Three-dimensional modeling method and device based on panoramic vision laser scanner

Abstract

The embodiment of the invention discloses a three-dimensional modeling method and device based on a panoramic vision laser scanner, and the method comprises the steps: carrying out the comprehensive scanning of a target scene based on the panoramic vision laser scanner according to a preset scanning path, so as to collect scene data, wherein the scene data comprises three-dimensional coordinate information, RGB color information, and texture information; preprocessing the scene data, generating point cloud data, and generating ellipsoid distribution data of a three-dimensional space based on the point cloud data; and establishing a three-dimensional model of the target scene based on the ellipsoid distribution data. According to the embodiment, the defects of a traditional method in the aspects of visual effect, precision and automation degree are overcome, a brand new solution is provided for rapid modeling of a large-scale scene with lower cost and higher efficiency, the centimeter-level precision standard is achieved, and a user can experience immersive feeling in a virtual space. Meanwhile, the high-precision point cloud data can also be widely applied to a plurality of fields such as topographic surveying and mapping, geological survey and forestry survey.

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 and device based on a panoramic vision laser scanner. Background Art

[0002] At present, in the construction of the digital world, visual reality and efficient modeling have always been the focus of attention inside and outside the industry. Today, mainstream large-scale scene modeling methods, such as panoramic images, laser point clouds, mesh models, etc., all have their own advantages, but also have their own limitations. The panoramic visual effect is very good, but lacks precision, and it is not a real "model" and can only be browsed in a step-by-step manner; the mesh model is highly versatile and editable, but the modeling effect is not satisfactory and requires a lot of manual post-processing; although the accuracy of the laser point cloud is guaranteed, the visual effect is difficult to satisfy people.

[0003] At present, most industries that need indoor modeling use manual modeling. The software used is mostly 3D Max, Maya, Blender, etc., and a white model is built manually, and then the corresponding texture is pasted on the white model to make a simulation model. Not only does it require a lot of manpower and material resources, it is difficult to make it exactly the same as the actual scene, so the model effect is distorted compared to the actual scene. Summary of the invention

[0004] In view of the above-mentioned defects, an embodiment of the present invention discloses a three-dimensional modeling method and device based on a panoramic vision laser scanner, which has convenient data collection and automated modeling.

[0005] A first aspect of an embodiment of the present invention discloses a three-dimensional modeling method based on a panoramic vision laser scanner, comprising:

[0006] Based on the panoramic vision laser scanner, the target scene is fully scanned according to the preset scanning path to collect scene data, and the scene data includes three-dimensional coordinate information, RGB color information, and texture information;

[0007] Preprocessing the scene data to generate point cloud data, and generating ellipsoid distribution data in three-dimensional space based on the point cloud data;

[0008] A three-dimensional model of the target scene is established based on the ellipsoidal distribution data.

[0009] As an optional implementation manner, in the first aspect of the embodiment of the present invention, the preprocessing of the scene data and generating point cloud data includes:

[0010] Performing filtering on the scene data to remove noise points in the scene data after filtering;

[0011] The three-dimensional coordinate information of the scene data is obtained, and the three-dimensional coordinate information is spliced ​​and matched to form point cloud data.

[0012] As an optional implementation manner, in the first aspect of the embodiment of the present invention, generating ellipsoidal distribution data in three-dimensional space based on the point cloud data includes:

[0013] Loading pre-stored ellipsoid parameters to perform coordinate transformation on the point cloud data to generate ellipsoid distribution data in three-dimensional space;

[0014] Alternatively, a number of control points are selected from the point cloud data, parameters of the control end are calculated to obtain ellipsoid parameters, and coordinate transformation is performed on the point cloud data according to the ellipsoid parameters to generate ellipsoid distribution data in three-dimensional space.

[0015] As an optional implementation manner, in the first aspect of the embodiment of the present invention, establishing a three-dimensional model of the target scene based on the ellipsoidal distribution data includes:

[0016] Construct a three-dimensional geometric model of the target scene based on the ellipsoid distribution data;

[0017] The texture information is mapped to the surface of the three-dimensional geometric model according to a texture mapping algorithm to form a three-dimensional model.

[0018] As an optional implementation manner, in the first aspect of the embodiment of the present invention, before performing preprocessing on the scene data, the method further includes:

[0019] In response to an account login instruction from a target user, obtaining the target user's account information and performing account verification on the account information;

[0020] When the account verification is successful, log in to the modeling space corresponding to the target user.

[0021] As an optional implementation manner, in the first aspect of the embodiment of the present invention, it also includes:

[0022] receiving a spatial viewing instruction input by a target user, and acquiring a viewing mode and a first position of the spatial viewing instruction, wherein the viewing modes include first-person viewing, digital human viewing, and pivot viewing;

[0023] A target location corresponding to the three-dimensional model is acquired according to the first position, and the three-dimensional model is played with the target location as a starting point according to the viewing mode and the moving path input by the target user.

[0024] As an optional implementation manner, in the first aspect of the embodiment of the present invention, it also includes:

[0025] Receive a spatial measurement instruction input by a target user, and obtain a measurement method, a measurement start point, and a measurement end point carried in the spatial measurement instruction;

[0026] Calculate the measured distance or measured area based on the measurement method, measurement start point and measurement end point.

[0027] A second aspect of an embodiment of the present invention discloses a three-dimensional modeling device based on a panoramic vision laser scanner, comprising:

[0028] Data acquisition module: used to comprehensively scan the target scene according to a preset scanning path based on a panoramic vision laser scanner to collect scene data, wherein the scene data includes three-dimensional coordinate information, RGB color information, and texture information;

[0029] Data processing module: used for preprocessing the scene data and generating point cloud data, and generating ellipsoid distribution data in three-dimensional space based on the point cloud data;

[0030] Model creation module: used to establish a three-dimensional model of the target scene based on the ellipsoid distribution data.

[0031] As an optional implementation manner, in the second aspect of the embodiment of the present invention, the preprocessing of the scene data and generating point cloud data includes:

[0032] Performing filtering on the scene data to remove noise points in the scene data after filtering;

[0033] The three-dimensional coordinate information of the scene data is obtained, and the three-dimensional coordinate information is spliced ​​and matched to form point cloud data.

[0034] As an optional implementation, in the second aspect of the embodiment of the present invention, generating ellipsoid distribution data in three-dimensional space based on the point cloud data includes:

[0035] Loading pre-stored ellipsoid parameters to perform coordinate transformation on the point cloud data to generate ellipsoid distribution data in three-dimensional space;

[0036] Alternatively, a number of control points are selected from the point cloud data, parameters of the control end are calculated to obtain ellipsoid parameters, and coordinate transformation is performed on the point cloud data according to the ellipsoid parameters to generate ellipsoid distribution data in three-dimensional space.

[0037] As an optional implementation manner, in the second aspect of the embodiment of the present invention, establishing a three-dimensional model of the target scene based on the ellipsoid distribution data includes:

[0038] Construct a three-dimensional geometric model of the target scene based on the ellipsoid distribution data;

[0039] The texture information is mapped to the surface of the three-dimensional geometric model according to a texture mapping algorithm to form a three-dimensional model.

[0040] As an optional implementation manner, in the second aspect of the embodiment of the present invention, before performing preprocessing on the scene data, the method further includes:

[0041] In response to an account login instruction from a target user, obtaining the target user's account information and performing account verification on the account information;

[0042] When the account verification is successful, log in to the modeling space corresponding to the target user.

[0043] As an optional implementation manner, in the second aspect of the embodiment of the present invention, it also includes:

[0044] receiving a spatial viewing instruction input by a target user, and acquiring a viewing mode and a first position of the spatial viewing instruction, wherein the viewing modes include first-person viewing, digital human viewing, and pivot viewing;

[0045] A target location corresponding to the three-dimensional model is acquired according to the first position, and the three-dimensional model is played with the target location as a starting point according to the viewing mode and the moving path input by the target user.

[0046] As an optional implementation manner, in the second aspect of the embodiment of the present invention, it also includes:

[0047] Receive a spatial measurement instruction input by a target user, and obtain a measurement method, a measurement start point, and a measurement end point carried in the spatial measurement instruction;

[0048] Calculate the measured distance or measured area based on the measurement method, measurement start point and measurement end point.

[0049] The third aspect of an embodiment of the present invention discloses an electronic device, comprising: a memory storing executable program code; a processor coupled to the memory; the processor calls the executable program code stored in the memory to execute the three-dimensional modeling method based on the panoramic vision laser scanner disclosed in the first aspect of the embodiment of the present invention.

[0050] A fourth aspect of an embodiment of the present invention discloses a computer-readable storage medium storing a computer program, wherein the computer program enables a computer to execute the three-dimensional modeling method based on a panoramic vision laser scanner disclosed in the first aspect of an embodiment of the present invention.

[0051] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0052] In the embodiment of the present invention, a panoramic vision laser scanner is used to collect data of the target scene, so that the data of the required scene can be quickly and comprehensively acquired. There is no need to rely on a tripod and static scanning at a fixed position. It can be operated in a handheld manner, and acquisition can be achieved while walking. The scanning speed is fast, and the data acquisition is fast and flexible. In addition, a panoramic vision camera is installed to acquire panoramic data of the target scene. After that, the acquired scene data is preprocessed, and cleaner and noise-free data is obtained by preprocessing the data to improve the data quality. After generating the point cloud data, the ellipsoid distribution data is continuously generated, which can reflect the shape, size and position relationship of the objects in the target scene. By subdividing the ellipsoid distribution data, the ellipsoid units of different objects and regions can be distinguished, thereby enhancing the detail expression capability of the three-dimensional model. The embodiment uses computer computing power to automatically generate a three-dimensional model based on the acquired data in one click, without manual intervention, which greatly saves manpower and saves the time cost of model generation. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0054] Figure 1 It is a flow chart of a three-dimensional modeling method based on a panoramic vision laser scanner disclosed in an embodiment of the present invention;

[0055] Figure 2 It is a flowchart of another three-dimensional modeling method based on a panoramic vision laser scanner disclosed in an embodiment of the present invention;

[0056] Figure 3 It is a flowchart of another three-dimensional modeling method based on a panoramic vision laser scanner disclosed in an embodiment of the present invention;

[0057] Figure 4 It is a structural schematic diagram of a three-dimensional modeling device based on a panoramic vision laser scanner provided by an embodiment of the present invention;

[0058] Figure 5 It is a structural schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0059] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] It should be noted that the terms "first", "second", "third", "fourth", etc. in the specification and claims of the present invention are used to distinguish different objects rather than to describe a specific order. The terms "including" and "having" in the embodiments of the present invention and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device including a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0061] The embodiment of the present invention discloses a 3D modeling method, device, electronic device and storage medium based on a panoramic vision laser scanner. In the embodiment, a panoramic vision laser scanner is used to collect data of a target scene, so that data of the required scene can be quickly and comprehensively obtained, without relying on a tripod and static scanning at a fixed position, and can be operated in a handheld manner, so that collection can be achieved while walking, with fast scanning speed, fast and flexible data collection, and a panoramic vision camera is installed to obtain panoramic data of the target scene; then, the collected scene data is preprocessed, and cleaner and noise-free data is obtained by intervening in the data through preprocessing, thereby improving data quality; after generating point cloud data, ellipsoid distribution data is continuously generated, which can reflect the shape, size and position relationship of objects in the target scene, and ellipsoid units of different objects and regions can be distinguished by subdividing the ellipsoid distribution data, thereby enhancing the detail expression capability of the 3D model; the embodiment uses computer computing power to automatically generate a 3D model based on the collected data in one click, without manual intervention, thereby greatly saving manpower and saving model generation time cost.

[0062] Embodiment 1

[0063] See also Figure 1 , Figure 1It is a flow chart of a three-dimensional modeling method based on a panoramic vision laser scanner disclosed in an embodiment of the present invention. Among them, the execution subject of the method described in the embodiment of the present invention is an execution subject composed of software and / or hardware, and the execution subject can receive relevant information by wired or / and wireless means, and can send certain instructions. Of course, it can also have certain processing functions and storage functions. The execution subject can control multiple devices, such as a remote physical server or cloud server and related software, or it can be a local host or server and related software that performs related operations on a device placed somewhere. In some scenarios, multiple storage devices can also be controlled, and the storage devices can be placed in the same place or different places as the devices. For example Figure 1 As shown, the 3D modeling method based on panoramic vision laser scanner includes the following steps:

[0064] 101. Based on the panoramic vision laser scanner, a target scene is fully scanned according to a preset scanning path to collect scene data, wherein the scene data includes three-dimensional coordinate information, RGB color information, and texture information.

[0065] The panoramic vision laser scanner of the embodiment is based on the laser scanner and equipped with a visual panoramic camera. It can quickly obtain the point cloud of the required scene by hand-held operation. The laser + visual positioning method no longer relies on a tripod and fixed-position static scanning. It can collect data while walking, with a scanning speed of up to 320,000 points / second and a measuring range of up to 300m. Through the 5G communication module, data can be transmitted back and previewed in real time. It achieves high efficiency, accuracy and portability in data collection.

[0066] Among them, the scene data collected by the panoramic vision laser scanner contains millions of three-dimensional coordinate points, which are the basis for the three-dimensional model. These three-dimensional coordinate information records the geometric shape and position information of the building surface. Each coordinate point has three coordinate values ​​of X, Y, and Z, which accurately represent the specific position of the point in three-dimensional space. In addition to the basic three-dimensional coordinate information, the scene data collected by the panoramic vision laser scanner in the embodiment also includes RGB color information, that is, the color information of each scanning point is obtained, which is represented by the values ​​of the three color channels of R (red), G (green), and B (blue). The color information helps to restore the true appearance of the target scene in the subsequent three-dimensional model. In addition, texture information can help analyze the material and texture of the building surface, and also help the model displayed after the subsequent three-dimensional modeling is completed to be more realistic.

[0067] 102. Preprocess the scene data and generate point cloud data, and generate ellipsoid distribution data in three-dimensional space based on the point cloud data.

[0068] After the original scene data is collected, the embodiment performs preprocessing on the data, including denoising and other operations. Denoising is to remove noise points in the point cloud data to ensure the quality of the data. Specifically, the scene data is filtered to remove noise points in the filtered scene data; the three-dimensional coordinate information of the scene data is obtained, and the three-dimensional coordinate information is spliced ​​and matched to form point cloud data.

[0069] According to the characteristics of the scene data and the type of noise, select a suitable filtering method. Common filtering methods include statistical filtering, radius filtering, voxel filtering, etc. Exemplarily, statistical filtering is to determine whether the point is a noise point based on the statistical characteristics of each point in the point cloud and its neighboring points (such as average distance, standard deviation, etc.). Radius filtering is to set a radius range and calculate the number of neighboring points of each point within the radius range. If the number of neighboring points is less than the set threshold, the point is considered to be a noise point. Voxel filtering is to divide the point cloud data into multiple small cubes (voxels) and downsample or average the points in each voxel to reduce the amount of data and noise. After selecting a suitable filtering method, the scene data is processed to remove noise points. During the filtering process, it may be necessary to adjust the filtering parameters according to the actual situation, such as the standard deviation threshold in statistical filtering, the radius size and the number of neighborhood points threshold in radius filtering, etc., to achieve the closest filtering effect.

[0070] In the process of generating point cloud data, since accurate three-dimensional coordinate data has been obtained in the early stage and the data has been preprocessed to ensure the quality, accuracy and consistency of the data, a suitable stitching method is selected according to the characteristics of the scene data and the stitching requirements. The selected stitching method is used to stitch and match the three-dimensional coordinate information collected from multiple perspectives or different positions. During the stitching process, it may be necessary to adjust the stitching parameters (such as the number of iterations and convergence threshold in the ICP algorithm) according to the actual situation to achieve the best stitching effect. After stitching, it is often necessary to verify and evaluate the stitching results to ensure the accuracy and reliability of the stitching. The stitched three-dimensional coordinate information is integrated into complete point cloud data, which can be used for subsequent three-dimensional reconstruction, visualization, analysis and other operations.

[0071] Generating ellipsoid distribution data in three-dimensional space based on the point cloud data includes: loading pre-stored ellipsoid parameters to perform coordinate transformation on the point cloud data to generate ellipsoid distribution data in three-dimensional space; or, selecting a number of control points from the point cloud data, performing parameter calculation on the control end to obtain ellipsoid parameters, and performing coordinate transformation on the point cloud data according to the ellipsoid parameters to generate ellipsoid distribution data in three-dimensional space.

[0072] Generating ellipsoid distribution data in three-dimensional space based on point cloud data is a task involving geometric processing and data analysis, which can be achieved in two ways in the embodiment, including using pre-stored ellipsoid parameters or directly calculating the ellipsoid parameters from point cloud data.

[0073] In the first method, the loaded ellipsoid parameters usually include the center position, major axis, end state and direction of the ellipsoid. After loading the ellipsoid parameters, the point cloud data is converted from the original coordinate system to the ellipsoid coordinate system, which usually involves translation, rotation and scaling operations to ensure that the point cloud data conforms to the expected ellipsoid distribution. After the coordinate transformation, the point cloud data will be presented as an ellipsoid shape distributed in three-dimensional space.

[0074] In the second method, the control points can be representative points evenly distributed in the point cloud data, or points selected by some algorithm such as clustering algorithm, meshing, etc. The ellipsoid parameters are calculated using traditional methods or geometric algorithms, which also involve the center, length and direction of the ellipsoid. Then, a similar coordinate transformation operation is performed on the original point cloud data according to the calculated ellipsoid parameters. After the transformation, the point cloud data will present a three-dimensional distribution that conforms to the calculated ellipsoid parameters. When selecting control points, ensure that they can represent the geometric characteristics of the entire point cloud data.

[0075] 103. Establish a three-dimensional model of the target scene based on the ellipsoid distribution data.

[0076] Figure 2 FIG. 4 is a flow chart showing another 3D modeling method based on a panoramic vision laser scanner provided by an embodiment of the present invention. Figure 2 As shown, the 3D modeling method based on panoramic vision laser scanner includes:

[0077] 201. Based on the panoramic vision laser scanner, a target scene is fully scanned according to a preset scanning path to collect scene data, wherein the scene data includes three-dimensional coordinate information, RGB color information, and texture information.

[0078] The panoramic vision laser scanner of the embodiment is a laser scanner with a visual panoramic camera. It can quickly obtain the point cloud of the required scene by hand-held operation. The laser + visual positioning method no longer relies on a tripod and fixed-position static scanning. It can collect data while walking, with a scanning speed of up to 320,000 points / second and a measuring range of up to 300m. Through the 5G communication module, data can be transmitted back and previewed in real time. It achieves high efficiency, accuracy and portability in data collection. Distance is usually measured by projecting a laser beam onto the surface of an object and receiving reflected light, while capturing RGB color information and texture information.

[0079] 202. In response to an account login instruction of a target user, obtain the account information of the target user, and perform account verification on the account information.

[0080] This step corresponds to the user's login. The embodiment is equivalent to providing an application platform that can be open to different users for application, so that everyone can collect original scene data for three-dimensional modeling. The user should first log in to the application platform. When the target user issues an account login instruction, the account information is obtained to ensure the authenticity of the user's identity. In the application platform, different account spaces are allocated to different accounts, and the three-dimensional model generated by the account is archived in its corresponding account space. The verification method can be but is not limited to the account + password method, or the account + password + SMS verification code, or the account + biometric method, etc.

[0081] 203. When the account verification is successful, log in to the modeling space corresponding to the target user.

[0082] When the verification is successful, the target user is guided to his / her exclusive modeling space for subsequent 3D modeling operations. In order to provide the target user with a personalized modeling space interface, customized toolbars, view settings, etc. may be included.

[0083] 204. Preprocess the scene data and generate point cloud data, and generate ellipsoid distribution data in three-dimensional space based on the point cloud data.

[0084] This step is to preprocess the scene data. The specific operations of preprocessing can also include filtering and denoising, and then generate point cloud data. Point cloud data is the geometry of a series of discrete points in three-dimensional space, and each point contains three-dimensional coordinate information. Based on point cloud data, geometries can be further generated, which is helpful for the subsequent construction of three-dimensional models.

[0085] 205. Establish a three-dimensional model of the target scene based on the ellipsoid distribution data.

[0086] The embodiment constructs a three-dimensional model of the target scene based on the ellipsoid distribution data, that is, converts the point cloud data into a mesh model, and uses texture and color information to enhance the visual effect of the model, which can improve interactivity.

[0087] Specifically, a three-dimensional geometric model of the target scene is constructed based on the ellipsoid distribution data; and texture information is mapped to the surface of the three-dimensional geometric model according to a texture mapping algorithm to form a three-dimensional model.

[0088] When collecting scene data, texture images have been collected, such as ground texture, ellipsoid surface texture, etc., and appropriate image processing software can be used to edit and optimize the texture to ensure that it is consistent with the scene style. In the provided application platform, that is, the 3D modeling software, the target user can independently select the texture mapping function to apply the texture information to the surface of the geometric element, ensure that the scale of the texture direction matches the model, and is correctly displayed in the final constructed 3D model.

[0089] 206 . Receive a spatial viewing instruction input by a target user, and obtain a viewing mode and a first position of the spatial viewing instruction, where the viewing modes include first-person viewing, digital human viewing, and pivot viewing.

[0090] The system monitors the input of the target user, such as the operation on the keyboard, mouse, touchpad or virtual reality device (such as VR helmet, handle). The user can trigger the space viewing instruction by clicking the corresponding menu selection, or by a specific key combination. When the user triggers the space viewing instruction, the system automatically captures the instruction. The viewing mode is extracted from the space viewing instruction. In the embodiment, there are three viewing modes, namely first-person viewing, digital human viewing and pivot viewing. Among them, the first-person viewing is also the target user seeing the space through the eyes. In this perspective, the screen displays the scene seen by the character lock, and the camera selects around its center, just like rotating the observer's head. The pivot mode is also the camera rotating around the pivot point in the scene, which is applicable to the global viewing mode and the editing mode. Since the panning camera will also synchronously offset the moving pivot point, when switching to the pivot mode, the center point is offset, which will cause the rotation to be disordered. Therefore, the initial point is defined as the reset center point. Clicking can correct the camera position and restore the center position of the model for easy operation. Digital human viewing is also the third person. In this mode, a virtual digital robot is displayed in the three-dimensional model. The three-dimensional model is browsed from the perspective of the virtual digital robot, and the virtual character can be controlled to move to any target position.

[0091] The first position of the embodiment is also a starting point or a starting position, and the target user starts browsing the three-dimensional model from the first position.

[0092] 207 . Acquire a target location corresponding to the first position in the three-dimensional model, and use the target location as a starting point to play the three-dimensional model according to the viewing mode and the moving path input by the target user.

[0093] The corresponding position in the 3D model is found based on the first position selected by the user, that is, the target location. The moving path input by the user may be a straight line, a curve, or a path obtained based on several key points by clicking on key points. During the movement, the platform updates the view in real time to reflect the current position and perspective. When the playback reaches the end point specified by the user or the user stops it actively, the system ends the playback and may return to the initial state or wait for the next instruction.

[0094] Figure 3 FIG. 1 is a flow chart showing another 3D modeling method based on a panoramic vision laser scanner according to an embodiment of the present invention. Figure 3 As shown, the 3D modeling method based on panoramic vision laser scanner includes:

[0095] 301. Based on the panoramic vision laser scanner, a target scene is fully scanned according to a preset scanning path to collect scene data, wherein the scene data includes three-dimensional coordinate information, RGB color information, and texture information.

[0096] The embodiment uses a panoramic vision laser scanner to comprehensively scan the target scene according to a preset scanning path. The three-dimensional coordinate information describes the position of the object in the three-dimensional space, the RGB color information describes the color of the object, and the texture information describes the surface details of the object.

[0097] 302. Preprocess the scene data and generate point cloud data, and generate ellipsoid distribution data in three-dimensional space based on the point cloud data.

[0098] This step pre-processes the collected scene data, including filtering and denoising, and may further include data calibration and the like.

[0099] Point cloud data is a geometry composed of many three-dimensional coordinate points, which is used to represent objects and surfaces in the target scene. In order to describe and classify the objects or spaces in the scene in more detail, ellipsoid distribution data is further generated based on the point cloud data. Specifically, the pre-stored ellipsoid parameters are loaded to perform coordinate transformation on the point cloud data to generate ellipsoid distribution data in three-dimensional space; or, a number of control points are selected from the point cloud data, and the parameters of the ellipsoid are calculated on the control end to obtain the ellipsoid parameters, and the point cloud data is transformed according to the ellipsoid parameters to generate ellipsoid distribution data in three-dimensional space.

[0100] 303. Establish a three-dimensional model of the target scene based on the ellipsoid distribution data.

[0101] The embodiment constructs a three-dimensional geometric model of the target scene based on the ellipsoid distribution data, maps the texture information to the surface of the three-dimensional geometric model according to the texture mapping algorithm to form a three-dimensional model. The three-dimensional model of the target scene is established using the ellipsoid distribution data to accurately reproduce the target scene and help subsequent analysis, measurement and visualization.

[0102] 304. Receive a space measurement instruction input by a target user, and obtain a measurement method, a measurement start point, and a measurement end point carried in the space measurement instruction.

[0103] The system receives a spatial measurement instruction from a target user, which may include the type of measurement the target user wants to perform, including area measurement and distance measurement.

[0104] 305. Calculate the measured distance or measured area according to the measurement method, measurement starting point and measurement end point.

[0105] For distance and area measurement, geometric calculations of points, lines and surfaces are designed. In operation, the target user can select the corresponding measurement type by clicking the corresponding menu option, such as selecting the measurement distance, and then select any desired measurement starting point in the 3D model, and then select the measurement end point, and the system automatically calculates the measurement distance between the measurement starting point and the measurement end point.

[0106] Embodiment 2

[0107] See also Figure 4 , Figure 4 Schematic diagram of the structure of a 3D modeling device based on a panoramic vision laser scanner disclosed in an embodiment of the present invention. Figure 4 As shown, the three-dimensional modeling device based on the panoramic vision laser scanner may include: a data acquisition module 401, a data processing module 402 and a model creation module 403, wherein the data acquisition module 401 is used to comprehensively scan the target scene according to a preset scanning path based on the panoramic vision laser scanner to collect scene data, and the scene data includes three-dimensional coordinate information, RGB color information, and texture information; the data processing module 402 is used to pre-process the scene data and generate point cloud data, and generate ellipsoid distribution data in three-dimensional space based on the point cloud data; the model creation module 403 is used to establish a three-dimensional model of the target scene based on the ellipsoid distribution data.

[0108] Specifically, in the data processing module 402, the scene data is preprocessed and point cloud data is generated, including: filtering the scene data to remove noise points in the scene data after filtering; obtaining three-dimensional coordinate information of the scene data, and splicing and matching the three-dimensional coordinate information to form point cloud data.

[0109] Generating ellipsoid distribution data in three-dimensional space based on the point cloud data includes: loading pre-stored ellipsoid parameters to perform coordinate transformation on the point cloud data to generate ellipsoid distribution data in three-dimensional space; or, selecting a number of control points from the point cloud data, performing parameter calculation on the control end to obtain ellipsoid parameters, and performing coordinate transformation on the point cloud data according to the ellipsoid parameters to generate ellipsoid distribution data in three-dimensional space.

[0110] In the model creation module 403, specifically, a three-dimensional geometric model of the target scene is constructed based on the ellipsoid distribution data; and texture information is mapped to the surface of the three-dimensional geometric model according to a texture mapping algorithm to form a three-dimensional model.

[0111] The embodiment also includes a login verification module, which is used to respond to the target user's account login instruction, obtain the target user's account information, and perform account verification on the account information; when the account verification is successful, log in to the modeling space corresponding to the target user.

[0112] The embodiment also includes a model viewing module, which is used to receive a spatial viewing instruction input by a target user, and obtain a viewing mode and a first position of the spatial viewing instruction, wherein the viewing mode includes first-person viewing, digital human viewing, and pivot viewing; a model playing module: which is used to obtain a corresponding target location in the three-dimensional model according to the first position, and to play the three-dimensional model with the target location as the starting point according to the viewing mode and the moving path input by the target user.

[0113] The embodiment also includes a model measurement module, which is used to receive a space measurement instruction input by a target user, obtain the measurement method, measurement starting point and measurement end point carried by the space measurement instruction; and calculate the measurement distance or measurement area according to the measurement method, measurement starting point and measurement end point.

[0114] The embodiment solves the deficiencies of traditional methods in visual effects, accuracy and automation through the technology of automatically generating three-dimensional scenes, and also provides a new solution for rapid modeling of large-scale scenes at a lower cost and higher efficiency. Not only does it achieve centimeter-level accuracy standards, but it also realizes measurable and precise annotation functions. Users can freely shuttle through every corner of the model in the virtual space and experience an immersive experience. At the same time, these high-precision point cloud data can also be widely used in multiple fields such as topographic surveying and mapping, geological surveys, and forestry surveys.

[0115] Embodiment 3

[0116] See also Figure 5 , Figure 5Schematic diagram of the structure of an electronic device disclosed in an embodiment of the present invention. The electronic device may be a computer, a server, etc. Of course, in certain circumstances, it may also be a smart device such as a mobile phone, a tablet computer, a monitoring terminal, and an image acquisition device with processing functions. Figure 5 As shown, the electronic device may include:

[0117] A memory 501 storing executable program codes;

[0118] a processor 502 coupled to the memory 501;

[0119] The processor 502 calls the executable program code stored in the memory 501 to execute part or all of the steps in the three-dimensional modeling method based on the panoramic vision laser scanner in the first embodiment.

[0120] An embodiment of the present invention discloses a computer-readable storage medium storing a computer program, wherein the computer program enables a computer to execute part or all of the steps in the three-dimensional modeling method based on a panoramic vision laser scanner in Embodiment 1.

[0121] An embodiment of the present invention further discloses a computer program product, wherein when the computer program product runs on a computer, the computer executes part or all of the steps in the three-dimensional modeling method based on the panoramic vision laser scanner in Embodiment 1.

[0122] An embodiment of the present invention also discloses an application publishing platform, wherein the application publishing platform is used to publish a computer program product, wherein when the computer program product runs on a computer, the computer executes part or all of the steps in the three-dimensional modeling method based on a panoramic vision laser scanner in Example 1.

[0123] In various embodiments of the present invention, it should be understood that the size of the serial numbers of the processes does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0124] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, i.e., they may be located in one place or distributed over multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0125] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0126] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-accessible memory. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product, which is stored in a memory and includes several requests for a computer device (which can be a personal computer, a server or a network device, etc., specifically a processor in a computer device) to perform some or all of the steps of the method described in each embodiment of the present invention.

[0127] In the embodiments provided by the present invention, it should be understood that "B corresponding to A" means that B is associated with A, and B can be determined according to A. However, it should also be understood that determining B according to A does not mean determining B only according to A, and B can also be determined according to A and / or other information.

[0128] A person of ordinary skill in the art can understand that some or all of the steps in the various methods of the embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable rewritable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0129] The three-dimensional modeling method, device, electronic device and storage medium based on the panoramic vision laser scanner disclosed in the embodiments of the present invention are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for general technical personnel in this field, according to the ideas of the present invention, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A three-dimensional modeling method based on panoramic vision laser scanner, characterized in that: include: Based on the panoramic vision laser scanner, the target scene is fully scanned according to the preset scanning path to collect scene data, and the scene data includes three-dimensional coordinate information, RGB color information, and texture information; Preprocessing the scene data to generate point cloud data, and generating ellipsoid distribution data in three-dimensional space based on the point cloud data; A three-dimensional model of the target scene is established based on the ellipsoidal distribution data.

2. The three-dimensional modeling method according to claim 1, characterized in that: The preprocessing of the scene data and generating point cloud data includes: Performing filtering on the scene data to remove noise points in the scene data after filtering; The three-dimensional coordinate information of the scene data is obtained, and the three-dimensional coordinate information is spliced ​​and matched to form point cloud data.

3. The three-dimensional modeling method according to claim 1, characterized in that: The step of generating ellipsoid distribution data in three-dimensional space based on the point cloud data comprises: Loading pre-stored ellipsoid parameters to perform coordinate transformation on the point cloud data to generate ellipsoid distribution data in three-dimensional space; Alternatively, a number of control points are selected from the point cloud data, parameters of the control end are calculated to obtain ellipsoid parameters, and coordinate transformation is performed on the point cloud data according to the ellipsoid parameters to generate ellipsoid distribution data in three-dimensional space.

4. The three-dimensional modeling method according to claim 1, characterized in that: The three-dimensional model of the target scene is established based on the ellipsoid distribution data, comprising: Construct a three-dimensional geometric model of the target scene based on the ellipsoid distribution data; The texture information is mapped to the surface of the three-dimensional geometric model according to a texture mapping algorithm to form a three-dimensional model.

5. The three-dimensional modeling method according to claim 1, characterized in that: Before performing preprocessing on the scene data, the method further includes: In response to an account login instruction from a target user, obtaining the target user's account information and performing account verification on the account information; When the account verification is successful, log in to the modeling space corresponding to the target user.

6. The three-dimensional modeling method according to claim 5, characterized in that: Also includes: receiving a spatial viewing instruction input by a target user, and acquiring a viewing mode and a first position of the spatial viewing instruction, wherein the viewing modes include first-person viewing, digital human viewing, and pivot viewing; A target location corresponding to the three-dimensional model is acquired according to the first position, and the three-dimensional model is played with the target location as a starting point according to the viewing mode and the moving path input by the target user.

7. The three-dimensional modeling method according to claim 5, characterized in that: Also includes: Receive a spatial measurement instruction input by a target user, and obtain a measurement method, a measurement start point, and a measurement end point carried in the spatial measurement instruction; Calculate the measured distance or measured area based on the measurement method, measurement start point and measurement end point.

8. A three-dimensional modeling device based on a panoramic vision laser scanner, characterized in that: include: Data acquisition module: used to comprehensively scan the target scene according to a preset scanning path based on a panoramic vision laser scanner to collect scene data, wherein the scene data includes three-dimensional coordinate information, RGB color information, and texture information; Data processing module: used for preprocessing the scene data and generating point cloud data, and generating ellipsoid distribution data in three-dimensional space based on the point cloud data; Model creation module: used to establish a three-dimensional model of the target scene based on the ellipsoid distribution data.

9. An electronic device, characterized in that: include: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the three-dimensional modeling method based on the panoramic vision laser scanner as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein the computer program enables a computer to execute the three-dimensional modeling method based on a panoramic vision laser scanner as described in any one of claims 1 to 7.

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