling in the virtual space, flexibly allocate computing power resources, and thus reduce the influence of environmental factors on the quality of the collected modeling data, improve the reliability of the acquired modeling data, and at the same time, well adapt to scene changes, reasonably allocate computing power resources, and reduce the waste of computing power resources.

[0078] Specifically, in step S3, adjusting the scanning frequency for the specific area includes:

[0079] The scanning frequency for specific areas was increased, and the increase was positively correlated with the number of frame areas.

[0080] In this embodiment, optionally,

[0081] The number of frame areas N is compared with a first frame area number comparison threshold N1 and a second frame area number comparison threshold N2,

[0082] If N>N2, the scanning frequency increase amount is determined to be the first scanning frequency increase amount c1, and c1=0.4×c0 is set;

[0083] If N1≤N≤N2, the scanning frequency increase amount is determined to be the second scanning frequency increase amount c2, and c2=0.3×c0 is set;

[0084] If N<N1, the scanning frequency increase amount is determined to be the third scanning frequency increase amount c3, and c3=0.2×c0 is set;

[0085] Wherein, c0 represents the standard scanning frequency, N1=1.1×N0, N2=1.3×N0.

[0086] Specifically, in step S3, adjusting the modeling parameters based on the environmental interference modeling characterization parameters includes:

[0087] The adjusted modeling parameters are positively correlated with the environmental interference modeling characterization parameters;

[0088] The modeling parameters include the number of grids and texture resolution.

[0089] In this embodiment, optionally,

[0090] The environmental interference modeling characterization parameter H is compared with the first environmental interference modeling characterization parameter H1 and the second environmental interference modeling characterization parameter H2, and the number of grids is adjusted, wherein:

[0091] If H>H2, adjust to the first grid number z1, setting z1=1.25×z0;

[0092] If H1≤H≤H2, adjust to the second grid number z2, and set z2=1.1×z0;

[0093] If H

[0094] Among them, z0 represents the initial grid number, H1=1.1×H0, H2=1.2×H0,

[0095] H0 represents the standard threshold for environmental interference modeling characterization, and H0 is selected within the interval [2.05,2.15].

[0096] The environmental interference modeling characterization parameter H is compared with the first environmental interference modeling characterization parameter H1 and the second environmental interference modeling characterization parameter H2 to adjust the texture resolution, wherein:​

[0097] If H>H2, adjust to the first texture resolution d1, setting d1=1.3×d0;

[0098] If H1≤H≤H2, adjust to the second texture resolution d2, and set d2=1.15×d0;

[0099] If H

[0100] Among them, d0 represents the standard texture resolution, H1=1.1×H0, H2=1.2×H0.

[0101] Specifically, there is no specific limitation on the method of increasing the number of 3D modeling grids. For example, the number of corresponding 3D modeling grids during 3D modeling can be increased through relevant subdivision surface algorithms. This is a prior art and will not be elaborated on.

[0102] Specifically, there is no specific limitation on the method of improving the texture resolution of the 3D model. For example, the texture resolution of the 3D model when rendering the 3D model can be improved by using a related compression algorithm. This is a prior art and will not be described in detail.

[0103] Specifically, in step S3, adjusting the point cloud interval according to the environmental interference modeling characterization parameter includes:

[0104] The distance between the adjusted point clouds is negatively correlated with the environmental interference modeling characterization parameter.

[0105] In this embodiment, optionally,

[0106] The environmental interference modeling characterization parameter is compared with the first environmental interference modeling characterization parameter and the second environmental interference modeling characterization parameter,

[0107] If H>H2, the point cloud interval distance is determined to be the first point cloud interval distance q1, and q1=0.85×h0 is set;

[0108] If H1≤H≤H2, the point cloud interval distance is determined to be the second point cloud interval distance q2, and q2=0.75×q0 is set;

[0109] If H

[0110] Among them, q0 represents the current point cloud interval distance, H1=1.1×H0, H2=1.2×H0.

[0111] Specifically, in step S1, the process of moving and acquiring the environmental data of objects in each area of ​​the actual scene includes: ​​

[0112] Determine key points within the object setting area;

[0113] Collect the vibration amplitude and frequency of key points;

[0114] The distance between the key point and the edge contour of the bottom surface of the object must be less than the predetermined distance threshold.

[0115] Specifically, the predetermined distance threshold is selected within the interval [10 cm, 20 cm].

[0116] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

1. A three-dimensional modeling method, characterized in that: include: Step S1, controlling the acquisition end to move and acquire preliminary modeling data and environmental data of objects in various regions in the actual scene, wherein the preliminary modeling data includes surface point cloud data acquired with a preset low point cloud interval standard for the object, and the environmental data includes vibration amplitude and vibration frequency of the object setting region; Step S2, determining the frame area and frame area parameters of the object surface according to the preliminary modeling data, calculating the environmental interference modeling characterization parameters for the object according to the frame area parameters combined with the environmental data, and classifying the environmental interference modeling complexity category of the object; Step S3, adjusting the modeling data acquisition method and constructing a three-dimensional model of the object in a virtual space according to the complexity category of the environmental interference modeling of the object, including: If the environmental interference modeling complexity category is the environmental interference modeling high complexity category, the acquisition end is controlled to scan the point cloud data of the surface area of ​​the object with a preset high point cloud interval standard, and when scanning, the specific area is determined according to the frame area parameters of each local area of ​​the surface of the object, and the scanning frequency for the specific area is adjusted, so as to adjust the modeling parameters based on the environmental interference modeling characterization parameters, and then construct the three-dimensional model of the object with the corresponding modeling parameters in the virtual space; If the environmental interference modeling complexity category is an environmental interference modeling low complexity category, adjusting the point cloud interval according to the environmental interference modeling characterization parameter, scanning the point cloud data of the surface area of ​​the object with the corresponding point cloud interval, and constructing a three-dimensional model of the object in the virtual space; In step S2, the environmental interference modeling characterization parameter for the object is calculated according to formula (1): （1） In formula (1), H represents the environmental interference modeling characterization parameter, N represents the number of frame areas, N0 represents the preset standard threshold of the number of frame areas, S represents the average plane curvature of the frame area, S0 represents the preset standard threshold of the average plane curvature of the frame area, A represents the vibration amplitude of the object setting area, A0 represents the preset standard threshold of the vibration amplitude of the object setting area, F represents the vibration frequency of the object setting area, and F0 represents the preset standard threshold of the vibration frequency of the object setting area; In step S3, the specific area is determined according to the frame area parameters of each local area on the surface of the object during scanning. If the number of frame areas is greater than a preset standard threshold of the number of frame areas and the average plane curvature of the frame areas is greater than a preset standard threshold of the average plane curvature of the frame areas, then the local area is determined to be a specific area; In step S2, the complex categories of environmental interference modeling of the object are divided into: If the environmental interference modeling characterization parameter is greater than or equal to a preset environmental interference modeling characterization standard threshold, the environmental interference modeling complexity category is determined to be an environmental interference modeling high complexity category; If the environmental interference modeling characterization parameter is less than a preset environmental interference modeling characterization standard threshold, the environmental interference modeling complexity category is determined to be an environmental interference modeling low complexity category.

2. The three-dimensional modeling method according to claim 1, characterized in that: In the step S2, determining the frame area and frame area parameters of each surface area of ​​the object according to the preliminary modeling data includes: Determine the plane curvature of each local area on the surface of the object based on the preliminary modeling data; Determine a local area whose plane curvature is greater than a predetermined plane curvature threshold as a frame area; The number of frame regions and the frame region average planar curvature are determined as frame region parameters.

3. The three-dimensional modeling method according to claim 1, characterized in that: In step S3, adjusting the scanning frequency for the specific area includes: The scanning frequency for specific areas was increased, and the increase was positively correlated with the number of frame areas.

4. The three-dimensional modeling method according to claim 1, characterized in that: In step S3, adjusting the modeling parameters based on the environmental interference modeling characterization parameters includes: The adjusted modeling parameters are positively correlated with the environmental interference modeling characterization parameters; The modeling parameters include the number of grids and texture resolution.

5. The three-dimensional modeling method according to claim 1, characterized in that: In step S3, adjusting the point cloud interval according to the environmental interference modeling characterization parameter includes: The distance between the adjusted point clouds is negatively correlated with the environmental interference modeling characterization parameter.

6. The three-dimensional modeling method according to claim 1, characterized in that: In step S1, the process of moving and acquiring the environmental data of objects in each area of ​​the actual scene includes: Determine key points within the object setting area; Collect the vibration amplitude and frequency of key points; The distance between the key point and the edge contour of the bottom surface of the object must be less than a predetermined distance threshold.

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