CN118212389A - Rapid visualization method and system for tunnel huge-amount point cloud data - Google Patents
Rapid visualization method and system for tunnel huge-amount point cloud data Download PDFInfo
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Abstract
The invention provides a method and a system for quickly visualizing huge amount of point cloud data of a tunnel, wherein the method for visualizing comprises the following steps: when a visualization request of a visualization terminal is received, determining a model diagram according to the visualization request and outputting the model diagram to the visualization terminal; receiving first operation data of a model diagram sent by a visual terminal; and constructing a visual picture according to the first operation data and outputting the visual picture to the visual terminal. The method and the system for quickly visualizing the tunnel huge-amount point cloud data realize quick visualization and display details according to the user requirements.
Description
Technical Field
The invention relates to the technical field of image data processing, in particular to a method and a system for quickly visualizing tunnel huge amount point cloud data.
Background
The three-dimensional laser scanning technology is characterized in that by utilizing the principle of laser ranging, the three-dimensional model of a measured object and various drawing data such as lines, planes, bodies and the like can be quickly reconstructed by recording the information such as the three-dimensional coordinates, the reflectivity, the textures and the like of a large number of dense points on the surface of the measured object.
Three-dimensional scanning techniques are widely used in many fields, especially in tunnel measurement; and scanning the tunnel by using a three-dimensional laser scanning technology to obtain huge amount of point cloud data, and analyzing the huge amount of point cloud data to realize deformation analysis, completion measurement and the like of the tunnel. For example: the prior patent CN201811529199.1 is a tunnel deformation monitoring analysis method based on a grid projection point cloud processing technology, the prior patent CN202210952011.4 is a subway tunnel damage detection method based on computer vision, and the like, which are all applications of the three-dimensional laser scanning technology in the aspect of tunnel monitoring analysis. However, some situations exist (for example, manual verification and confirmation are performed on the result after automatic analysis) in which a large amount of point cloud data cannot be directly presented to an analyst, and then visualization processing is required on the large amount of point cloud data, and for the visualization processing, a method for denoising tunnel point cloud and generating a visualization model in the prior patent cn 20201394518. X discloses generation of a visualization model according to the point cloud data, but because the visualization model is integrally generated, the display requirement of detail of manual verification and confirmation cannot be met.
Disclosure of Invention
The invention aims to provide a method and a system for quickly visualizing huge amount of tunnel point cloud data, which realize quick visualization and detailed display according to user requirements.
The embodiment of the invention provides a rapid visualization method for tunnel huge-amount point cloud data, which comprises the following steps:
When a visualization request of a visualization terminal is received, determining a model diagram according to the visualization request and outputting the model diagram to the visualization terminal;
Receiving first operation data of a model diagram sent by a visual terminal;
and constructing a visual picture according to the first operation data and outputting the visual picture to the visual terminal.
Preferably, determining the model graph according to the visualization request includes:
Analyzing the visual request, and determining a target code and a region code;
extracting corresponding point cloud data from a point cloud data storage library according to the target code and the region code;
constructing an initial model diagram according to the point cloud data;
And adding observation points in the initial model diagram according to a preset observation point adding rule.
Preferably, the first operation data includes: and selecting the observation point in the model diagram, and selecting parameters on a preset parameter selection interface corresponding to the selected observation point.
Preferably, constructing the visual according to the first operation data includes:
analyzing the first operation data, and determining observation points and corresponding parameters;
constructing a mapping window in the model diagram according to the observation point positions and the corresponding parameters;
determining a corresponding first area on the model diagram according to the observation point position and the mapping window;
And mapping the corresponding first area on the model diagram to a mapping window to construct a visual picture.
Preferably, the method for quickly visualizing the huge amount of point cloud data of the tunnel further comprises the following steps:
Receiving second operation data of the visual terminal for the visual picture;
According to the second operation data, the visual picture is adjusted;
wherein, according to the second operation data, adjust the visual picture, include:
analyzing the second operation data, and determining an up-down dragging parameter and a left-right dragging parameter;
constructing a correction window at a position corresponding to the mapping window according to the up-down dragging parameter and the left-right dragging parameter;
determining a corresponding second area on the model diagram according to the observation point position and the correction window;
And mapping a second area corresponding to the model image to a correction window, acquiring a correction image and adjusting the visual picture based on the correction image.
The invention also provides a rapid visualization system for the huge amount of point cloud data of the tunnel, which comprises the following steps:
The determining module is used for determining a model diagram according to the visualization request and outputting the model diagram to the visualization terminal when the visualization request of the visualization terminal is received;
The receiving module is used for receiving first operation data of the model diagram sent by the visual terminal;
And the construction output module is used for constructing a visual picture according to the first operation data and outputting the visual picture to the visual terminal.
Preferably, the determining module determines a model diagram according to the visualization request, and performs the following operations:
Analyzing the visual request, and determining a target code and a region code;
extracting corresponding point cloud data from a point cloud data storage library according to the target code and the region code;
constructing an initial model diagram according to the point cloud data;
And adding observation points in the initial model diagram according to a preset observation point adding rule.
Preferably, the first operation data includes: and selecting the observation point in the model diagram, and selecting parameters on a preset parameter selection interface corresponding to the selected observation point.
Preferably, the construction output module constructs a visual picture according to the first operation data, and performs the following operations:
analyzing the first operation data, and determining observation points and corresponding parameters;
constructing a mapping window in the model diagram according to the observation point positions and the corresponding parameters;
determining a corresponding first area on the model diagram according to the observation point position and the mapping window;
And mapping the corresponding first area on the model diagram to a mapping window to construct a visual picture.
Preferably, the tunnel huge amount point cloud data rapid visualization system further comprises: an adjustment module;
the adjustment module performs the following operations:
Receiving second operation data of the visual terminal for the visual picture;
According to the second operation data, the visual picture is adjusted;
wherein, according to the second operation data, adjust the visual picture, include:
analyzing the second operation data, and determining an up-down dragging parameter and a left-right dragging parameter;
constructing a correction window at a position corresponding to the mapping window according to the up-down dragging parameter and the left-right dragging parameter;
determining a corresponding second area on the model diagram according to the observation point position and the correction window;
And mapping a second area corresponding to the model image to a correction window, acquiring a correction image and adjusting the visual picture based on the correction image.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a schematic diagram of a method for fast visualizing huge amount of point cloud data in a tunnel according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a grid division in an embodiment of the present invention;
Fig. 3 is a schematic diagram of a fast visualization system for tunnel huge amount point cloud data according to an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
The embodiment of the invention provides a rapid visualization method for tunnel huge-amount point cloud data, which is shown in fig. 1 and comprises the following steps:
Step S1: when a visualization request of a visualization terminal is received, determining a model diagram according to the visualization request and outputting the model diagram to the visualization terminal;
step S2: receiving first operation data of a model diagram sent by a visual terminal;
step S3: and constructing a visual picture according to the first operation data and outputting the visual picture to the visual terminal.
Wherein determining the model graph according to the visualization request comprises:
Analyzing the visual request, and determining a target code and a region code;
extracting corresponding point cloud data from a point cloud data storage library according to the target code and the region code; storing point cloud data in a point cloud data storage library of a server in a corresponding association manner with the target code and the region code;
constructing an initial model diagram according to the point cloud data;
And adding observation points in the initial model diagram according to a preset observation point adding rule.
Wherein the first operation data includes: and selecting the observation point in the model diagram, and selecting parameters on a preset parameter selection interface corresponding to the selected observation point. The selection operation of the observation point in the model diagram is a click operation of a user on the observation point on an initial model diagram of the visual terminal, after the click operation, the visual terminal displays a preset parameter selection interface, and selectable parameters on the parameter selection interface comprise: line of sight angle parameters, length and width of visual images, line of sight and the like; wherein the line of sight angle parameter represents a line of sight direction from the viewpoint; the sight distance is the distance between the mapping window and the observation point; the length and width of the visual image are the length and width of the mapping window;
wherein, according to the first operation data, construct the visual picture, include:
analyzing the first operation data, and determining observation points and corresponding parameters;
constructing a mapping window in the model diagram according to the observation point positions and the corresponding parameters;
Determining a corresponding first area on the model diagram according to the observation point position and the mapping window; the region formed by the intersection points of the extension line of the connecting line between the observation point and the sampling points on each boundary on the mapping window and the model diagram is a first region;
And mapping the corresponding first area on the model diagram to a mapping window to construct a visual picture. And connecting lines between the continuous points and the observation points in the first area and the mapping windows are used as mapping points, and an image formed by all the mapping points is a visual image.
The working principle and the beneficial effects of the technical scheme are as follows:
The rapid visualization method for the huge amount of tunnel point cloud data is applied to a server, and the point cloud data measured in each measurement time period of each tunnel is stored in the server; the visual terminal is in communication connection with the server; the user sends a visual request to the server through the visual terminal, and when the server receives the visual request of the visual terminal, a model diagram is determined according to the visual request and is output to the visual terminal; then, the server receives first operation data of the model diagram sent by the visual terminal, constructs a visual picture according to the first operation data and outputs the visual picture to the visual terminal.
The specific operation of sending the visualization request to the server after the user operates on the visualization terminal comprises the following steps: the user clicks a visual application virtual button of a display page on the visual terminal, the visual terminal sends an application to the server, and the server returns an overall layout diagram of the tunnel, wherein the overall layout diagram can comprise distribution diagrams of all tunnels in each preset area; the user clicks a tunnel graph on the distribution graph, determines a target code of the tunnel and a region code on the tunnel region through the tunnel clicked by the user and the region on the tunnel, and then generates a visual request based on the target code and the region code; the target codes are identification codes among the tunnels, namely, the target codes are associated with the tunnels in a one-to-one correspondence manner; dividing tunnels from a starting point to an ending point in advance in an equidistant mode, and associating each section with a region code; thus, a specific area of the tunnel can be positioned through the target code and the area code.
After extracting the point cloud data from the point cloud data storage library, constructing an initial model diagram according to the point cloud data; dividing the extracted point cloud data through a grid index, constructing a multi-resolution octree, web rendering and the like, and forming a visual initial model diagram; and then adding observation points in the initial model diagram according to a preset observation point adding rule, so that a user can conveniently select a specific observation position.
Wherein the data extracted from the point cloud data repository is the most recently measured data. The grid division is shown in fig. 2, in the diagram, the point clouds AABB of the area a are close to tightAABB, the point number is enough, and the construction of the multi-resolution octree is directly carried out. The cloud point number of the b area point is enough, but the AABB is larger from tightA-ABB, and the index is established by tightAABB. The region c is obtained by combining two regions, the number of grid point clouds on the right side of the region c is small and tightAABB is far smaller than AABB of the grid, the region c is combined with the left grid according to an algorithm, the number of points after combination and the AABB are calculated, and if the combined grid does not meet the condition of constructing an index in the next step, the process is repeated. The grid where no data is present is directly discarded. And sequentially storing the grid nodes, and respectively establishing multi-resolution octree indexes for point clouds in the grid. Assuming that the original point number is N and the average value of the grid point number is M, the multi-resolution octree construction efficiency is approximately improved。
In addition, the point cloud data can be processed in advance to obtain an initial model, and then the initial model is stored in a model library and is associated with the point cloud data in the point cloud data storage library, so that the point cloud data can be directly called according to the identification code corresponding to the point cloud data. When the initial model is built in advance, the virtual space can be built, and then the point cloud data is mapped to the virtual space according to the coordinates of the point cloud data to build the initial model.
In one embodiment, a method for quickly visualizing tunnel huge amount of point cloud data includes:
When a visualization request of a visualization terminal is received, determining a model diagram according to the visualization request and outputting the model diagram to the visualization terminal;
Receiving first operation data of a model diagram sent by a visual terminal;
and constructing a visual picture according to the first operation data and outputting the visual picture to the visual terminal.
Wherein determining the model graph according to the visualization request comprises:
Analyzing the visual request, and determining a target code and a region code;
extracting corresponding point cloud data from a point cloud data storage library according to the target code and the region code;
When only one group of data is extracted, an initial model diagram is constructed according to the point cloud data; adding observation points in the initial model diagram according to a preset observation point adding rule;
When two or more groups of data are extracted, constructing a time range selection table according to the time range corresponding to each group of data, and outputting the time range selection table to a visual terminal;
Constructing an initial model diagram by using point cloud data corresponding to a time range fed back by a visual terminal; adding observation points in the initial model diagram according to a preset observation point adding rule;
the working principle and the beneficial effects of the technical scheme are as follows:
The tunnel measurement is generally carried out at different times, so that a plurality of groups of point cloud data of each area of each tunnel in the point cloud database can exist, and the specific intention of a user is determined by a time range selection table query mode, so that the accuracy of the target determination can be realized through visualization.
In one embodiment, adding the viewpoint in the initial model diagram according to a preset viewpoint adding rule includes:
Extracting a corresponding visual image from a pre-stored image library according to the target code and the region code;
determining point location parameters corresponding to the visual image;
based on the point position parameters, adding observation points in the initial model;
The visual images stored in the image library are visual images corresponding to the historical visual requests of the visual terminal. The storage rule is to store the target code, the region code, the observation point position, the distance of the mapping window and the length and width of the mapping window in a corresponding association way with the visualized image. The point location parameters include: coordinates of the observation point.
When no corresponding visual image is extracted from the image library, adding the initial model image through a preset observation point position adding table; the observation point position adding table can define the center points of the initial model diagram, the center points of each unit after the initial model is divided by a preset grid, and the like; each cell after grid segmentation may be a cube. The center point of the initial model diagram is the point on the initial model diagram where the sum of distances from each other point on the initial model diagram is the shortest. The dimensions of the cubes may be configured by the staff to any one of 10cm to 3 m.
Further, before adding the observation point, synchronously establishing a visual image corresponding to a preset corresponding parameter corresponding to the observation point, and adding the observation point after the visual image is established; after the observation point appears on the initial model diagram, the user can quickly output a visual image by clicking. And adding the observation point into the initial model and displaying the observation point at a visual terminal after the construction of the visual image corresponding to the observation point is completed.
In order to realize the preferential addition of the observation point of the user's intent, in one embodiment, the identity information of the user of the visual terminal is obtained;
acquiring a history operation record of a user based on the identity information;
According to the historical operation records, constructing a historical observation point position sequence table corresponding to each historical operation record;
Determining the priority value of each point in the observation point position adding table according to the historical observation point position sequence table;
The addition of observation points is performed based on the order of the priority values from large to small.
The method for determining the priority value of each point in the observation point position adding table according to the historical observation point position sequence table comprises the following steps:
Assigning values to each observation point in the historical observation point sequence table according to a preset assignment rule; the assignment rule is that the first to the last in the same historical observation point position sequence table are sequentially reduced, and assignment of the historical observation points of the same bit in the historical observation point position sequence table, which is close to the current moment, is higher;
The priority value of each point in the observation point position adding table is the sum value of the assignment of the same or similar point positions in the history observation point position sequence table.
In order to meet the visual angle adjustment requirement of a user after visual image output, the tunnel huge amount point cloud data rapid visualization method comprises the following steps:
When a visualization request of a visualization terminal is received, determining a model diagram according to the visualization request and outputting the model diagram to the visualization terminal;
Receiving first operation data of a model diagram sent by a visual terminal;
constructing a visual picture according to the first operation data and outputting the visual picture to a visual terminal;
Receiving second operation data of the visual terminal for the visual picture;
According to the second operation data, the visual picture is adjusted;
wherein, according to the second operation data, adjust the visual picture, include:
Analyzing the second operation data, and determining an up-down dragging parameter and a left-right dragging parameter; the parameters of the up-and-down dragging are as follows
Constructing a correction window at a position corresponding to the mapping window according to the up-down dragging parameter and the left-right dragging parameter;
determining a corresponding second area on the model diagram according to the observation point position and the correction window;
And mapping a second area corresponding to the model image to a correction window, acquiring a correction image and adjusting the visual picture based on the correction image.
In order to more quickly cope with the possible adjustment requirement of a user after the visual image is output, when a mapping window is constructed, the actual constructed size is enlarged on a parameter reference selected by the user, a preset threshold corresponding to the parameter can be added on the basis of the parameter selected by the user, so that the mapping window is constructed, and when the visual image is output, middle image output is intercepted through an intercepting frame corresponding to the parameter selected by the user; when adjusted, the image output may be directly truncated from the previous visual image moving the image-truncated frame.
In addition, the threshold value corresponding to each parameter can also be obtained by analyzing the historical second operation data of the user, and the specific calculation formula is as follows:
；
Wherein, Is a threshold value; /(I)Parameters determined for the second operational data of the ith history; /(I)A weight coefficient determined according to time corresponding to a parameter determined for the second operation data of the ith history; n represents the total number of second operation data of the history; when a plurality of values of the same parameter exist in the same operation data, taking the maximum value as the reference; the weight coefficient is correlated with the past time of the second operation data of the history, and the longer the time, the smaller the weight coefficient.
In order to ensure the timeliness of output, a limit is set for the threshold value, a maximum value is set, and when the calculated threshold value exceeds the maximum value, the maximum value is taken as a reference to adjust the mapping window.
In order to improve the intellectualization, the visualization processing step is optimized on the basis of analyzing the abnormal data through the data in advance, so that the user can verify the abnormal data manually, and in one embodiment, the method for quickly visualizing the huge amount of point cloud data of the tunnel further comprises the following steps:
Acquiring an abnormal point position corresponding to the analyzed abnormal data;
Mapping the abnormal point positions into an initial model, and determining a target area from the initial model;
determining an observation point position corresponding to a target area and a mapping window corresponding to the observation point position according to a preset area and point position relation library;
Labeling observation points determined by the abnormal data on the model diagram; the user can quickly determine the observation point position corresponding to the abnormal data by the marking mode different from other observation point positions, so that the user can conveniently click; for example: the common observation point positions can be marked by adopting green as a main tone, and the observation point positions corresponding to the abnormal data are marked by adopting red tone;
The abnormal point positions can be the point positions corresponding to the abnormal data automatically analyzed by the system or the point positions input after the analysis by the staff.
When a target area is determined from the initial model, firstly calculating the distance between each abnormal point, and when the maximum distance is smaller than or equal to a preset distance threshold (any one value from 10cm to 3 m), calculating the point on the initial model with the shortest total distance to each abnormal point as a reference point; determining a target area by taking a reference point as a center; when the maximum distance is greater than a preset distance threshold, eliminating the point position with the distance greater than the distance threshold, taking the point on the initial model with the shortest total distance to the rest point positions as a reference point, and taking the reference point as a center to determine a target area; the boundary of the target area falls on a point farthest from the reference point in each direction of the reference point;
On the basis, the mapping window is determined by sliding a preset window template in a target area, and selecting the position with the largest included point position as the position of the mapping window; inquiring a region and point relation library by using the region range of the mapping window, and determining an observation point; mapping windows in the library and associating observation points one by one;
In addition, when the mapping window does not include all the abnormal points, and the user definitely has the abnormal points in the area which cannot be seen outside the visual image, a marking area can be further arranged around the visual image corresponding to the abnormal data, and film coating processing is performed on the marking area so as to distinguish the area corresponding to the window; and the region outside the mapping window is displayed in the marking region after being subjected to the thumbnail processing, wherein the proportion of the thumbnail processing is in direct proportion to the distance from the abnormal point position to the boundary of the mapping window, namely, the larger the distance is, the larger the thumbnail proportion is.
The invention also provides a rapid visualization system for the huge amount of point cloud data of the tunnel, as shown in fig. 3, comprising:
the determining module 1 is used for determining a model diagram according to the visualization request and outputting the model diagram to the visualization terminal when the visualization request of the visualization terminal is received;
A receiving module 2, configured to receive first operation data of a model diagram sent by a visual terminal;
And the construction output module 3 is used for constructing a visual picture according to the first operation data and outputting the visual picture to the visual terminal.
The determining module determines a model diagram according to the visualization request, and performs the following operations:
Analyzing the visual request, and determining a target code and a region code;
extracting corresponding point cloud data from a point cloud data storage library according to the target code and the region code;
constructing an initial model diagram according to the point cloud data;
And adding observation points in the initial model diagram according to a preset observation point adding rule.
Wherein the first operation data includes: and selecting the observation point in the model diagram, and selecting parameters on a preset parameter selection interface corresponding to the selected observation point.
The construction output module constructs a visual picture according to the first operation data, and executes the following operations:
analyzing the first operation data, and determining observation points and corresponding parameters;
constructing a mapping window in the model diagram according to the observation point positions and the corresponding parameters;
determining a corresponding first area on the model diagram according to the observation point position and the mapping window;
And mapping the corresponding first area on the model diagram to a mapping window to construct a visual picture.
In one embodiment, a tunnel macro point cloud data rapid visualization system, comprising: the device comprises a determining module, a receiving module, a construction output module and an adjusting module;
the adjustment module performs the following operations:
Receiving second operation data of the visual terminal for the visual picture;
According to the second operation data, the visual picture is adjusted;
wherein, according to the second operation data, adjust the visual picture, include:
analyzing the second operation data, and determining an up-down dragging parameter and a left-right dragging parameter;
constructing a correction window at a position corresponding to the mapping window according to the up-down dragging parameter and the left-right dragging parameter;
determining a corresponding second area on the model diagram according to the observation point position and the correction window;
And mapping a second area corresponding to the model image to a correction window, acquiring a correction image and adjusting the visual picture based on the correction image.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (6)
1. A rapid visualization method for tunnel huge-amount point cloud data is characterized by comprising the following steps:
when a visualization request of a visualization terminal is received, determining a model diagram according to the visualization request and outputting the model diagram to the visualization terminal;
Receiving first operation data of a model diagram sent by the visual terminal;
Constructing a visual picture according to the first operation data and outputting the visual picture to the visual terminal;
wherein, according to the first operation data, constructing a visual picture includes:
analyzing the first operation data, and determining observation points and corresponding parameters;
constructing a mapping window in the model diagram according to the observation point positions and the corresponding parameters;
determining a corresponding first area on the model diagram according to the observation point position and the mapping window;
Mapping the corresponding first area on the model diagram to the mapping window to construct a visual picture;
The method further comprises the steps of:
receiving second operation data of the visual terminal for the visual picture;
according to the second operation data, the visual picture is adjusted;
wherein, according to the second operation data, adjust the visual picture, include:
analyzing the second operation data, and determining an up-down dragging parameter and a left-right dragging parameter;
constructing a correction window at a position corresponding to the mapping window according to the up-down dragging parameter and the left-right dragging parameter;
determining a corresponding second area on the model diagram according to the observation point position and the correction window;
And mapping a second area corresponding to the model image to the correction window, acquiring a correction image and adjusting the visual picture based on the correction image.
2. The method for quickly visualizing tunnel huge-amount point cloud data according to claim 1, wherein the determining step of the model map comprises:
Determining a target code and a region code from the visualization request;
extracting corresponding point cloud data from a point cloud data storage library by taking the target code and the region code as identifiers;
Analyzing and constructing an initial model diagram on the basis of the point cloud data;
And adding observation points in the initial model diagram according to a preset observation point adding rule.
3. The method for quickly visualizing tunnel macropoint cloud data of claim 2, wherein the first operational data comprises: selecting operation of observation points in the model diagram and parameter selecting operation on a parameter selection interface popped up after the selected observation points.
4. The utility model provides a tunnel huge amount point cloud data quick visualization system which characterized in that includes:
the determining module is used for determining a model diagram and outputting the model diagram to the visual terminal according to the visual request when the visual request of the visual terminal is received;
the receiving module is used for receiving first operation data of the model diagram sent by the visual terminal;
the construction output module is used for constructing a visual picture according to the first operation data and outputting the visual picture to the visual terminal;
An adjustment module;
Wherein, the adjustment module performs the following operations:
receiving second operation data of the visual terminal for the visual picture;
according to the second operation data, the visual picture is adjusted;
wherein, according to the second operation data, adjust the visual picture, include:
analyzing the second operation data, and determining an up-down dragging parameter and a left-right dragging parameter;
constructing a correction window at a position corresponding to the mapping window according to the up-down dragging parameter and the left-right dragging parameter;
determining a corresponding second area on the model diagram according to the observation point position and the correction window;
mapping a second area corresponding to the model image to the correction window, acquiring a correction image and adjusting the visual picture based on the correction image;
The construction output module constructs a visual picture according to the first operation data, and executes the following operations:
analyzing the first operation data, and determining observation points and corresponding parameters;
constructing a mapping window in the model diagram according to the observation point positions and the corresponding parameters;
determining a corresponding first area on the model diagram according to the observation point position and the mapping window;
and mapping the corresponding first area on the model diagram to the mapping window to construct a visual picture.
5. The rapid visualization system of tunnel mass point cloud data of claim 4, wherein the determination module determines a model map based on the visualization request, performing the operations of:
Analyzing the visual request, and determining a target code and a region code;
Extracting corresponding point cloud data from a point cloud data storage library according to the target code and the region code;
Constructing an initial model diagram according to the point cloud data;
And adding observation points in the initial model diagram according to a preset observation point adding rule.
6. The rapid visualization system of tunnel macro point cloud data of claim 4, wherein the first operational data comprises: and selecting the observation point in the model diagram, and selecting parameters on a preset parameter selection interface corresponding to the selected observation point.
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