CN116704138B - Method and device for establishing oblique photography three-dimensional model - Google Patents
Method and device for establishing oblique photography three-dimensional model Download PDFInfo
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Abstract
The invention discloses a method and a device for establishing an oblique photography three-dimensional model, wherein the method comprises the following steps: acquiring oblique aerial image data in a target area; performing aerial triangulation in the target area through at least one target control point preset in the target area to obtain a target external azimuth element corresponding to the inclined aerial image data; constructing a digital model of the target area according to the inclined aerial image data and the target external azimuth element; and according to the predetermined data processing parameters, performing data processing operation matched with the data processing parameters on the inclined aerial image data and the digital model to obtain a target three-dimensional model corresponding to the target area. Therefore, the method and the device can be used for intelligently processing the acquired aerial image data to generate the target three-dimensional model corresponding to the target area, thereby being beneficial to improving the intelligence of building the three-dimensional model and improving the efficiency and the accuracy of building the three-dimensional model.
Description
Technical Field
The invention relates to the technical field of three-dimensional model construction processing, in particular to a method and a device for constructing an oblique photography three-dimensional model.
Background
In real life, the oblique photography technology is a high-new technology developed in recent years in the international mapping field, and overturns the limitation that the original orthographic image can only be photographed from a vertical angle, and by carrying a plurality of sensors on the same flight platform and collecting images from five different angles such as a vertical angle, a four-inclined angle and the like, a user is introduced into the real visual world conforming to human vision, so that the oblique photography has wide application scenes in application scenes such as engineering measurement and the like as a novel technology.
However, in the current oblique photography technology, image data is generally collected by a data collection device, and the collected image data is manually processed according to a preset data processing flow to obtain a three-dimensional model matched with the image data. This not only makes the efficiency of the obtained three-dimensional model low, but also the degree of matching between the obtained three-dimensional model and the image data is low, which in turn results in low accuracy of the obtained three-dimensional model. It is important to provide a new method for constructing a three-dimensional model to improve the efficiency and accuracy of obtaining the three-dimensional model.
Disclosure of Invention
The invention aims to solve the technical problem of providing a method and a device for establishing an oblique photography three-dimensional model, which are beneficial to improving the efficiency of generating the three-dimensional model and the accuracy of generating the three-dimensional model.
In order to solve the technical problem, a first aspect of the present invention discloses a method for establishing an oblique photography three-dimensional model, which comprises the following steps:
acquiring oblique aerial image data in a target area;
performing aerial triangulation in the target area through at least one target control point preset in the target area to obtain a target external azimuth element corresponding to the inclined aerial image data;
constructing a digital model of the target area according to the inclined aerial image data and the target external azimuth element;
and according to the predetermined data processing parameters, performing data processing operation matched with the data processing parameters on the inclined aerial image data and the digital model to obtain a target three-dimensional model corresponding to the target region.
The second aspect of the invention discloses a device for establishing an oblique photography three-dimensional model, which comprises:
The acquisition module is used for acquiring inclined aerial image data in the target area;
the measuring module is used for carrying out aerial triangulation in the target area through at least one target control point preset in the target area so as to obtain a target external azimuth element corresponding to the inclined aerial image data;
the construction module is used for constructing a digital model of the target area according to the inclined aerial image data and the target external azimuth element;
and the processing module is used for executing data processing operation matched with the data processing parameters on the inclined aerial image data and the digital model according to the predetermined data processing parameters to obtain a target three-dimensional model corresponding to the target area.
As an optional implementation manner, in the second aspect of the present invention, the obtaining module is further configured to obtain model building requirement information before obtaining oblique aerial image data in the target area;
the apparatus further comprises:
the determining module is used for constructing the demand information according to the model and determining a target area;
the acquisition module is further configured to acquire area information of the target area, where the area information includes one or more of area map information and area control point information;
The first generation module is used for constructing demand information according to the region information and the model to generate a target route;
the acquisition module is further configured to acquire device parameters of a target acquisition device, where the device parameters include one or more of a focal length parameter of the target acquisition device, an acquisition resolution parameter of the target acquisition device, and a device performance parameter of the target acquisition device;
the judging module is used for judging whether the equipment parameters meet preset equipment performance conditions or not;
when the judging module judges that the equipment parameter meets the preset equipment performance condition, the specific mode of acquiring the inclined aerial image data in the target area by the acquiring module comprises the following steps:
according to the target route, controlling the target acquisition equipment to execute data acquisition operation matched with the target route so as to acquire oblique aerial image data in the target area;
the determining module is further configured to determine a target device parameter that does not meet a preset device performance condition when the judging module judges that the device parameter does not meet the preset device performance condition;
and the execution module is used for executing parameter processing operation on the target equipment parameters and re-triggering the judging module to execute the operation of judging whether the equipment parameters meet the preset equipment performance conditions.
As an optional implementation manner, in the second aspect of the present invention, the acquiring module is further configured to acquire real-time image data in the target area acquired by the target acquisition device;
the apparatus further comprises:
the analysis module is used for analyzing the real-time image data to obtain a real-time image analysis result;
the judging module is further used for judging whether target image data which does not meet preset image acquisition conditions exist in all the real-time image data according to the real-time image analysis result;
the acquisition module is further configured to acquire data acquisition parameters corresponding to each piece of target image data when the judgment module judges that the target image data which does not meet the preset image acquisition conditions exists in all pieces of real-time image data, where the data acquisition parameters include acquisition time of the target image data and acquisition area of the target image data;
the determining module is further used for determining target adjustment parameters according to data acquisition parameters corresponding to all the target image data;
the execution module is also used for executing the adjustment operation matched with the target adjustment parameter;
Wherein the target adjustment parameters include one or more of course adjustment operations, acquisition adjustment operations, and calibration adjustment operations.
As an optional implementation manner, in the second aspect of the present invention, the predetermined data processing parameters include a point cloud interpolation processing parameter and a DSM generation processing parameter;
the specific method for obtaining the target three-dimensional model corresponding to the target region by the processing module according to the predetermined data processing parameters and executing the data processing operation matched with the data processing parameters on the inclined aerial image data and the digital model comprises the following steps:
determining original point cloud data from the oblique aerial image data according to the point cloud interpolation processing parameters, performing preset point cloud data processing operation on all the original point cloud data to obtain target point cloud data, performing operation matched with the point cloud data processing parameters on all the target point cloud data according to the preset point cloud data processing parameters to obtain a preliminary data image, and performing data conversion operation on the preliminary data image to obtain a target data image;
generating processing parameters according to the DSM, and determining target modeling parameters from the digital model, wherein the target modeling parameters comprise model drawing surface parameters, model resolution parameters and model camera height parameters;
Generating a preliminary three-dimensional model based on the target modeling parameters and the target data image;
according to the model construction requirement, determining texture requirement parameters and differential requirement parameters matched with the model construction requirement;
generating three-dimensional model processing parameters according to the texture demand parameters and the differential demand parameters, and executing processing operation matched with the three-dimensional model processing parameters on the preliminary three-dimensional model to obtain a target three-dimensional model corresponding to the target region;
wherein the three-dimensional model processing parameters include differential correction processing parameters and texture mapping processing parameters.
In a second aspect of the present invention, the specific manner of performing aerial triangulation in the target area by using at least one target control point preset in the target area to obtain the target external azimuth element corresponding to the oblique aerial image data includes:
for each target control point preset in the target area, judging whether the target control point meets preset point position conditions according to preset point position thumbnails, and when judging that the target control point does not meet the preset point position conditions, carrying out positioning change on the target control point according to the preset point position thumbnails so as to update the point position of the target control point;
Performing aerial triangulation in the target area through all the target control points to obtain a triangulation result, and calculating a triangulation adjustment corresponding to the triangulation result according to a preset adjustment algorithm;
judging whether coarse control points exist in all the target control points or not based on the triangulation adjustment, wherein the triangulation adjustment comprises coarse detection values of each target control point, and the coarse control points are used for representing target control points with coarse detection values being greater than or equal to a preset coarse detection threshold;
when judging that the rough difference control points exist in all the target control points, eliminating all the rough difference control points from the target control points, and updating all the target control points;
and generating a target external azimuth element corresponding to the inclined aerial image data based on all the updated target control points.
As an optional implementation manner, in the second aspect of the present invention, the obtaining module is further configured to obtain application requirement information corresponding to the target three-dimensional model, where the application requirement information includes model reconstruction platform requirement information of the target three-dimensional model and application requirement information of an application platform of the target three-dimensional model;
The judging module is further used for judging whether the target three-dimensional model is matched with the application demand information;
the determining module is further configured to determine at least one parameter to be adjusted in the target three-dimensional model when the judging module judges that the target three-dimensional model is not matched with the application requirement information;
the determining module is further configured to determine, for each parameter to be adjusted, an adjustment operation parameter of the parameter to be adjusted according to the application requirement information;
the execution module is further used for executing parameter adjustment operation matched with the adjustment operation parameter of the parameter to be adjusted on the parameter to be adjusted so as to obtain a target reconstruction model;
the apparatus further comprises:
the detection module is used for detecting the model precision coefficient of the target reconstruction model;
the judging module is further used for judging whether the model precision coefficient meets a preset precision condition; when the model precision coefficient is judged to not meet the preset precision condition, the detection module is triggered to execute the detection of the model precision coefficient of the target reconstruction model again, and the judgment module is triggered to execute the operation of judging whether the model precision coefficient meets the preset precision condition or not;
And the updating module is used for updating the target three-dimensional model according to the target reconstruction model when the judging module judges that the model precision coefficient meets the preset precision condition.
As an alternative embodiment, in the second aspect of the present invention, the apparatus further includes:
the classifying module is used for executing image data classifying operation on the inclined aerial image data for each inclined aerial image data before the constructing module constructs a digital model of the target area according to the inclined aerial image data and the target external azimuth element, so as to obtain the data category of the inclined aerial image data;
the extraction module is used for executing feature extraction operation on all the inclined aviation image data included in each data category so as to obtain image feature data of the data category;
the second generation module is used for generating modeling characteristic data of the data category according to the image characteristic data of the data category;
the construction module constructs the digital model of the target area according to the oblique aerial image data and the target external azimuth element, wherein the specific mode comprises the following steps:
And constructing a digital model of the target area according to the modeling characteristic data of each data category, the inclined aerial image data and the target external azimuth element.
The third aspect of the present invention discloses another apparatus for creating a three-dimensional model of oblique photography, the apparatus comprising:
a memory storing executable program code;
a processor coupled to the memory;
the processor invokes the executable program code stored in the memory to perform the method of creating a oblique photography three-dimensional model as disclosed in the first aspect of the present invention.
A fourth aspect of the present invention discloses a computer storage medium storing computer instructions for performing the method of creating a oblique photography three-dimensional model disclosed in the first aspect of the present invention when the computer instructions are called.
Compared with the prior art, the embodiment of the invention has the following beneficial effects:
in the embodiment of the invention, oblique aerial image data in a target area is acquired; performing aerial triangulation in the target area through at least one target control point preset in the target area to obtain a target external azimuth element corresponding to the inclined aerial image data; constructing a digital model of the target area according to the inclined aerial image data and the target external azimuth element; and according to the predetermined data processing parameters, performing data processing operation matched with the data processing parameters on the inclined aerial image data and the digital model to obtain a target three-dimensional model corresponding to the target area. Therefore, the method and the device can be used for intelligently processing the acquired aerial image data to generate the target three-dimensional model corresponding to the target area, thereby being beneficial to improving the intelligence of building the three-dimensional model and improving the efficiency and the accuracy of building the three-dimensional model.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a method for creating an oblique photography three-dimensional model according to an embodiment of the present invention;
FIG. 2 is a flow chart of another method for creating a oblique photography three-dimensional model according to an embodiment of the present invention;
FIG. 3 is a schematic structural view of an apparatus for creating a three-dimensional model of oblique photography according to an embodiment of the present invention;
FIG. 4 is a schematic structural view of another oblique photography three-dimensional model building device according to the embodiment of the present invention;
fig. 5 is a schematic structural view of a device for creating a three-dimensional model of oblique photography according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The terms first, second and the like in the description and in the claims and in the above-described figures are used for distinguishing between different objects and not necessarily for describing a sequential or chronological order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, apparatus, article, or article that comprises a list of steps or elements is not limited to only those listed but may optionally include other steps or elements not listed or inherent to such process, method, article, or article.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the invention. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
The invention discloses a method and a device for establishing an oblique photography three-dimensional model, which can perform intelligent processing on acquired aerial image data to generate a target three-dimensional model corresponding to a target area, and are beneficial to improving the intelligence of establishing the three-dimensional model and the efficiency and the accuracy of establishing the three-dimensional model. The following will describe in detail.
Example 1
Referring to fig. 1, fig. 1 is a flow chart of a method for creating a three-dimensional model of oblique photography according to an embodiment of the present invention. The method for establishing the oblique photography three-dimensional model described in fig. 1 can be applied to an apparatus for establishing the oblique photography three-dimensional model, and also can be applied to a cloud server or a local server for establishing the oblique photography three-dimensional model, and the embodiment of the invention is not limited. As shown in fig. 1, the method for creating the oblique photography three-dimensional model may include the following operations:
101. and acquiring oblique aerial image data in the target area.
In the embodiment of the present invention, optionally, the acquiring of the oblique aerial image data in the target area may be performed by an image acquisition device; further optionally, the image acquisition device is a movable and controllable acquisition device; further, the image acquisition equipment is an unmanned aerial vehicle with an image acquisition function.
In the embodiment of the present invention, optionally, the oblique aerial image data in the target area may be acquired in real time, or may be acquired at fixed time according to a preset time period, and the embodiment of the present invention is not limited specifically.
In the embodiment of the invention, optionally, the oblique aerial image data is obtained by an oblique aerial photography technology; among them, the oblique photography technology is a high-new technology developed in the field of international photography measurement for more than ten years, and acquires rich high-resolution textures of the top surface and side view of a building by synchronously acquiring images from one vertical, four oblique and five different viewing angles. The method can not only truly reflect the ground object condition and acquire the object texture information with high precision, but also generate a real three-dimensional city model through advanced positioning, fusion, modeling and other technologies.
102. And carrying out aerial triangulation in the target area through at least one target control point preset in the target area to obtain a target external azimuth element corresponding to the inclined aerial image data.
In the embodiment of the invention, optionally, the target control point is a ground control point preset on the ground of the target area; further optionally, all target control points are used for aerial triangulation to obtain precise external azimuth elements of the aerial image.
In the embodiment of the present invention, optionally, triangulation is a method of measuring the distance of a target by measuring the angle of the target point with a known end point of a fixed reference line, both trigonometrically and geometrically. Rather than directly measuring the distance of a particular location (trilateration). When a side length and two observation angles are known, the observation target point can be calibrated as the third point of a triangle.
In an embodiment of the present invention, optionally, the external azimuth element is basic data for determining a geometric relationship of the photographic light beam in the object space. The three-dimensional coordinate value (namely line element) of the photographing center in a certain space rectangular coordinate system and three angular orientation elements for determining the space orientation of the photographing light beam are 6 pieces of data. The 3 angular orientation elements are often represented by different elements depending on the angular system employed. Further alternatively, six external orientation elements of each photo are determined, so that the correlation between the aerial photo and the photographed ground can be recovered, a ground three-dimensional model is reconstructed, the geometric and physical information of a target is extracted by using the three-dimensional model, so that how to acquire the external orientation elements of the photo is always a problem of photographic work discussion.
103. And constructing a digital model of the target area according to the inclined aerial image data and the target external azimuth element.
In the embodiment of the present invention, optionally, constructing a digital model of the target area according to the tilted aerial image data and the target external azimuth element may include:
establishing a three-dimensional model of the target area according to the inclined aerial image data and the target external azimuth element;
generating a digital surface model of the target area based on the image matching technique and the oblique aerial image data;
and constructing a digital model of the target area according to the stereoscopic model of the target area and the digital surface model of the target area.
In the embodiment of the invention, optionally, the image matching technology refers to a process of identifying the same name point between two or more images through a certain matching algorithm. The method is an important early step in the problems of image fusion, target identification, target change detection, computer vision and the like, and has wide application in a plurality of fields such as remote sensing, digital photogrammetry, computer vision, graphics, military application and the like; further, the image correlation is to evaluate the similarity of two images by using a cross-correlation function to determine the homonymy point. Firstly, the image signal in the region taking the to-be-fixed point as the center is taken out, then the image signal of the corresponding region in the other image is taken out, the correlation function of the two is calculated, and the center point of the corresponding region corresponding to the maximum value of the correlation function is taken as the homonymy point. Namely, the most similar area of the image signal is taken as the same-name area, and the center point of the same-name area is taken as the same-name point. This is also the basic principle of automated stereo measurement.
104. And according to the predetermined data processing parameters, performing data processing operation matched with the data processing parameters on the inclined aerial image data and the digital model to obtain a target three-dimensional model corresponding to the target area.
In the embodiment of the present invention, optionally, the predetermined data processing parameters include a point cloud interpolation processing parameter and a DSM generation processing parameter; further optionally, the predetermined data processing parameters further include differential correction processing parameters and mapped texture processing parameters.
In an embodiment of the present invention, optionally, the target three-dimensional model may be terrain monomer model data formed by fusing a Digital Surface Model (DSM) and a digital true shot image (TDOM).
Therefore, implementing the method for creating the oblique photography three-dimensional model described in fig. 1 can acquire oblique aerial image data in a target area, and through performing aerial triangulation on at least one target control point preset in the target area to obtain a target external azimuth element corresponding to the oblique aerial photography data, constructing a digital model of the target area according to the oblique aerial image data and the target external azimuth element, and performing matched data processing operation on the oblique aerial image data and the digital model according to predetermined data processing parameters to obtain a target three-dimensional model of the target area, acquiring images of the target area through an oblique photography technology, performing aerial triangulation on target control points in the target area to obtain the external azimuth element, and improving accuracy and reliability of constructing the digital model of the target area.
In an alternative embodiment, the method further comprises, prior to acquiring oblique aerial image data within the target area:
acquiring model construction requirement information, and determining a target area according to the model construction requirement information;
acquiring area information of a target area, wherein the area information comprises one or more of area map information and area control point information;
constructing demand information according to the region information and the model, and generating a target route;
acquiring equipment parameters of target acquisition equipment, wherein the equipment parameters comprise one or more of focal length parameters of the target acquisition equipment, acquisition resolution parameters of the target acquisition equipment and equipment performance parameters of the target acquisition equipment;
judging whether the equipment parameters meet preset equipment performance conditions or not;
when the equipment parameters are judged to meet the preset equipment performance conditions, acquiring the inclined aerial image data in the target area, wherein the method comprises the following steps:
according to the target route, controlling the target acquisition equipment to execute data acquisition operation matched with the target route so as to acquire inclined aerial image data in a target area;
when the equipment parameters are judged to not meet the preset equipment performance conditions, determining target equipment parameters which do not meet the preset equipment performance conditions, executing parameter processing operation on the target equipment parameters, and re-triggering the operation of judging whether the equipment parameters meet the preset equipment performance conditions.
In this alternative embodiment, the model build requirement information optionally includes one or more of model build resolution requirement information, model build size information, model build map requirement information, model build render requirement information, model build region requirement information.
In this optional embodiment, optionally, when the model building requirement information includes model building region requirement information, determining the target region according to the model building requirement information includes: and determining a target area according to the model construction area demand information.
In this optional embodiment, optionally, generating the target route according to the region information and the model building requirement information includes:
determining a model construction area coverage according to the area information and the model construction requirement information, and determining at least one flight route according to the model construction area coverage;
for each flight route, according to the model construction demand information, determining the navigation information of the flight route, wherein the navigation information comprises one or more of navigation frequency, navigation times, navigation duration and navigation acquisition range of the flight route;
and generating a target route according to the navigation information of each flight route.
In this alternative embodiment, optionally, the target acquisition device is a drone.
In this optional embodiment, optionally, the focal length parameter of the target acquisition device comprises a focal length range of the target acquisition device; the acquisition resolution parameters of the target acquisition equipment comprise the acquisition resolution of the target acquisition equipment; the device performance parameters of the target acquisition device include one or more of response sensitivity and response duration of the target acquisition device in response to the control instruction.
In this optional embodiment, optionally, after the parameter processing operation is performed on the target device parameter, the operation of determining whether the device parameter satisfies the preset device performance condition is performed again triggered.
In this optional embodiment, optionally, when the device parameter of the target acquisition device includes a focal length parameter of the target acquisition device and includes an acquisition resolution parameter of the target acquisition device, determining whether the device parameter meets a preset device performance condition includes:
judging whether the focal length parameter of the target acquisition equipment meets a preset focal length condition and whether the acquisition resolution parameter of the target acquisition equipment meets a preset resolution condition;
when the focal length parameter of the target acquisition equipment meets the preset focal length condition and the acquisition resolution parameter of the target acquisition equipment meets the preset resolution condition, determining that the equipment parameter meets the preset equipment performance condition;
And when the focal length parameter of the target acquisition equipment is judged to not meet the preset focal length condition and/or the acquisition resolution parameter of the target acquisition equipment is judged to not meet the preset resolution condition, determining that the equipment parameter does not meet the preset equipment performance condition.
In this optional embodiment, optionally, the target acquisition device is an unmanned aerial vehicle; further optionally, according to the target route, controlling the target acquisition device to perform a data acquisition operation matched with the target route to acquire oblique aerial image data in the target area may include:
according to the target route, controlling the unmanned aerial vehicle to execute navigation operation matched with the target route, and executing data acquisition operation in the navigation process of the target route so as to acquire inclined aerial image data in the target area.
In this alternative embodiment, optionally, the number of target device parameters is at least one; further optionally, performing a parameter processing operation on the target device parameter may include:
for each target equipment parameter, analyzing a target equipment reason that the target equipment parameter does not meet the preset equipment performance condition according to the preset equipment performance condition;
for each target equipment parameter, extracting a reason keyword in a target equipment reason of the target equipment parameter, judging whether a target parameter processing operation matched with the reason keyword of the target equipment parameter exists in a predetermined parameter processing operation set, and executing a parameter processing operation matched with the target parameter processing operation on the target equipment parameter according to the target parameter processing operation corresponding to the target equipment parameter when judging that the target parameter processing operation exists; when judging that the target parameter processing operation does not exist, calculating the matching degree between the reason keyword of the target equipment parameter and each parameter processing operation in the parameter processing operation set which is determined in advance, determining the highest matching degree from all the matching degrees, determining the parameter processing operation corresponding to the highest matching degree as the target parameter processing operation corresponding to the target equipment parameter, and executing the parameter processing operation matched with the target parameter processing operation on the target equipment parameter according to the target parameter processing operation corresponding to the target equipment parameter.
It can be seen that, implementing this optional embodiment can obtain model construction requirement information and determine a target area according to the model construction requirement information, obtain area information of the target area, generate a target course according to the area information and the model construction requirement information, obtain device parameters of the target acquisition device, determine whether the device parameters meet preset device performance conditions, if so, control the target acquisition device to perform data acquisition operation matched with the target course according to the target course so as to obtain oblique aerial image data in the target area, if not, determine the target device parameters, perform parameter processing operation on the target device parameters, and re-trigger execution of operation for determining whether the device parameters meet the preset device performance conditions, so that the matching degree between the determined target area and the model construction requirement information can be improved, thereby being beneficial to improving the accuracy and reliability of determining the target area, and further being beneficial to improving the accuracy and reliability of generating the target course, and further being beneficial to improving the effective degree of data obtained in the data acquisition operation performed by the target acquisition device; and through obtaining the equipment parameters of the target acquisition equipment and judging whether the preset equipment performance conditions are met, if so, the target acquisition equipment is controlled to execute the data acquisition operation to obtain the inclined aerial image data, so that the effectiveness of the data obtained in the data acquisition operation of the target acquisition equipment can be improved, the phenomena of data omission, data deletion or data errors and the like are prevented, and if the equipment parameters do not meet the equipment performance conditions, the parameter processing operation is executed, the accuracy and the reliability of the inclined aerial image data in a target area can be improved, and further the accuracy and the reliability of a digital model of the target area and a three-dimensional model of the target are improved.
In another alternative embodiment, the method further comprises:
acquiring real-time image data in a target area acquired by target acquisition equipment, and analyzing the real-time image data to obtain a real-time image analysis result;
judging whether target image data which does not meet preset image acquisition conditions exist in all the real-time image data according to the real-time image analysis result;
when judging that target image data which does not meet the preset image acquisition conditions exist in all the real-time image data, acquiring data acquisition parameters corresponding to each target image data, wherein the data acquisition parameters comprise acquisition time of the target image data and acquisition areas of the target image data;
determining target adjustment parameters according to data acquisition parameters corresponding to all target image data, and executing adjustment operation matched with the target adjustment parameters;
the target adjustment parameters comprise one or more of course adjustment operation, acquisition adjustment operation and calibration adjustment operation.
In this optional embodiment, optionally, analyzing the real-time image data to obtain a real-time image analysis result may include:
inputting the real-time image data into a predetermined image data analysis model to obtain an analysis model output result, and determining the real-time image analysis result according to the analysis model output result.
In this optional embodiment, optionally, the real-time image analysis result includes one or more of a real-time image resolution analysis result, a real-time image number analysis result, a real-time image acquisition frequency analysis result, and a real-time image acquisition size analysis result; further, when the real-time image analysis result includes a real-time image resolution analysis result, determining whether target image data that does not satisfy a preset image acquisition condition exists in all the real-time image data according to the real-time image analysis result may include:
determining the image resolution of the real-time image data for each real-time image data according to the real-time image resolution analysis result;
judging whether image data with image resolution not meeting preset resolution conditions exist in all the real-time image data according to the image resolution of all the real-time image data;
when judging that the image data with the image resolution which does not meet the preset resolution condition does not exist in all the real-time image data, determining that the target image data which does not meet the preset image acquisition condition does not exist in all the real-time image data;
when it is judged that at least one image data with image resolution which does not meet the preset resolution condition exists in all the real-time image data, determining that target image data which does not meet the preset image acquisition condition exists in all the real-time image data.
In this optional embodiment, further optionally, when it is determined that there is no target influence data that does not satisfy the preset image capturing condition in all the real-time image data, the present procedure may be ended.
In this optional embodiment, optionally, determining the target adjustment parameter according to the data acquisition parameters corresponding to all the target image data, and performing an adjustment operation matched with the target adjustment parameter, including:
according to the data acquisition parameters corresponding to all the target influence data, determining the data acquisition parameters which do not meet the preset image acquisition conditions as target adjustment parameters, wherein the number of the target adjustment parameters is at least one;
for each target adjustment parameter, determining an adjustment coefficient of the target adjustment parameter according to a preset image acquisition condition and a current parameter value of the target adjustment parameter, and executing adjustment operation matched with the adjustment coefficient of the target adjustment parameter on the target adjustment parameter.
In this optional embodiment, optionally, the course adjustment operation includes one or more of a course voyage frequency adjustment operation, a course trajectory adjustment operation, a course voyage number adjustment operation, a course voyage duration adjustment operation; the acquisition adjustment operation comprises one or more of acquisition frequency adjustment operation, acquisition precision adjustment operation, acquisition resolution adjustment operation, acquisition region adjustment operation and acquisition range adjustment operation; the calibration adjustment operations include one or more of a calibration coefficient adjustment operation and a calibration error adjustment operation.
Therefore, the implementation of the alternative embodiment can acquire the real-time image data in the target area acquired by the target acquisition equipment and analyze the real-time image data to obtain a real-time image analysis result, judge whether the target image data exists in all implementation image data based on the real-time image analysis result, acquire the data acquisition parameters corresponding to each target image data if the target image data exists, further determine the target adjustment parameters and execute the matched adjustment operation, analyze the real-time image data acquired by the target acquisition equipment in real time to obtain the real-time image analysis result, adjust the real-time image data in real time when the acquisition abnormality occurs in the image data, improve the validity of the acquired image data, be beneficial to improving the accuracy and the reliability of the acquired image data, and determine the target adjustment parameters and execute the matched adjustment operation when the target image data exists in the real-time image analysis result, be beneficial to improving the efficiency and the intelligence of the adjustment operation on the target adjustment parameters, and be beneficial to improving the accuracy and the reliability of the subsequent construction of the digital model of the target area and the target three-dimensional model corresponding to the target area.
In yet another alternative embodiment, the predetermined data processing parameters include point cloud interpolation processing parameters and DSM generation processing parameters;
According to the predetermined data processing parameters, performing data processing operation matched with the data processing parameters on the inclined aerial image data and the digital model to obtain a target three-dimensional model corresponding to the target area, wherein the method comprises the following steps:
determining original point cloud data from oblique aerial image data according to the point Yun Nacha processing parameters, performing preset point cloud data processing operation on all the original point cloud data to obtain target point cloud data, performing operation matched with the point cloud data processing parameters on all the target point cloud data according to the preset point cloud data processing parameters to obtain a preliminary data image, and performing data conversion operation on the preliminary data image to obtain a target data image;
generating processing parameters according to the DSM, and determining target modeling parameters from the digital model, wherein the target modeling parameters comprise model drawing surface parameters, model resolution parameters and model camera height parameters;
generating a preliminary three-dimensional model based on the target modeling parameters and the target data image;
according to the model construction requirement, determining texture requirement parameters and differential requirement parameters matched with the model construction requirement;
generating three-dimensional model processing parameters according to the texture demand parameters and the differential demand parameters, and executing processing operation matched with the three-dimensional model processing parameters on the preliminary three-dimensional model to obtain a target three-dimensional model corresponding to the target area;
Wherein the three-dimensional model processing parameters include differential correction processing parameters and texture mapping processing parameters.
In this alternative embodiment, the digital surface model (Digital Surface Model, DSM) may optionally refer to a ground elevation model that includes the height of surface structures, bridges, trees, and the like.
In this alternative embodiment, optionally, the point cloud data (pointclouddata) refers to a set of vectors in a three-dimensional coordinate system. The scan data is recorded in the form of dots, each dot containing three-dimensional coordinates and carrying other information about the properties of the dot, such as color, reflectivity, intensity, etc. The point cloud data are generally acquired by a laser scanner, a camera, a three-dimensional scanner and other devices, and can be used for three-dimensional modeling, scene reconstruction, robot navigation, virtual reality, augmented reality and other applications; the main characteristics of the point cloud data are that the point cloud data have high-precision, high-resolution and high-dimensional geometric information, and can intuitively represent the information of the shape, the surface, the texture and the like of an object in space. Processing and analysis of point cloud data typically requires the use of techniques of computer vision and computer graphics, such as point cloud filtering, registration, segmentation, reconstruction, identification and classification, and the like.
In this optional embodiment, optionally, performing a preset point cloud data processing operation on all original point cloud data to obtain target point cloud data, including:
for each original point cloud data, performing point cloud classification processing operation on the original point cloud data to obtain a point cloud class of the original point cloud data;
and for each point cloud class, performing point cloud quality inspection operation on all original point cloud data included in the point cloud class, judging whether point cloud data which does not meet the preset quality condition exist in all original point cloud data included in the point cloud class, and eliminating all point cloud data which does not meet the preset quality condition when judging that point cloud data which does not meet the preset quality condition exist in all original point cloud data included in the point cloud class, so as to obtain target point cloud data.
In this optional embodiment, optionally, according to preset point cloud data processing parameters, performing an operation of matching with the point cloud data processing parameters on all target point cloud data to obtain a preliminary data image, and performing a data conversion operation on the preliminary data image to obtain a target data image, including:
according to preset point cloud data processing parameters, preprocessing operation is carried out on all the target point cloud data so as to update all the target point cloud data, wherein the preprocessing operation comprises one or more of point cloud registration, point cloud denoising, density resampling, invalid point deletion, point cloud coloring and point cloud segmentation;
Performing interpolation operation on all target point cloud data in a grid form to obtain a preliminary data image;
and according to the point cloud data processing parameters, determining data format requirement information corresponding to the point cloud data, and performing data conversion operation matched with the data format requirement information on the preliminary data image to obtain a target data image.
In this alternative embodiment, optionally, generating the preliminary three-dimensional model based on the target modeling parameters and the target data image includes:
based on the target modeling parameters, an image model fitting operation is performed on the target data image to generate a preliminary three-dimensional model.
In this optional embodiment, optionally, generating three-dimensional model processing parameters according to the texture requirement parameter and the differential requirement parameter, and performing a processing operation matched with the three-dimensional model processing parameters on the preliminary three-dimensional model to obtain a target three-dimensional model corresponding to the target area, where the method includes:
and generating three-dimensional model processing parameters according to the texture demand parameters and the differential processing parameters, and performing texture selection, texture mapping and texture color homogenizing operation on the preliminary three-dimensional model to obtain a target three-dimensional model corresponding to the target region.
In this alternative embodiment, optionally, differential correction refers to using the tiny area of aerial photographs or other remote sensing images as a correction unit, and implementing any one of the transformations between the two images by the geometric transformation of the correction unit; texture Mapping (Texture Mapping), also known as Texture Mapping, is a process of Mapping Texture pixels in Texture space to pixels in screen space.
It can be seen that implementing this alternative embodiment can process the oblique aerial image by using the point cloud interpolation processing parameters to obtain a target data image, determine the target modeling parameters according to the DSM generation processing parameters to generate a preliminary three-dimensional model, perform a matched processing operation on the preliminary three-dimensional model in combination with the model construction requirements to obtain the target three-dimensional model, generate a corresponding preliminary data image in combination with the point cloud data, perform a data conversion operation on the preliminary data image to obtain the target data image, improve the accuracy and reliability of obtaining the target data image, and determine the target modeling parameters by using the DSM generation processing parameters to generate the preliminary three-dimensional model in combination with the target data image, thereby being beneficial to improving the intelligence and efficiency of generating the preliminary three-dimensional model, improving the accuracy of generating the preliminary three-dimensional model, and also being beneficial to performing differential correction processing and texture mapping processing on the preliminary three-dimensional model to obtain the target three-dimensional model, improving the fineness of the obtained target three-dimensional model, and improving the accuracy and reliability of the obtained target three-dimensional model.
In yet another alternative embodiment, the aerial triangulation is performed in the target area by at least one target control point preset in the target area to obtain a target external azimuth element corresponding to the tilted aerial image data, including:
for each target control point preset in a target area, judging whether the target control point meets preset point position conditions according to preset point position thumbnails, and when judging that the target control point does not meet the preset point position conditions, carrying out positioning change on the target control point according to the preset point position thumbnails so as to update the point position of the target control point;
performing aerial triangulation in a target area through all target control points to obtain a triangulation result, and calculating triangulation adjustment corresponding to the triangulation result according to a preset adjustment algorithm;
judging whether coarse difference control points exist in all target control points or not based on triangulation adjustment, wherein the triangulation adjustment comprises coarse difference detection values of all target control points, and the coarse difference control points are used for representing the target control points with the coarse difference detection values being larger than or equal to a preset coarse difference detection threshold value;
when the rough difference control points exist in all the target control points, eliminating all the rough difference control points from the target control points, and updating all the target control points;
And generating target external azimuth elements corresponding to the inclined aerial image data based on all the updated target control points.
In this alternative embodiment, optionally, when it is determined that all the target control points meet the preset point location condition, the present process may be ended.
In this optional embodiment, optionally, for each target control point preset in the target area, determining, according to a preset point location thumbnail, whether the target control point meets a preset point location condition includes:
for each target control point preset in a target area, judging whether the target control point is positioned at a position matched with the target control point in the point position thumbnail according to a preset point position thumbnail;
when the target control point is judged to be positioned at the position matched with the target control point in the point position thumbnail, determining that the target control point meets the preset point position condition;
and when the target control point is judged not to be positioned at the position matched with the target control point in the point position thumbnail, determining that the target control point does not meet the preset point position condition.
In this alternative embodiment, further alternatively, when it is determined that no coarse control point exists among all the target control points, the present flow may be ended.
In this alternative embodiment, the software relative orientation index is represented by a backprojection error, for example, by oblique photography data processing software, wherein the error in backprojection of the connection point is the maximum residual 3 pixels requiring better than 1 pixel. Each pair of connection points are uniformly distributed, the number of each pair of connection points is automatically and relatively oriented, after comprehensive judgment is carried out on image control points submitted by the outside industry and outside industry check points according to point position sketch and description, the point positions of the image control points and the outside industry check points are accurately determined, automatic aerial triangulation is adopted, coarse difference detection is carried out on the connection points and the image control points, coarse difference points are removed, aerial triangulation adjustment is carried out on the regional network adjustment by adopting a beam method, after calculation of the regional network adjustment is finished, the residual error of a basic orientation point is not more than 0.7 times of the limit value (namely +/-0.245 m) of the error in an encryption point specified by the specification, the check point error is not more than 1.2 times of the limit value (namely +/-0.42 m) of the error in the encryption point, and the difference of common points between the regional networks is not more than 2 times of the limit value (namely +/-0.7 m) of the error in the encryption point; the elevation error is not larger than the 0.7 times limit value (namely + -0.28 m) of the error of the encryption point Gao Chengzhong, and the target external azimuth element corresponding to the inclined aerial image data is generated after the control triangulation is completed.
Therefore, implementing the alternative embodiment can judge whether each target control point meets the preset point location condition according to the preset point location sketch, if not, the target control point is subjected to positioning change to update the point location of the target control point, aerial triangulation is performed in the target area through all the target control points to obtain a triangulation result, and the triangulation adjustment is calculated according to the preset adjustment algorithm, so that whether all the target control points have coarse-difference control points with coarse-difference detection values larger than or equal to the preset coarse-difference detection threshold value is judged, if so, all the coarse-difference control points are removed from the target control points to update the target control points, and target external azimuth elements are generated based on all the updated target control points, so that the target control points which do not meet the point location condition can be subjected to positioning change to update the point location of the target control points, the measurement accuracy and the measurement reliability of subsequent aerial triangulation can be improved, the accuracy and the measurement reliability of the obtained triangulation result can be improved, and the accuracy and the reliability of the calculated triangulation adjustment can be improved; and eliminating and updating all the rough control points to the target control points, thereby being beneficial to improving the accuracy and reliability of generating the external target azimuth element, further being beneficial to improving the accuracy and reliability of a digital model of a subsequent generation target area, and further being beneficial to improving the accuracy and reliability of a target three-dimensional model of the subsequent generation target area.
In yet another alternative embodiment, the method further includes, after performing a data processing operation matched with the data processing parameters on the tilted aerial image data and the digital model according to the predetermined data processing parameters to obtain a target three-dimensional model corresponding to the target region:
acquiring application demand information corresponding to a target three-dimensional model, wherein the application demand information comprises model reconstruction platform demand information of the target three-dimensional model and application demand information of an application platform of the target three-dimensional model;
judging whether the target three-dimensional model is matched with the application demand information or not;
when the target three-dimensional model is not matched with the application demand information, determining at least one parameter to be adjusted in the target three-dimensional model;
for each parameter to be adjusted, determining an adjustment operation parameter of the parameter to be adjusted according to the application demand information, and executing parameter adjustment operation matched with the adjustment operation parameter of the parameter to be adjusted on the parameter to be adjusted to obtain a target reconstruction model;
detecting a model precision coefficient of the target reconstruction model, and judging whether the model precision coefficient meets a preset precision condition;
when the model precision coefficient is judged to meet the preset precision condition, updating the target three-dimensional model according to the target reconstruction model;
When the model precision coefficient is judged not to meet the preset precision condition, the model precision coefficient of the target reconstruction model is triggered again, and whether the model precision coefficient meets the operation of the preset precision condition is judged.
In this optional embodiment, optionally, the application requirement information further includes metadata integrity requirement information, absolute precision requirement information, activity requirement information, and data integrity requirement information; the metadata integrity requirement information comprises the integrity degree of a data file under a view data folder; the absolute precision requirement information comprises the matching degree of a three-dimensional model coordinate system and a preset project technical design; the gesture demand information comprises that the model time precision meets the preset standard condition; the data integrity requirement information comprises the matching degree of the data format and the file organization form and the preset technical design requirements, the integrity degree of the data folder and the damage and loss degree of the data.
In this optional embodiment, optionally, determining whether the target three-dimensional model matches the application requirement information may include:
determining model size information of the target three-dimensional model and model precision information of the target three-dimensional model, determining model size conditions according to model reconstruction platform demand information of the target three-dimensional model, and determining model precision conditions according to application demand information of an application platform of the target three-dimensional model;
Judging whether model size information of the target three-dimensional model meets model size conditions and whether model precision information of the target three-dimensional model meets model precision conditions;
when the model size information of the target three-dimensional model meets the model size condition and the model precision information of the target three-dimensional model meets the model precision condition, determining that the target three-dimensional model is matched with the application demand information;
and when the model size information of the target three-dimensional model is judged to not meet the model size condition and/or the model precision information of the target three-dimensional model is judged to not meet the model precision condition, determining that the target three-dimensional model is not matched with the application demand information.
In this alternative embodiment, optionally, when it is determined that the target three-dimensional model matches the application requirement information, the present flow may be ended.
In this alternative embodiment, optionally, the adjustment operation parameter of each parameter to be adjusted includes one or more of a numerical adjustment operation, a weight adjustment operation, and a quantity adjustment operation.
Therefore, the implementation of the optional embodiment can judge whether the target three-dimensional model is matched with the application demand information according to the application demand information corresponding to the target three-dimensional model, if not, the parameters to be adjusted are determined, and the matched parameter adjustment operation is carried out on the parameters to obtain the target reconstruction model, so that the target three-dimensional model can be adjusted in time when the model parameters of the target three-dimensional model do not meet the demand information, the timeliness and the instantaneity of adjusting the target three-dimensional model are improved, the intelligence of adjusting the target three-dimensional model is improved, the experience and the comfort of a user using the three-dimensional model are improved, and the use demands of the user can be met; and the model precision coefficient of the target reconstruction model is detected, and the operation of updating the target three-dimensional model according to the target reconstruction model is executed when the model precision coefficient is determined to meet the preset precision condition, so that the accuracy and the reliability of updating the target three-dimensional model can be improved, the intelligent of adjusting the target three-dimensional model can be further improved, the experience and the comfort of a user using the three-dimensional model can be further improved, and the use requirements of the user can be further met.
Example two
Referring to fig. 2, fig. 2 is a flow chart of another method for creating a three-dimensional model of oblique photography according to an embodiment of the present invention. The method for establishing the oblique photography three-dimensional model described in fig. 2 can be applied to an apparatus for establishing the oblique photography three-dimensional model, and also can be applied to a cloud server or a local server for establishing the oblique photography three-dimensional model, and the embodiment of the invention is not limited. As shown in fig. 2, the method for creating the oblique photography three-dimensional model may include the following operations:
201. and acquiring oblique aerial image data in the target area.
202. And carrying out aerial triangulation in the target area through at least one target control point preset in the target area to obtain a target external azimuth element corresponding to the inclined aerial image data.
203. And for each piece of inclined aerial image data, performing image data classification operation on the inclined aerial image data to obtain the data type of the inclined aerial image data.
In the embodiment of the invention, optionally, the data category comprises one or more of a building data category, a topography data category, an indicative identification data category, a road facility data category, a bridge data category, an indoor and facility data category; further, the indicative identification data category includes one or more of guideboard data and landmark building data, and the embodiment of the present invention is not particularly limited.
In an embodiment of the present invention, optionally, for each oblique aerial image data, performing an image data classification operation on the oblique aerial image data to obtain a data class of the oblique aerial image data may include:
and inputting the inclined aerial image data into a preset image data classification model for each inclined aerial image data to obtain an image data classification result, and determining the data type of the inclined aerial image data according to the image data classification result.
204. For each data category, performing feature extraction operations on all oblique aerial image data included in the data category to obtain image feature data of the data category, and generating modeling feature data of the data category according to the image feature data of the data category.
In an embodiment of the present invention, optionally, generating modeling feature data of the data category according to image feature data of the data category may include:
and executing feature fusion operation on all the image feature data of the data category to obtain a feature fusion result, and determining the feature fusion result as modeling feature data of the data category.
205. And constructing a digital model of the target area according to the modeling characteristic data, the inclined aerial image data and the target external azimuth element of each data category.
In the embodiment of the invention, optionally, according to modeling feature data and inclined aerial image data of each data category, a digital surface model of a target area is established by combining an image matching technology;
establishing a three-dimensional model of the target area according to the inclined aerial image data and the target external azimuth element;
and constructing a digital model of the target area according to the stereoscopic model of the target area and the digital surface model of the target area.
206. And according to the predetermined data processing parameters, performing data processing operation matched with the data processing parameters on the inclined aerial image data and the digital model to obtain a target three-dimensional model corresponding to the target area.
In the embodiment of the present invention, for the detailed descriptions of step 201 to step 202 and step 206, please refer to the other descriptions of step 101 to step 102 and step 104 in the first embodiment, and the detailed description of the embodiment of the present invention is omitted.
As can be seen, implementing the method for creating a three-dimensional model of oblique photography described in fig. 2 can perform an image data classification operation on each oblique aerial image data to obtain a data class of the oblique aerial image data, perform a feature extraction operation on all oblique aerial image data included in the data class for each data class to obtain image feature data of the data class and further generate modeling feature data, construct a digital model of a target region according to the modeling feature data, the oblique aerial image data, and the target external orientation element of each data class, perform a classification operation on each oblique aerial image data first, improve accuracy and reliability of the data class from which each oblique aerial image data is obtained, and improve efficiency of subsequently generating the modeling feature data and constructing the digital model of the target region based on each data class; further, by performing feature extraction operation on oblique aviation influence data included in each data category, accuracy and reliability of obtaining image feature data of the data category can be improved, accuracy and reliability of generating modeling feature data can be improved, further modeling feature data of each data category, oblique aviation image data and target external orientation elements can be combined to construct a digital model of a target area, accuracy and reliability of constructing the digital model can be improved, intelligence of constructing the digital model can be improved, accuracy and reliability of constructing a target three-dimensional model of a target area can be improved, and accuracy and reliability of constructing a target three-dimensional model of the target area can be improved.
Example III
Referring to fig. 3, fig. 3 is a schematic structural diagram of an apparatus for creating a three-dimensional model of oblique photography according to an embodiment of the present invention. As shown in fig. 3, the apparatus for creating a oblique photography three-dimensional model may include:
an acquisition module 301, configured to acquire oblique aerial image data in a target area;
the measurement module 302 is configured to perform aerial triangulation in the target area through at least one target control point preset in the target area, so as to obtain a target external azimuth element corresponding to the oblique aerial image data;
the construction module 303 is configured to construct a digital model of the target area according to the oblique aerial image data and the target external azimuth element;
and the processing module 304 is configured to perform a data processing operation matched with the data processing parameter on the oblique aerial image data and the digital model according to the predetermined data processing parameter, so as to obtain a target three-dimensional model corresponding to the target region.
As can be seen, implementing the apparatus described in fig. 3 can obtain oblique aerial image data in a target area, and perform aerial triangulation on at least one target control point preset in the target area to obtain a target external azimuth element corresponding to the oblique aerial image data, construct a digital model of the target area according to the oblique aerial image data and the target external azimuth element, perform matched data processing operations on the oblique aerial image data and the digital model according to predetermined data processing parameters to obtain a target three-dimensional model of the target area, collect an image of the target area through an oblique photography technology, and perform aerial triangulation on the target control point in the target area to obtain the external azimuth element, so as to improve accuracy and reliability of constructing the digital model of the target area, and improve intelligence of constructing the digital model of the target area, further facilitate improving a matching degree between the digital model of the target area and the target area, and facilitate improving intelligence of constructing the three-dimensional model of the target area and further facilitate improving accuracy and efficiency of establishing the accurate three-dimensional model.
In an alternative embodiment, the obtaining module 301 is further configured to obtain model building requirement information before obtaining oblique aerial image data in the target area;
as shown in fig. 4, the apparatus further includes:
a determining module 305, configured to determine a target area according to the model building requirement information;
the acquiring module 301 is further configured to acquire area information of the target area, where the area information includes one or more of area map information and area control point information;
the first generation module 306 is configured to generate a target route according to the region information and the model construction requirement information;
the acquiring module 301 is further configured to acquire device parameters of the target acquisition device, where the device parameters include one or more of a focal length parameter of the target acquisition device, an acquisition resolution parameter of the target acquisition device, and a device performance parameter of the target acquisition device;
a judging module 307, configured to judge whether the device parameter meets a preset device performance condition;
when the judging module 307 judges that the device parameter meets the preset device performance condition, the specific ways of acquiring the oblique aerial image data in the target area by the acquiring module 301 include:
according to the target route, controlling the target acquisition equipment to execute data acquisition operation matched with the target route so as to acquire inclined aerial image data in a target area;
The determining module 305 is further configured to determine, when the determining module 307 determines that the device parameter does not meet the preset device performance condition, a target device parameter that does not meet the preset device performance condition;
the execution module 308 is configured to perform a parameter processing operation on the target device parameter, and re-trigger the determination module 307 to perform an operation of determining whether the device parameter meets a preset device performance condition.
As can be seen, implementing the apparatus described in fig. 4 can obtain model construction requirement information, determine a target area according to the model construction requirement information, obtain area information of the target area, generate a target course according to the area information and the model construction requirement information, obtain device parameters of the target acquisition device, determine whether the device parameters meet preset device performance conditions, if so, control the target acquisition device according to the target course to perform data acquisition operation matched with the target course so as to obtain oblique aerial image data in the target area, if not, determine the target device parameters, perform parameter processing operation on the target device parameters, and re-trigger execution of operation for determining whether the device parameters meet the preset device performance conditions, so that the matching degree between the determined target area and the model construction requirement information can be improved, thereby being beneficial to improving the accuracy and reliability of determining the target area, being beneficial to improving the accuracy and reliability of generating the target course, and being beneficial to improving the effective degree of data obtained in the data acquisition operation performed by the target acquisition device; and through obtaining the equipment parameters of the target acquisition equipment and judging whether the preset equipment performance conditions are met, if so, the target acquisition equipment is controlled to execute the data acquisition operation to obtain the inclined aerial image data, so that the effectiveness of the data obtained in the data acquisition operation of the target acquisition equipment can be improved, the phenomena of data omission, data deletion or data errors and the like are prevented, and if the equipment parameters do not meet the equipment performance conditions, the parameter processing operation is executed, the accuracy and the reliability of the inclined aerial image data in a target area can be improved, and further the accuracy and the reliability of a digital model of the target area and a three-dimensional model of the target are improved.
In another alternative embodiment, as shown in fig. 4, the acquiring module 301 is further configured to acquire real-time image data in the target area acquired by the target acquisition device;
the apparatus further comprises:
the analysis module 309 is configured to analyze the real-time image data to obtain a real-time image analysis result;
the judging module 307 is further configured to judge whether target image data that does not meet a preset image acquisition condition exists in all the real-time image data according to the real-time image analysis result;
the acquiring module 301 is further configured to acquire a data acquisition parameter corresponding to each target image data when the judging module 307 judges that target image data that does not meet a preset image acquisition condition exists in all real-time image data, where the data acquisition parameter includes an acquisition time of the target image data and an acquisition area of the target image data;
the determining module 305 is further configured to determine a target adjustment parameter according to data acquisition parameters corresponding to all the target image data;
the execution module 308 is further configured to execute an adjustment operation matched with the target adjustment parameter;
the target adjustment parameters comprise one or more of course adjustment operation, acquisition adjustment operation and calibration adjustment operation.
Therefore, the device described in fig. 4 can acquire and analyze the real-time image data in the target area acquired by the target acquisition device to obtain a real-time image analysis result, determine whether the target image data exists in all the implementation image data based on the real-time image analysis result, acquire the data acquisition parameters corresponding to each target image data if the target image data exists, further determine the target adjustment parameters and execute the matched adjustment operation, analyze the real-time image data acquired by the target acquisition device to obtain the real-time image analysis result, adjust the real-time image data in real time when the acquisition abnormality occurs in the image data to improve the validity of the acquired image data, be beneficial to improving the accuracy and the reliability of the acquired image data, and determine the target adjustment parameters and execute the matched adjustment operation when the target image data exists in the real-time image analysis result, be beneficial to improving the efficiency and the intelligence of the adjustment operation on the target adjustment parameters, and be beneficial to improving the accuracy and the reliability of the subsequent construction of the digital model of the target area and the target three-dimensional model corresponding to the target area.
In yet another alternative embodiment, as shown in FIG. 4, the predetermined data processing parameters include point cloud interpolation processing parameters and DSM generation processing parameters;
the specific manner of the processing module 304 executing the data processing operation matched with the data processing parameters on the oblique aerial image data and the digital model according to the predetermined data processing parameters to obtain the target three-dimensional model corresponding to the target region includes:
determining original point cloud data from oblique aerial image data according to the point Yun Nacha processing parameters, performing preset point cloud data processing operation on all the original point cloud data to obtain target point cloud data, performing operation matched with the point cloud data processing parameters on all the target point cloud data according to the preset point cloud data processing parameters to obtain a preliminary data image, and performing data conversion operation on the preliminary data image to obtain a target data image;
generating processing parameters according to the DSM, and determining target modeling parameters from the digital model, wherein the target modeling parameters comprise model drawing surface parameters, model resolution parameters and model camera height parameters;
generating a preliminary three-dimensional model based on the target modeling parameters and the target data image;
According to the model construction requirement, determining texture requirement parameters and differential requirement parameters matched with the model construction requirement;
generating three-dimensional model processing parameters according to the texture demand parameters and the differential demand parameters, and executing processing operation matched with the three-dimensional model processing parameters on the preliminary three-dimensional model to obtain a target three-dimensional model corresponding to the target area;
wherein the three-dimensional model processing parameters include differential correction processing parameters and texture mapping processing parameters.
It can be seen that the apparatus described in fig. 4 is implemented to process the oblique aerial image through the point cloud interpolation processing parameters to obtain a target data image, determine the target modeling parameters according to the DSM generation processing parameters to generate a preliminary three-dimensional model, perform a matched processing operation on the preliminary three-dimensional model in combination with the model construction requirements to obtain the target three-dimensional model, generate a corresponding preliminary data image in combination with the point cloud data, perform a data conversion operation on the preliminary data image to obtain the target data image, improve the accuracy and reliability of the obtained target data image, determine the target modeling parameters through the DSM generation processing parameters to generate the preliminary three-dimensional model in combination with the target data image, and thereby facilitate improving the intelligence and efficiency of generating the preliminary three-dimensional model, and facilitate improving the accuracy of generating the preliminary three-dimensional model, and also perform a differential correction process and a texture mapping process on the preliminary three-dimensional model to obtain the target three-dimensional model, facilitate improving the fineness and reliability of the obtained target three-dimensional model.
In yet another alternative embodiment, as shown in fig. 4, the specific manner of the measurement module 302 performing aerial triangulation in the target area through at least one target control point preset in the target area to obtain the target external azimuth element corresponding to the oblique aerial image data includes:
for each target control point preset in a target area, judging whether the target control point meets preset point position conditions according to preset point position thumbnails, and when judging that the target control point does not meet the preset point position conditions, carrying out positioning change on the target control point according to the preset point position thumbnails so as to update the point position of the target control point;
performing aerial triangulation in a target area through all target control points to obtain a triangulation result, and calculating triangulation adjustment corresponding to the triangulation result according to a preset adjustment algorithm;
judging whether coarse difference control points exist in all target control points or not based on triangulation adjustment, wherein the triangulation adjustment comprises coarse difference detection values of all target control points, and the coarse difference control points are used for representing the target control points with the coarse difference detection values being larger than or equal to a preset coarse difference detection threshold value;
When the rough difference control points exist in all the target control points, eliminating all the rough difference control points from the target control points, and updating all the target control points;
and generating target external azimuth elements corresponding to the inclined aerial image data based on all the updated target control points.
As can be seen, implementing the apparatus described in fig. 4 can determine whether each target control point meets a preset point location condition according to a preset point location outline, if not, perform positioning modification on the target control point to update its point location, perform aerial triangulation in a target area through all target control points to obtain a triangulation result, calculate a triangulation adjustment according to a preset adjustment algorithm, further determine whether there is a coarse control point with a coarse detection value greater than or equal to a preset coarse detection threshold in all target control points, if so, reject all coarse control points from the target control points to update the target control points, generate a target external azimuth element based on all updated target control points, and perform positioning modification on the target control points that do not meet the point location condition to update their point location, thereby being beneficial to improving the measurement accuracy and measurement reliability of subsequent aerial triangulation, and further being beneficial to improving the accuracy and reliability of the obtained triangulation result; and eliminating and updating all the rough control points to the target control points, thereby being beneficial to improving the accuracy and reliability of generating the external target azimuth element, further being beneficial to improving the accuracy and reliability of a digital model of a subsequent generation target area, and further being beneficial to improving the accuracy and reliability of a target three-dimensional model of the subsequent generation target area.
In yet another alternative embodiment, as shown in fig. 4, the obtaining module 301 is further configured to obtain application requirement information corresponding to the target three-dimensional model, where the application requirement information includes model reconstruction platform requirement information of the target three-dimensional model, and application requirement information of an application platform of the target three-dimensional model;
the judging module 307 is further configured to judge whether the target three-dimensional model is matched with the application requirement information;
the determining module 305 is further configured to determine at least one parameter to be adjusted in the target three-dimensional model when the judging module 307 judges that the target three-dimensional model is not matched with the application requirement information;
the determining module 305 is further configured to determine, for each parameter to be adjusted, an adjustment operation parameter of the parameter to be adjusted according to the application requirement information;
the execution module 308 is further configured to perform a parameter adjustment operation on the parameter to be adjusted, where the parameter adjustment operation matches an adjustment operation parameter of the parameter to be adjusted, so as to obtain a target reconstruction model;
the apparatus further comprises:
a detection module 310, configured to detect a model precision coefficient of the target reconstruction model;
the judging module 307 is further configured to judge whether the model precision coefficient meets a preset precision condition; when the model precision coefficient is judged not to meet the preset precision condition, the re-triggering detection module 310 executes the model precision coefficient of the detection target reconstruction model and executes the operation of judging whether the model precision coefficient meets the preset precision condition;
The updating module 311 is configured to update the target three-dimensional model according to the target reconstruction model when the determining module 307 determines that the model precision coefficient meets a preset precision condition.
Therefore, the device described in fig. 4 can determine whether the target three-dimensional model is matched with the application demand information according to the application demand information corresponding to the target three-dimensional model, if not, the parameters to be adjusted are determined, and the matched parameter adjustment operation is performed on the parameters to obtain the target reconstruction model, so that the target three-dimensional model can be adjusted in time when the model parameters of the target three-dimensional model do not meet the demand information, the timeliness and the instantaneity of adjusting the target three-dimensional model are improved, the intelligence of adjusting the target three-dimensional model is improved, the experience and the comfort of a user using the three-dimensional model are improved, and the use demands of the user can be met; and the model precision coefficient of the target reconstruction model is detected, and the operation of updating the target three-dimensional model according to the target reconstruction model is executed when the model precision coefficient is determined to meet the preset precision condition, so that the accuracy and the reliability of updating the target three-dimensional model can be improved, the intelligent of adjusting the target three-dimensional model can be further improved, the experience and the comfort of a user using the three-dimensional model can be further improved, and the use requirements of the user can be further met.
In yet another alternative embodiment, as shown in fig. 4, the apparatus further comprises:
the classifying module 312 is configured to perform an image data classifying operation on each oblique aerial image data to obtain a data class of the oblique aerial image data before the constructing module 303 constructs a digital model of the target region according to the oblique aerial image data and the target external azimuth element;
an extraction module 313, configured to perform, for each data category, a feature extraction operation on all oblique aerial image data included in the data category, so as to obtain image feature data of the data category;
a second generating module 314, configured to generate modeling feature data of the data class according to the image feature data of the data class;
the specific way of constructing the digital model of the target region by the construction module 303 according to the oblique aerial image data and the target external azimuth element includes:
and constructing a digital model of the target area according to the modeling characteristic data, the inclined aerial image data and the target external azimuth element of each data category.
As can be seen, implementing the apparatus described in fig. 4 can perform an image data classification operation on each oblique aerial image data to obtain a data class of the oblique aerial image data, perform a feature extraction operation on all the oblique aerial image data included in the data class for each data class to obtain image feature data of the data class and further generate modeling feature data, construct a digital model of a target area according to the modeling feature data, the oblique aerial image data and the target external azimuth element of each data class, perform a classification operation on each oblique aerial image data first, improve accuracy and reliability of the data class to obtain each oblique aerial image data, and improve efficiency of subsequently generating the modeling feature data and constructing the digital model of the target area based on each data class; further, by performing feature extraction operation on oblique aviation influence data included in each data category, accuracy and reliability of obtaining image feature data of the data category can be improved, accuracy and reliability of generating modeling feature data can be improved, further modeling feature data of each data category, oblique aviation image data and target external orientation elements can be combined to construct a digital model of a target area, accuracy and reliability of constructing the digital model can be improved, intelligence of constructing the digital model can be improved, accuracy and reliability of constructing a target three-dimensional model of a target area can be improved, and accuracy and reliability of constructing a target three-dimensional model of the target area can be improved.
Example IV
Referring to fig. 5, fig. 5 is a schematic structural diagram of a device for creating a three-dimensional model of oblique photography according to an embodiment of the present invention. As shown in fig. 5, the apparatus for creating a oblique photography three-dimensional model may include:
a memory 401 storing executable program codes;
a processor 402 coupled with the memory 401;
the processor 402 invokes executable program codes stored in the memory 401 to execute the steps in the method for creating a oblique photography three-dimensional model described in the first or second embodiment of the present invention.
Example five
The embodiment of the invention discloses a computer storage medium which stores computer instructions for executing the steps in the method for establishing the oblique photography three-dimensional model described in the first or second embodiment of the invention when the computer instructions are called.
Example six
An embodiment of the present invention discloses a computer program product including a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute the steps in the method for creating a oblique photography three-dimensional model described in the first or second embodiment.
The apparatus embodiments described above are merely illustrative, wherein the modules illustrated as separate components may or may not be physically separate, and the components shown as modules may or may not be physical, i.e., may be located in one place, or may be distributed over a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above detailed description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course by means of hardware. Based on such understanding, the foregoing technical solutions may be embodied essentially or in part in the form of a software product that may be stored in a computer-readable storage medium including Read-Only Memory (ROM), random-access Memory (Random Access Memory, RAM), programmable Read-Only Memory (Programmable Read-Only Memory, PROM), erasable programmable Read-Only Memory (Erasable Programmable Read Only Memory, EPROM), one-time programmable Read-Only Memory (OTPROM), electrically erasable programmable Read-Only Memory (EEPROM), compact disc Read-Only Memory (Compact Disc Read-Only Memory, CD-ROM) or other optical disc Memory, magnetic disc Memory, tape Memory, or any other medium that can be used for computer-readable carrying or storing data.
Finally, it should be noted that: the embodiment of the invention discloses a method and a device for establishing an oblique photography three-dimensional model, which are disclosed by the embodiment of the invention and are only used for illustrating the technical scheme of the invention, but not limiting the technical scheme; although the invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that; the technical scheme recorded in the various embodiments can be modified or part of technical features in the technical scheme can be replaced equivalently; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions.
Claims (8)
1. A method for creating a three-dimensional model of oblique photography, the method comprising:
acquiring oblique aerial image data in a target area;
performing aerial triangulation in the target area through at least one target control point preset in the target area to obtain a target external azimuth element corresponding to the inclined aerial image data;
constructing a digital model of the target area according to the inclined aerial image data and the target external azimuth element;
According to the predetermined data processing parameters, performing data processing operation matched with the data processing parameters on the inclined aerial image data and the digital model to obtain a target three-dimensional model corresponding to the target region;
acquiring real-time image data in the target area acquired by target acquisition equipment, and analyzing the real-time image data to obtain a real-time image analysis result;
judging whether target image data which does not meet preset image acquisition conditions exist in all the real-time image data according to the real-time image analysis result;
when judging that the target image data which does not meet the preset image acquisition conditions exist in all the real-time image data, acquiring data acquisition parameters corresponding to each piece of target image data, wherein the data acquisition parameters comprise acquisition time of the target image data and acquisition areas of the target image data;
determining target adjustment parameters according to data acquisition parameters corresponding to all the target image data, and executing adjustment operation matched with the target adjustment parameters;
wherein the target adjustment parameters comprise one or more of course adjustment operation, acquisition adjustment operation and calibration adjustment operation;
The analyzing the real-time image data to obtain a real-time image analysis result includes:
inputting the real-time image data into a predetermined image data analysis model to obtain an analysis model output result, and determining a real-time image analysis result according to the analysis model output result; the real-time image analysis result comprises one or more of a real-time image resolution analysis result, a real-time image quantity analysis result, a real-time image acquisition frequency analysis result and a real-time image acquisition size analysis result; when the real-time image analysis result includes the real-time image resolution analysis result, the determining, according to the real-time image analysis result, whether target image data that does not satisfy a preset image acquisition condition exists in all the real-time image data includes:
determining the image resolution of the real-time image data for each real-time image data according to the real-time image resolution analysis result;
judging whether image data with image resolution not meeting a preset resolution condition exist in all the real-time image data according to the image resolution of all the real-time image data;
When judging that no image data with image resolution which does not meet the preset resolution condition exists in all the real-time image data, determining that no target image data which does not meet the preset image acquisition condition exists in all the real-time image data;
when judging that at least one image data with image resolution which does not meet the preset resolution condition exists in all the real-time image data, determining that target image data which does not meet the preset image acquisition condition exists in all the real-time image data;
the aerial triangulation is performed in the target area through at least one target control point preset in the target area to obtain a target external azimuth element corresponding to the oblique aerial image data, which comprises the following steps:
for each target control point preset in the target area, judging whether the target control point meets preset point position conditions according to preset point position thumbnails, and when judging that the target control point does not meet the preset point position conditions, carrying out positioning change on the target control point according to the preset point position thumbnails so as to update the point position of the target control point;
Performing aerial triangulation in the target area through all the target control points to obtain a triangulation result, and calculating a triangulation adjustment corresponding to the triangulation result according to a preset adjustment algorithm;
judging whether coarse control points exist in all the target control points or not based on the triangulation adjustment, wherein the triangulation adjustment comprises coarse detection values of each target control point, and the coarse control points are used for representing target control points with coarse detection values being greater than or equal to a preset coarse detection threshold;
when judging that the rough difference control points exist in all the target control points, eliminating all the rough difference control points from the target control points, and updating all the target control points;
and generating a target external azimuth element corresponding to the inclined aerial image data based on all the updated target control points.
2. The method of claim 1, further comprising, prior to the acquiring oblique aerial image data within the target area:
obtaining model construction requirement information, and determining a target area according to the model construction requirement information;
Acquiring area information of the target area, wherein the area information comprises one or more of area map information and area control point information;
constructing demand information according to the region information and the model, and generating a target route;
acquiring equipment parameters of target acquisition equipment, wherein the equipment parameters comprise one or more of focal length parameters of the target acquisition equipment, acquisition resolution parameters of the target acquisition equipment and equipment performance parameters of the target acquisition equipment;
judging whether the equipment parameters meet preset equipment performance conditions or not;
when the equipment parameter is judged to meet the preset equipment performance condition, acquiring the inclined aerial image data in the target area comprises the following steps:
according to the target route, controlling the target acquisition equipment to execute data acquisition operation matched with the target route so as to acquire oblique aerial image data in the target area;
when the equipment parameter is judged to not meet the preset equipment performance condition, determining a target equipment parameter which does not meet the preset equipment performance condition, executing parameter processing operation on the target equipment parameter, and re-triggering the operation for judging whether the equipment parameter meets the preset equipment performance condition.
3. The method of creating a oblique photography three-dimensional model according to claim 2, wherein the predetermined data processing parameters include a point cloud interpolation processing parameter and a DSM generation processing parameter;
and executing data processing operation matched with the data processing parameters on the inclined aerial image data and the digital model according to the predetermined data processing parameters to obtain a target three-dimensional model corresponding to the target region, wherein the method comprises the following steps of:
determining original point cloud data from the oblique aerial image data according to the point cloud interpolation processing parameters, performing preset point cloud data processing operation on all the original point cloud data to obtain target point cloud data, performing operation matched with the point cloud data processing parameters on all the target point cloud data according to the preset point cloud data processing parameters to obtain a preliminary data image, and performing data conversion operation on the preliminary data image to obtain a target data image;
generating processing parameters according to the DSM, and determining target modeling parameters from the digital model, wherein the target modeling parameters comprise model drawing surface parameters, model resolution parameters and model camera height parameters;
Generating a preliminary three-dimensional model based on the target modeling parameters and the target data image;
according to the model construction requirement, determining texture requirement parameters and differential requirement parameters matched with the model construction requirement;
generating three-dimensional model processing parameters according to the texture demand parameters and the differential demand parameters, and executing processing operation matched with the three-dimensional model processing parameters on the preliminary three-dimensional model to obtain a target three-dimensional model corresponding to the target region;
wherein the three-dimensional model processing parameters include differential correction processing parameters and texture mapping processing parameters.
4. The method according to claim 2, wherein after performing a data processing operation matched with the data processing parameter on the oblique aerial image data and the digital model according to a predetermined data processing parameter to obtain a target three-dimensional model corresponding to the target region, the method further comprises:
acquiring application demand information corresponding to the target three-dimensional model, wherein the application demand information comprises model reconstruction platform demand information of the target three-dimensional model and application demand information of an application platform of the target three-dimensional model;
Judging whether the target three-dimensional model is matched with the application demand information or not;
when the target three-dimensional model is not matched with the application demand information, determining at least one parameter to be adjusted in the target three-dimensional model;
for each parameter to be adjusted, determining an adjustment operation parameter of the parameter to be adjusted according to the application demand information, and executing parameter adjustment operation matched with the adjustment operation parameter of the parameter to be adjusted on the parameter to be adjusted to obtain a target reconstruction model;
detecting a model precision coefficient of the target reconstruction model, and judging whether the model precision coefficient meets a preset precision condition;
when the model precision coefficient is judged to meet the preset precision condition, updating the target three-dimensional model according to the target reconstruction model;
and when the model precision coefficient is judged to not meet the preset precision condition, re-triggering the model precision coefficient for detecting the target reconstruction model, and judging whether the model precision coefficient meets the preset precision condition.
5. A method of constructing a tilted photographic three-dimensional model as in any of claims 1-3, wherein prior to constructing a digital model of the target region from the tilted aerial image data and the target external azimuth element, the method further comprises:
For each piece of inclined aerial image data, performing image data classification operation on the inclined aerial image data to obtain the data category of the inclined aerial image data;
for each data category, performing feature extraction operation on all the inclined aerial image data included in the data category to obtain image feature data of the data category, and generating modeling feature data of the data category according to the image feature data of the data category;
the constructing a digital model of the target area according to the oblique aerial image data and the target external azimuth element comprises the following steps:
and constructing a digital model of the target area according to the modeling characteristic data of each data category, the inclined aerial image data and the target external azimuth element.
6. An apparatus for creating a three-dimensional model of oblique photography, the apparatus comprising:
the acquisition module is used for acquiring inclined aerial image data in the target area;
the measuring module is used for carrying out aerial triangulation in the target area through at least one target control point preset in the target area so as to obtain a target external azimuth element corresponding to the inclined aerial image data;
The construction module is used for constructing a digital model of the target area according to the inclined aerial image data and the target external azimuth element;
the processing module is used for executing data processing operation matched with the data processing parameters on the inclined aerial image data and the digital model according to the predetermined data processing parameters to obtain a target three-dimensional model corresponding to the target area;
the acquisition module is also used for acquiring real-time image data in the target area acquired by the target acquisition equipment;
the analysis module is used for analyzing the real-time image data to obtain a real-time image analysis result;
the judging module is used for judging whether target image data which does not meet preset image acquisition conditions exist in all the real-time image data according to the real-time image analysis result;
the acquisition module is further configured to acquire data acquisition parameters corresponding to each piece of target image data when the judgment module judges that the target image data which does not meet the preset image acquisition conditions exists in all pieces of real-time image data, where the data acquisition parameters include acquisition time of the target image data and acquisition area of the target image data;
The determining module is used for determining target adjustment parameters according to the data acquisition parameters corresponding to all the target image data;
the execution module is used for executing the adjustment operation matched with the target adjustment parameter;
wherein the target adjustment parameters comprise one or more of course adjustment operation, acquisition adjustment operation and calibration adjustment operation;
the specific way for analyzing the real-time image data by the analysis module to obtain the real-time image analysis result comprises the following steps:
inputting the real-time image data into a predetermined image data analysis model to obtain an analysis model output result, and determining a real-time image analysis result according to the analysis model output result;
the real-time image analysis result comprises one or more of a real-time image resolution analysis result, a real-time image quantity analysis result, a real-time image acquisition frequency analysis result and a real-time image acquisition size analysis result;
when the real-time image analysis result includes the real-time image resolution analysis result, the judging module judges whether target image data which does not meet a preset image acquisition condition exists in all the real-time image data according to the real-time image analysis result, and the judging module comprises the following steps:
Determining the image resolution of the real-time image data for each real-time image data according to the real-time image resolution analysis result;
judging whether image data with image resolution not meeting a preset resolution condition exist in all the real-time image data according to the image resolution of all the real-time image data;
when judging that no image data with image resolution which does not meet the preset resolution condition exists in all the real-time image data, determining that no target image data which does not meet the preset image acquisition condition exists in all the real-time image data;
when judging that at least one image data with image resolution which does not meet the preset resolution condition exists in all the real-time image data, determining that target image data which does not meet the preset image acquisition condition exists in all the real-time image data;
the specific method for obtaining the target external azimuth element corresponding to the inclined aerial image data by the measuring module through at least one target control point preset in the target area and carrying out aerial triangulation in the target area comprises the following steps:
For each target control point preset in the target area, judging whether the target control point meets preset point position conditions according to preset point position thumbnails, and when judging that the target control point does not meet the preset point position conditions, carrying out positioning change on the target control point according to the preset point position thumbnails so as to update the point position of the target control point;
performing aerial triangulation in the target area through all the target control points to obtain a triangulation result, and calculating a triangulation adjustment corresponding to the triangulation result according to a preset adjustment algorithm;
judging whether coarse control points exist in all the target control points or not based on the triangulation adjustment, wherein the triangulation adjustment comprises coarse detection values of each target control point, and the coarse control points are used for representing target control points with coarse detection values being greater than or equal to a preset coarse detection threshold;
when judging that the rough difference control points exist in all the target control points, eliminating all the rough difference control points from the target control points, and updating all the target control points;
And generating a target external azimuth element corresponding to the inclined aerial image data based on all the updated target control points.
7. An apparatus for creating a three-dimensional model of oblique photography, the apparatus comprising:
a memory storing executable program code;
a processor coupled to the memory;
the processor invokes the executable program code stored in the memory to perform the method of constructing a oblique photography three-dimensional model according to any one of claims 1-5.
8. A computer storage medium storing computer instructions which, when invoked, are adapted to perform the method of constructing a oblique photography three-dimensional model according to any one of claims 1 to 5.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112862966A (en) * | 2021-02-20 | 2021-05-28 | 中煤航测遥感集团有限公司 | Method, device and equipment for constructing three-dimensional model of earth surface and storage medium |
| CN114998536A (en) * | 2022-05-31 | 2022-09-02 | 广州市城市规划勘测设计研究院 | Model generation method and device based on novel basic mapping and storage medium |
| CN116051785A (en) * | 2023-02-08 | 2023-05-02 | 广州市城市规划勘测设计研究院 | Method, device, equipment and storage medium for constructing urban live-action three-dimensional model |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2019128641A (en) * | 2018-01-22 | 2019-08-01 | キヤノン株式会社 | Image processing device, image processing method and program |
| US11189104B2 (en) * | 2019-08-28 | 2021-11-30 | Snap Inc. | Generating 3D data in a messaging system |
-
2023
- 2023-08-07 CN CN202310980824.9A patent/CN116704138B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112862966A (en) * | 2021-02-20 | 2021-05-28 | 中煤航测遥感集团有限公司 | Method, device and equipment for constructing three-dimensional model of earth surface and storage medium |
| CN114998536A (en) * | 2022-05-31 | 2022-09-02 | 广州市城市规划勘测设计研究院 | Model generation method and device based on novel basic mapping and storage medium |
| CN116051785A (en) * | 2023-02-08 | 2023-05-02 | 广州市城市规划勘测设计研究院 | Method, device, equipment and storage medium for constructing urban live-action three-dimensional model |
Non-Patent Citations (3)
| Title |
|---|
| "倾斜摄影测量应用于城市三维单体模型构建的研究";施骏骋;《基础科学辑》;参见正文第3-4章 * |
| "基于无人机遥感的电力走廊精细化制图研究";马威威;《工程科技Ⅱ辑》;参见正文第3章 * |
| 马威威."基于无人机遥感的电力走廊精细化制图研究".《工程科技Ⅱ辑》.2021,参见正文第3章. * |
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