CN113124824A - Unmanned aerial vehicle photogrammetry acquisition planning method and system based on significance calculation - Google Patents

Unmanned aerial vehicle photogrammetry acquisition planning method and system based on significance calculation Download PDF

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CN113124824A
CN113124824A CN202110435201.4A CN202110435201A CN113124824A CN 113124824 A CN113124824 A CN 113124824A CN 202110435201 A CN202110435201 A CN 202110435201A CN 113124824 A CN113124824 A CN 113124824A
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point
acquisition
points
peak
significance
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王海晓
张国星
吕贞
丁旭
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Inner Mongolia Agricultural University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C5/00—Measuring height; Measuring distances transverse to line of sight; Levelling between separated points; Surveyors' levels
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C11/00—Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C11/00—Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
    • G01C11/02—Picture taking arrangements specially adapted for photogrammetry or photographic surveying, e.g. controlling overlapping of pictures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
    • G06T17/05—Geographic models

Abstract

The invention discloses an unmanned aerial vehicle photogrammetry acquisition planning method and system based on significance calculation, wherein the planning method comprises the following steps of S1, extracting peak points of a survey area based on significance calculation to generate a smooth earth surface elevation model; and S2, planning the pose of the acquisition point based on the smooth earth surface elevation model. The advantages are that: the earth surface model is generated based on the maximum significance calculation and the linear interpolation, the acquisition point planning is carried out on the model, and the performance of the unmanned aerial vehicle in data acquisition in a high-fall area is improved. The problem of the conflict between the reconstruction precision and the flight safety is solved, and the method can be used for generating a three-dimensional model of an international metropolitan city.

Description

Unmanned aerial vehicle photogrammetry acquisition planning method and system based on significance calculation
Technical Field
The invention relates to the technical field of path planning, in particular to a method and a system for unmanned aerial vehicle photogrammetry acquisition planning based on significance calculation.
Background
Because the elevation of a building in a survey area is unknown, the current method for solving the problem of collecting the high fall area mainly comprises the following steps:
1. the increase of the image overlapping rate is beneficial to reducing the probability of the occurrence of the mask and the broken hole. The efficiency of data acquisition and data processing is reduced due to the excessively high overlapping degree, images are acquired under the conditions of fixed elevation and fixed inclination angle in the mode, and the accuracy of reconstruction cannot be guaranteed
2. The supplementary acquisition method is used for carrying out independent secondary acquisition on a high-rise building with insufficient overlapping degree after reconstruction. However, the improvement of the accuracy of the region after the fly-back does not change the reconstruction accuracy of the entire region.
3. The use of a tele acquisition device is a method to adapt to high-altitude acquisition scenes by improving the camera model. Because the collection position is high, the blind area that the building eaves caused is just bigger.
4. The layered acquisition method acquires the area at different heights for multiple times according to terrain Data (DSM) of a target survey area. The method needs terrain data of a target survey area, which is similar to a terrain tracking method, and inaccurate terrain data can cause the occurrence of an impact event of the unmanned aerial vehicle; meanwhile, the acquisition inclination angle of the layered acquisition and terrain tracking method is fixed, and the acquisition effect on vertical building wall surfaces or mountain cliffs is not good.
5. The variable inclination angle acquisition or close acquisition method ensures that the acquisition visual angle is vertical to the surface of the building as much as possible by changing the inclination angle during image acquisition, thereby ensuring the accuracy. But this approach increases the risk of unmanned aerial vehicle flight, while varying camera poses also a challenge to ensure that the overlap ratio is affected.
6. An acquisition method based on the horizontal outline of a building. The collection locations are arranged at the building edge. The method needs the unmanned aerial vehicle to perform online calculation in the air, so that the acquisition cost is high; meanwhile, building extraction based on deep learning is unstable, non-building areas and building areas in cities are located in the survey area, and the method cannot generate a collection visual angle for the non-building areas.
Therefore, a new urban high-fall terrain tracking method is urgently needed, the accuracy and the overlapping rate of the acquisition results are ensured under the condition that the acquisition process is safe and efficient, and the problem that the acquisition accuracy of the unmanned aerial vehicle in a high-fall area and a non-high-fall area conflicts with the flight safety is solved.
Disclosure of Invention
The invention aims to provide a method and a system for unmanned aerial vehicle photogrammetry acquisition planning based on significance calculation, so that the problems in the prior art are solved.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
an unmanned aerial vehicle photogrammetry acquisition planning method based on significance calculation comprises the following steps,
s1, extracting peak points of the measuring area based on the significance calculation to generate a smooth earth surface elevation model;
and S2, planning the pose of the acquisition point based on the smooth earth surface elevation model.
Preferably, step S1 specifically includes the following steps,
s11, calculating a peak point of the measuring area based on the significance according to the original DSM of the measuring area; DSM, a digital surface elevation model;
and S12, generating a smooth earth surface elevation model by utilizing a linear interpolation mode based on the peak points of the measurement areas.
Preferably, the original DSM of the survey area is obtained by a process,
calculating the precision Q of the acquired reconstruction result according to the absolute altitude;
according to absolute altitude HSAFEImage overlapping rate alpha of acquisition point and horizontal field angle FOV of cameraxDetermining the distance D between two adjacent acquisition pointsview；
Arranging a route and acquisition points in the survey area according to the distance between the acquisition points;
acquiring an inclined pose of the acquisition point relative to a vertical visual angle pose according to the acquisition inclination angle;
constructing an original DSM for the survey area based on the tilt pose of the acquisition point relative to the vertical view pose.
Preferably, the specific way of arranging the flight path and the acquisition point in the survey area is,
arranging N number of flight paths in the horizontal direction of the survey area, arranging M number of flight paths in the vertical direction, and arranging K number of flight paths on each flight path with the distance of DviewCollection point of (1).
Preferably, step S11 specifically includes the following steps,
defining the transverse direction and the longitudinal direction at will in an original DSM of a measuring area, constructing transverse waves and longitudinal waves according to point clouds intercepted in the transverse direction and the longitudinal direction, traversing all points in the transverse waves and the longitudinal waves, and acquiring a starting point, a middle point and an end point of each local maximum value;
and performing significance calculation on each local maximum to obtain a peak point of the measurement area, and generating a smooth earth surface elevation model.
Preferably, the specific process of obtaining the start point, the middle point and the end point of each local maximum is,
defining point clouds intercepted in any direction in an original DSM of a survey area as transverse waves, and point clouds intercepted in a direction vertical to the any direction as longitudinal waves; traverse all points x in shear and longitudinal wavesiIf the current point xiIs greater than the previous point xi-1And is larger than the latter point xi+1Then update the local maximum midpoint pmidStarting point pleftEnd point prightThe number m of local maximum values; and finally outputting the starting point, the middle point and the end point of each found local maximum value.
Preferably, the specific process of performing the significance calculation to obtain the peak point of the measurement region is,
performing significance calculation on each local maximum; respectively at the midpoint peak of the wave0Find a point from the peak midpoint peak0Starting, stopping when a point larger than the median is encountered, and taking the difference between the point and the peak as significance left on two sides of the current local maximummin、rightminTaking the minimum value of the significance of the left side and the right side as the significance promoters of the current local maximum value; finally, judging whether the wave crest is kept according to the significance threshold value; the intersection of the latitude and longitude peaks in the original DSM or the intersection of the peak weights is used as the peak point of the measurement region.
Preferably, step S2 specifically includes the following steps,
s21, according to the smooth earth surface elevation model, acquiring the number of new air routes in the horizontal direction and the vertical direction and the distance D ' between adjacent new acquisition points on the new air routes by utilizing the image overlapping rate alpha ' in the air route distance calculation process 'viewArranging new routes and new acquisition points in the survey area according to the number of the new routes and the distance between the new acquisition points;
s22, FOV according to known camera horizontal field anglexAcquiring a field angle coverage distance S by the default overlapping rate alpha and the precision Q of the acquisition and reconstruction result;
and S23, sequentially determining the poses of all the new acquisition points according to the coverage distance S of the field angle.
Preferably, in step S23, specifically,
from section At-3The point starts to reach B by the distance St-3Based on line segment At-3Bt-3Arranged perpendicular to the line segment and at a distance h from the perpendicularviewPosition p oft-3And A ist-2And At-3Is S x alpha, and then B is determinedt-2Determining the poses of all the new acquisition points by analogy in the method;
wherein A ist-3、Bt-3Respectively for the camera in position pt-3FOV of field angle of time cameraxFOV of elevation model of upper and lower sides and smooth earth surfacexAn intersection in the field angle direction; a. thet-3Is a lower side intersection point, Bt-3Are the upper intersection points and recur in turn.
Preferably, after the cameras are arranged according to the pose of the acquisition points, when the included angle between the main sights of two adjacent new acquisition points is greater than a preset degree, a plurality of transitional acquisition points are inserted between the main sights of the two adjacent new acquisition points; the insertion process of the transition acquisition points is that according to the pose ptAnd pt+1Obtaining intersection points k of the lower main sight lines, inserting transition acquisition points with the number of W according to a preset insertion interval, enabling the main sight lines of the transition acquisition points to pass through the intersection points k, and enabling the main sight lines to be h according to the distance between the transition acquisition points and the intersection points kviewIs determinedAnd crossing the pose of the acquisition point.
The invention also aims to provide an unmanned aerial vehicle photogrammetry acquisition planning system based on significance calculation, which is used for realizing the unmanned aerial vehicle photogrammetry acquisition planning method based on significance calculation, and the acquisition planning system comprises
An original DSM acquisition module; original DSM for obtaining survey area;
an elevation model generation module; the system comprises a model generator, a model acquisition module, a model generation module and a data processing module, wherein the model generator is used for extracting peak points of a measurement area based on significance calculation to generate a smooth earth surface elevation model;
a pose planning module; and planning the pose of the acquisition point based on the smooth earth surface elevation model.
The invention has the beneficial effects that: 1. the earth surface model is generated based on the maximum significance calculation and the linear interpolation, the acquisition point planning is carried out on the model, and the performance of the unmanned aerial vehicle in data acquisition in a high-fall area is improved. 2. The problem of the conflict between the reconstruction precision and the flight safety is solved, and the method can be used for generating a three-dimensional model of an international metropolitan city. 3. The application range is wide, and the game scene data generating device can be used as a game scene material production tool to improve the generation speed and effect of game scene data; as a production tool for automatic driving high-precision maps; the modeling tool is used for traffic simulation and BIM simulation high-definition scenes; as a tool for producing data of a city digital twin management bottom layer; the urban data acquisition planning module is used as an unmanned aerial vehicle aerial survey software urban data acquisition planning module.
Drawings
FIG. 1 is a schematic flow chart illustrating the principle of pose planning and pose acquisition in an embodiment of the present invention;
FIG. 2 is a detailed flow diagram of planning pose acquisition in an embodiment of the present invention;
FIG. 3 is a schematic diagram of initial acquisition point pose planning in an embodiment of the present invention;
FIG. 4 is a schematic view of visualization of an initial pose acquisition and a reconstruction result in an embodiment of the present invention;
FIG. 5 is a DSM, orthographic projection output after initial reconstruction of a survey area in an embodiment of the invention;
FIG. 6 is a schematic diagram of the interception of shear waves and longitudinal waves according to an embodiment of the present invention;
FIG. 7 is a schematic diagram of a transverse wave form in the central region of the measurement area according to an embodiment of the present invention;
FIG. 8 is a schematic diagram comparing the saliency-based peak extraction with other common methods in an embodiment of the present invention;
FIG. 9 is a diagram illustrating intersection results of horizontal and vertical peaks according to an embodiment of the present invention;
FIG. 10 is a schematic diagram comparing SDSM to DSM in an embodiment of the invention;
FIG. 11 is a schematic illustration of horizontally and vertically arranged path lines in an embodiment of the invention;
FIG. 12 is a schematic diagram of elevation curves of latitude and longitude sections on a path line in accordance with an embodiment of the present invention;
FIG. 13 is a schematic diagram of observation points arranged on a cross-sectional curve according to an embodiment of the present invention;
FIG. 14 is a schematic view of an embodiment of the present invention illustrating a transition pose interposed between two poses;
FIG. 15 is a schematic diagram of collection point pose distribution based on a smooth surface model in an embodiment of the present invention;
fig. 16 is a schematic diagram comparing before planning reconstruction and after planning reconstruction in the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention.
As shown in fig. 1 and fig. 2, in the present embodiment, there is provided a method for planning the acquisition of a photogrammetric survey of an unmanned aerial vehicle based on saliency calculation, including the following steps,
s1, extracting peak points of the measuring area based on the significance calculation to generate a smooth earth surface elevation model;
and S2, planning the pose of the acquisition point based on the smooth earth surface elevation model.
In this embodiment, the planning method mainly includes two parts, which are respectively to obtain a peak point of a measurement area based on the significance to generate a smooth surface elevation model and plan a pose of a collection point based on the smooth surface elevation model. The following is a detailed description of each of these two sections.
The method for obtaining the peak points of the measurement area based on the significance to generate the smooth earth surface elevation model comprises two steps of: s11, calculating a peak point of the measuring area based on the significance according to the original DSM of the measuring area; and S12, generating a smooth earth surface elevation model by utilizing a linear interpolation mode based on the peak points of the measurement areas. The DSM is a Digital Surface elevation Model (DSM).
Before generating a smooth earth surface elevation model according to an initial earth surface elevation model, an initial earth surface elevation model (DSM) needs to be acquired, and the modes for acquiring the initial earth surface elevation model (DSM) are various, such as laser scanning of an unmanned aerial vehicle and equivalent remote sensing satellites; the method is used for planning the initial acquisition point.
The initial acquisition acquires data at an absolutely safe flying height for generating a high precision raw DSM. At present, the opened DSM data has poor timeliness and poses great threat to the flight safety of the unmanned aerial vehicle, so the method uses the step of initial acquisition to acquire the latest urban terrain information.
The absolute safety elevation is the height that any substrate cannot reach, at which the collection is absolutely safe. The default absolute altitude is 300 m.
With the planned initial acquisition point, the details of the original DSM from which the survey area was acquired are as follows (see figure 3),
calculating the precision Q of the acquired reconstruction result according to the absolute altitude; the calculation formula is as follows,
Q＝f/HSAFE
wherein Q is the modeling precision; f is the focal length of the camera; hSAFEThe absolute altitude is 300 m;
according to absolute altitude HSAFEImage overlapping rate alpha of acquisition point and horizontal field angle FOV of cameraxDetermining the distance D between two adjacent acquisition pointsview(ii) a The calculation formula is as follows,
Figure BDA0003032906840000061
wherein D isviewAs adjacent acquisition points Pt、Pt-1The distance between them; alpha is the default overlap ratio; FOV (field of View)xIs the horizontal field angle of the camera; the value of the default overlap ratio α can be determined according to specific needs so as to better meet actual requirements, for example, the value is 60%; FOV (field of View)xThe horizontal field angle of the camera, the parameter is determined by the camera used, and belongs to a known value;
arranging a route and acquisition points in the survey area according to the distance between the acquisition points; the specific arrangement mode is that N number of flight paths are arranged in the horizontal direction of the survey area, M number of flight paths are arranged in the vertical direction, and K number of flight paths are arranged on each flight path, and the distance between the K number of flight paths and the D number of flight pathsviewThe collection point of (1);
acquiring an inclined pose of the acquisition point relative to a vertical visual angle pose according to the acquisition inclination angle; the calculation formula is as follows,
P′＝P*Sin(θ)-1
wherein P is the pose P of the acquisition point at the vertical viewing angle; p' is an inclined pose of the acquisition point relative to the vertical view pose; theta is the collection inclination angle and takes a value of 15 degrees.
Constructing an original DSM for the survey area based on the tilt pose of the acquisition point relative to the vertical view pose.
And when the planning of the initial acquisition point is finished, the position visualization result of the acquisition point in the space is shown in fig. 4, and the upper strip is the position of the acquisition point. The high-precision DSM model and the orthographic projection of the survey area reconstructed through multiple views after initial acquisition are shown in FIG. 5, and the left graph and the right graph in FIG. 5 are respectively the original DSM and the orthographic projection view output after the survey area is reconstructed through initial acquisition.
Firstly, extracting peak points of a measurement area based on significance calculation to generate a smooth earth surface elevation model
The method comprises the steps of S11, calculating a peak point and S12 of a measuring area based on significance according to original DSM of the measuring area, and generating a smooth earth surface elevation model based on the peak point of the measuring area by utilizing a linear interpolation mode.
The step S11 specifically includes the following contents,
defining the transverse direction and the longitudinal direction at will in an original DSM of a measuring area, constructing transverse waves and longitudinal waves according to point clouds intercepted in the transverse direction and the longitudinal direction, traversing all points in the transverse waves and the longitudinal waves, and acquiring a starting point, a middle point and an end point of each local maximum value;
and performing significance calculation on each local maximum to obtain a peak point of the measurement area, and generating a smooth earth surface elevation model.
The specific process of acquiring the starting point, the middle point and the end point of each local maximum value is as follows:
performing significance calculation on each local maximum; respectively at the midpoint peak of the wave0Find a point from the peak midpoint peak0Starting, stopping when a point larger than the median is encountered, and taking the difference between the point and the peak as significance left on two sides of the current local maximummin、rightminTaking the minimum value of the significance of the left side and the right side as the significance promoters of the current local maximum value; finally, judging whether the wave crest is kept according to the significance threshold value;
the specific process of obtaining the peak point of the measurement area by performing significance calculation is as follows:
performing significance calculation on each local maximum; respectively at the midpoint peak of the wave0Find a point from the peak midpoint peak0Starting, stopping when a point larger than the median is encountered, and taking the difference between the point and the peak as significance left on two sides of the current local maximummin、rightminTaking the minimum value of the significance of the left side and the right side as the significance promoters of the current local maximum value; finally, judging whether the wave crest is kept according to the significance threshold value; the intersection of the latitude and longitude peaks in the original DSM or the intersection of the peak weights is used as the peak point of the measurement region.
The specific operation process of step S12 is: interpolating between the obtained peak points of the measurement area to generate a smooth earth surface elevation model; the smooth surface elevation model fills the streets between the two buildings, preventing the location of the collection points from being located between the two buildings.
In summary, step S1 includes two steps, namely, generating a smooth surface elevation model based on the saliency-based terrain peak point calculation and based on the peak point linear interpolation.
1. Terrain peak point calculation based on saliency: defining the point cloud intercepted in any direction (which may be the X-axis) in the original DSM of the initial acquisition as shear waves, and the point cloud intercepted in a direction perpendicular to any direction (which may be the Y-direction) as compressional waves, the visualization of which is shown in fig. 6. The transverse wave shape of the central region of the survey area can be seen in fig. 7.
The peak of a building in a measuring area in the oscillogram belongs to the wave crest, and the street belongs to the wave trough. In the non-building area in the survey area, although the wave crest of no building area is remarkable, a small wave crest still exists.
The theoretical definition of a peak is "maximum over a range of wavelengths". Although it cannot be determined what the wavelength of the waveform is intercepted in the current scenario, the peak can be understood as the maximum value in a range, and the range at least includes three points. Thus, a peak can be defined as a point x in a segment of a waveiIt is more or less adjacent to x than itselfi-1、xi+1Are all large. Of course, x needs to be considerediThe case when it is equal to its left and right neighbors. Furthermore, significance (prominence) is also required to describe whether this peak should belong to a peak, i.e. the degree of protrusion of the current peak.
The method for extracting the wave crest based on the significance can be divided into two steps: and searching local maximum values and calculating significance. When searching for local maxima, the algorithm traverses points x on the wavei(neither the default starting point nor the end point is likely to be a peak value), if the current point x isiIs greater than the previous point xi-1And is larger than the latter point xi+1Then update the local maximum midpoint pmidStarting point pleftEnd point prightAnd the number m of local maximum values. And finally outputting the starting point, the middle point and the end point of each found local maximum value.
The significance calculation method of the current local maximum is to respectively calculate peak points peak in wave crests0One point is found on both the left and right sides of the image. Starting from the midpoint of the peak, a point larger than the median is encounteredAnd then stop. Significance left on both sides of the maximum by calculating the difference between the point and the peakmin、rightminThe minimum value of the significance of the left side and the right side is taken as the significance promoters of the current maximum value. And finally judging whether the wave crest is kept or not according to the significance threshold value.
The peak is obtained by the maximum saliency, and the ratio of the peak to other common peak extraction methods (threshold, distance, wave width) is shown in fig. 8. The comparison shows that the peak extraction method based on significance has the best effect. All latitudes and longitudes are traversed on the original DSM, and the intersection of peaks at longitude and latitude is solved as the peak of the survey area. And intersection of the results in the horizontal and vertical directions is shown in fig. 9.
2. Generating a smooth surface elevation model (SDSM) based on peak point linear interpolation: and interpolating between the extracted peaks in the measurement area to generate a smooth earth surface elevation model. The smooth surface elevation model fills the streets between the two buildings, preventing the location of the collection points from being located between the two buildings. The buildings in the city are mostly made of steel structures, and the electronic compass and the GPS signals of the unmanned aerial vehicle are threatened greatly. In addition, the vertical facade of the building is converted into a slope with a certain inclination angle. Preventing the dip angle of the collection point from suddenly becoming severe. By comparing the SDSM to the DSM, as shown in FIG. 10, the vast majority of the narrow streets in the building area are filled while building elevations and open area elevations are preserved. It is safe as long as the planned acquisition location is not below the elevation drone of the SDSM at this point.
Planning acquisition point pose based on smooth earth surface elevation model
This section corresponds to the content of step S2, and step S2 is specifically as follows,
s21, according to the smooth earth surface elevation model, acquiring the number of new air routes in the horizontal direction and the vertical direction and the distance D ' between adjacent new acquisition points on the new air routes by utilizing the image overlapping rate alpha ' in the air route distance calculation process 'viewArranging new routes and new acquisition points in the survey area according to the number of the new routes and the distance between the new acquisition points; the calculation formula is as follows,
Figure BDA0003032906840000091
Figure BDA0003032906840000092
wherein alpha' is the image overlapping rate in the course of calculating the route distance; x, Y are the horizontal and longitudinal distances of the test area, respectively; m 'and N' are respectively the number of new air routes in the horizontal direction and the number of new air routes in the vertical direction;
s22, FOV according to known camera horizontal field anglexAcquiring a field angle coverage distance S by the overlapping rate alpha on the default route and the precision Q of the acquisition and reconstruction result; the calculation formula is as follows,
hview＝f*Q-1
Figure BDA0003032906840000093
wherein h isviewCamera position height to meet accuracy requirements; alpha is the default on-lane overlap ratio.
And S23, sequentially determining the poses of all the new acquisition points according to the coverage distance S of the field angle.
In this embodiment, step S23 is specifically,
from section At-3The point starts to pass through the distance A to reach Bt-3Based on line segment At-3Bt-3Arranged perpendicular to the line segment and at a distance h from the perpendicularviewPosition p oft-3And A ist-2And At-3Is S x alpha, and then B is determinedt-2Determining the poses of all the new acquisition points by analogy in the method;
wherein A ist-3、Bt-3Respectively for the camera in position pt-3FOV of field angle of time cameraxFOV of elevation model of upper and lower sides and smooth earth surfacexAn intersection in the field angle direction; a. thet-3Is a lower side intersection point, Bt-3Are the upper intersection points and recur in turn.
In the embodiment, after the cameras are arranged according to the pose of the acquisition points, when the included angle between the main sight lines of two adjacent acquisition points is greater than a preset degree, a plurality of transitional acquisition points are inserted between the main sight lines of the two adjacent acquisition points; the insertion process of the transition acquisition points is that according to the pose ptAnd pt+1Obtaining intersection points k of the lower main sight lines, inserting transition acquisition points with the number of W according to a preset insertion interval, enabling the main sight lines of the transition acquisition points to pass through the intersection points k, and enabling the main sight lines to be h according to the distance between the transition acquisition points and the intersection points kviewAnd determining the pose of the transition acquisition point.
In summary, step S2 specifically includes two parts, namely, generating interpolation between observation points that change with terrain and observation points that change drastically.
1. And generating observation points along with terrain: an acquisition point camera pose is generated based on the generated smooth surface elevation model (SDSM). Firstly, the module generates a plurality of equidistant routes in a survey area, a horizontal route is generated along the latitude direction, a vertical route is generated along the longitude direction, and the spatial distribution result is shown in fig. 11. The default overlap rate α' of the images during the course spacing calculation is 80%. M 'and N' are the number of transverse and longitudinal routes respectively, and X, Y is the horizontal and longitudinal distance of survey area respectively.
Then, arranging acquisition points on the sailing line and calculating the inclination angle of the camera to ensure that the visual angle direction of the camera is vertical to the section. The results of visualizing the cross-sectional elevation changes of the survey area central longitudinal and transverse routes on the SDSM are shown in FIG. 12.
The default on-line overlap rate α is 60%, according to the known camera field angle FOVxThe field angle coverage distance S can be calculated according to the modeling precision Q. h isviewThe camera position height to meet the accuracy requirement.
The above calculation method is an acquisition point planning method for a plane. Then, the position of the acquisition point on the cross-sectional curve is determined by expanding the curve to the curved surface as shown in fig. 13: p is a radical oft-3The pose calculation process of the acquisition point is as followst-3The point starts to reach B by the distance St-3Based on line segment At-3Bt-3Arranged perpendicular to the lineSegment and perpendicular distance is hviewPosition p oft-3. And A ist-2And At-3Is S x alpha, and then B is determinedt-2The position of (a). And determining the poses of all acquisition points by analogy in the method.
2. Interpolation between the strongly varying observation points: the above arranged poses ptAnd pt+1The viewing angle between them is very large, which is a very big threat to reconstruction. Therefore, after the positions are arranged, when the included angle sigma between main view lines is larger than 25 degrees or a specified degree, a plurality of transition acquisition points p 'are inserted between two visual angles't、p″t、p″′t(ii) a As shown in fig. 14.
Insertion of transition points: according to ptAnd pt+1Obtaining intersection points k of the main sight lines under the pose, defaulting to insert transition acquisition points with 10 degrees as insertion intervals and the number of the insertion points being N, enabling the main sight lines of the acquisition points to pass through the intersection points k, and setting the distance between the transition acquisition points and the intersection points k as hviewAnd determining the pose of the transition acquisition point.
In this embodiment, according to the above determination method for plane and curved surface acquisition points, after traversing all transverse and longitudinal routes, the result of acquiring pose visualization is shown in fig. 15. The pose of the acquisition point after the module planning is more accurate and is fit with the actual situation; the acquisition point is low in the low region and high in the higher building region.
Comparing the multi-view reconstruction results acquired by different planning modes at the same position, the method of the invention has better effect. Referring to fig. 16, the left image is before planning reconstruction, and the right image is after planning reconstruction; the reconstruction results of the bridge opening (16a), the roof (16b), the building wall (16c) and the road surface (16d) respectively show that the planned reconstruction results are better in shade, precision, texture detail and definition.
In this embodiment, an unmanned aerial vehicle photogrammetry acquisition planning system based on saliency calculation is provided, and the planning system is used for implementing the unmanned aerial vehicle photogrammetry acquisition planning method based on saliency calculation, and the acquisition planning system includes
An original DSM acquisition module; original DSM for obtaining survey area;
an elevation model generation module; the system comprises a model generator, a model acquisition module, a model generation module and a data processing module, wherein the model generator is used for extracting peak points of a measurement area based on significance calculation to generate a smooth earth surface elevation model;
a pose planning module; and planning the pose of the acquisition point based on the smooth earth surface elevation model.
Acquiring original DSMs of the measurement areas, transmitting the acquired information to an elevation model generation module, calculating peak points of the measurement areas by adopting a significance calculation mode according to the original DSMs by the elevation model generation module, generating a smooth earth surface elevation model according to the peak points of the measurement areas, and transmitting the generated smooth earth surface elevation model to a pose planning module; and the pose planning module plans the pose of the acquisition point according to the smooth earth surface elevation model.
In the embodiment, the acquisition planning method provided by the invention has a very wide application range, and can be applied to the fields of flight games, automatic driving, navigation software, BIM development, traffic simulation and the like.
When the unmanned aerial vehicle photogrammetry acquisition planning method based on significance calculation is applied to a flying game, the planning method can be used for planning a path where a player is about to fly, and can be used for reconstructing a three-dimensional scene in the field where the player flies in a virtual game, so that the generation speed and effect of game scene data are improved, and the player can have better experience.
When the unmanned aerial vehicle photogrammetry acquisition planning method based on saliency calculation provided by the invention is applied to automatic driving or navigation software, the planning method is utilized to plan the route of automatic driving or navigation, and the method can also be used for reconstructing a three-dimensional scene of an area of automatic driving or navigation, so that the automatic driving vehicle or the navigation software can calculate the best planned route with less calculation force and higher speed; the three-dimensional scene reconstructed by the method can be utilized to flexibly select a more optimal moving route and avoid roadblocks and congested routes; the automatic driving and the navigation are safer and more convenient.
When the unmanned aerial vehicle photogrammetry acquisition planning method based on significance calculation is applied to the fields of BIM simulation, traffic simulation and the like, the terrain and scene data acquired by the planning method can be butted with simulation software through programming, and a high-precision road network and building information model is established, so that the simulation effect is more intelligent and vivid, and the simulation result is more accurate.
By adopting the technical scheme disclosed by the invention, the following beneficial effects are obtained:
the invention discloses a method and a system for unmanned aerial vehicle photogrammetry acquisition planning based on significance calculation, wherein the method generates a ground surface model based on maximum significance calculation and linear interpolation, and performs acquisition point planning on the model, thereby improving the performance of unmanned aerial vehicle in data acquisition in a high fall area; the method solves the problem that the reconstruction precision and the flight safety conflict with each other, and can be used for generating a three-dimensional model of an international metropolitan city; the method has wide application range, can be used as a game scene material production tool, and improves the generation speed and effect of game scene data; as a production tool for automatic driving high-precision maps; the modeling tool is used for traffic simulation and BIM simulation high-definition scenes; as a tool for producing data of a city digital twin management bottom layer; the urban data acquisition planning module is used as an unmanned aerial vehicle aerial survey software urban data acquisition planning module.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and improvements can be made without departing from the principle of the present invention, and such modifications and improvements should also be considered within the scope of the present invention.

Claims (11)

1. An unmanned aerial vehicle photogrammetry acquisition planning method based on significance calculation is characterized in that: comprises the following steps of (a) carrying out,
s1, extracting peak points of the measuring area based on the significance calculation to generate a smooth earth surface elevation model;
and S2, planning the pose of the acquisition point based on the smooth earth surface elevation model.
2. The method of claim 1, wherein the method comprises: the step S1 specifically includes the following steps,
s11, calculating a peak point of the measuring area based on the significance according to the original DSM of the measuring area; DSM, a digital surface elevation model;
and S12, generating a smooth earth surface elevation model by utilizing a linear interpolation mode based on the peak points of the measurement areas.
3. The method of claim 2, wherein the method comprises: the original DSM of the survey area is obtained by the following procedure,
calculating the precision Q of the acquired reconstruction result according to the absolute altitude;
according to absolute altitude HSAFEImage overlapping rate alpha of acquisition point and horizontal field angle FOV of cameraxDetermining the distance D between two adjacent acquisition pointsview；
Arranging a route and acquisition points in the survey area according to the distance between the acquisition points;
acquiring an inclined pose of the acquisition point relative to a vertical visual angle pose according to the acquisition inclination angle;
constructing an original DSM for the survey area based on the tilt pose of the acquisition point relative to the vertical view pose.
4. The method of claim 3, wherein the method comprises: the specific way of arranging the flight path and the acquisition point in the survey area is,
arranging N number of flight paths in the horizontal direction of the survey area, arranging M number of flight paths in the vertical direction, and arranging K number of flight paths on each flight path with the distance of DviewCollection point of (1).
5. The method of claim 2, wherein the method comprises: the step S11 specifically includes the following contents,
defining the transverse direction and the longitudinal direction at will in an original DSM of a measuring area, constructing transverse waves and longitudinal waves according to point clouds intercepted in the transverse direction and the longitudinal direction, traversing all points in the transverse waves and the longitudinal waves, and acquiring a starting point, a middle point and an end point of each local maximum value;
and performing significance calculation on each local maximum to obtain a peak point of the measurement area, and generating a smooth earth surface elevation model.
6. The method of claim 5, wherein the method comprises: the specific process of obtaining the start point, the middle point and the end point of each local maximum is,
defining point clouds intercepted in any direction in an original DSM of a survey area as transverse waves, and point clouds intercepted in a direction vertical to the any direction as longitudinal waves; traverse all points x in shear and longitudinal wavesiIf the current point xiIs greater than the previous point xi-1And is larger than the latter point xi+1Then update the local maximum midpoint pmidStarting point pleftEnd point prightThe number m of local maximum values; and finally outputting the starting point, the middle point and the end point of each found local maximum value.
7. The method of claim 5, wherein the method comprises: the specific process of obtaining the peak point of the measured area by performing the significance calculation is,
performing significance calculation on each local maximum; respectively at the midpoint peak of the wave0Find a point from the peak midpoint peak0Starting, stopping when a point larger than the median is encountered, and taking the difference between the point and the peak as significance left on two sides of the current local maximummin、rightminTaking the minimum value of the significance of the left side and the right side as the significance promoters of the current local maximum value; finally, judging whether the wave crest is kept according to the significance threshold value; the intersection of the latitude and longitude peaks in the original DSM or the intersection of the peak weights is used as the peak point of the measurement region.
8. The method of claim 1, wherein the method comprises: the step S2 specifically includes the following contents,
s21, according to the smooth earth surface elevation model, acquiring the number of new air routes in the horizontal direction and the vertical direction and the distance D ' between adjacent new acquisition points on the new air routes by utilizing the image overlapping rate alpha ' in the air route distance calculation process 'viewArranging new routes and new acquisition points in the survey area according to the number of the new routes and the distance between the new acquisition points;
s22, FOV according to known camera horizontal field anglexAcquiring a field angle coverage distance S by the default overlapping rate alpha and the precision Q of the acquisition and reconstruction result;
and S23, sequentially determining the poses of all the new acquisition points according to the coverage distance S of the field angle.
9. The method of claim 3, wherein the method comprises: in step S23, specifically, the step,
from section At-3The point starts to reach B by the distance St-3Based on line segment At-3Bt-3Arranged perpendicular to the line segment and at a distance h from the perpendicularviewPosition p oft-3And A ist-2And At-3Is S x alpha, and then B is determinedt-2Determining the poses of all the new acquisition points by analogy in the method;
wherein A ist-3、Bt-3Respectively for the camera in position pt-3FOV of field angle of time cameraxFOV of elevation model of upper and lower sides and smooth earth surfacexAn intersection in the field angle direction; a. thet-3Is a lower side intersection point, Bt-3Are the upper intersection points and recur in turn.
10. The method of claim 9, wherein the method comprises: after the cameras are arranged according to the pose of the acquisition points, when the included angle between the main sight lines of two adjacent new acquisition points is greater than a preset degree, the cameras are in phaseA plurality of transitional acquisition points are inserted between the main sight lines of two adjacent new acquisition points; the insertion process of the transition acquisition points is that according to the pose ptAnd pt+1Obtaining intersection points k of the lower main sight lines, inserting transition acquisition points with the number of W according to a preset insertion interval, enabling the main sight lines of the transition acquisition points to pass through the intersection points k, and enabling the main sight lines to be h according to the distance between the transition acquisition points and the intersection points kviewAnd determining the pose of the transition acquisition point.
11. The utility model provides an unmanned aerial vehicle photogrammetry gathers planning system based on significance calculates which characterized in that: a planning system for implementing the method of planning for the acquisition of the photogrammetry based on unmanned aerial vehicle based on saliency calculation as claimed in any one of claims 1 to 10, the acquisition planning system comprising
An original DSM acquisition module; original DSM for obtaining survey area;
an elevation model generation module; the system comprises a model generator, a model acquisition module, a model generation module and a data processing module, wherein the model generator is used for extracting peak points of a measurement area based on significance calculation to generate a smooth earth surface elevation model;
a pose planning module; and planning the pose of the acquisition point based on the smooth earth surface elevation model.
CN202110435201.4A 2021-04-22 2021-04-22 Unmanned aerial vehicle photogrammetry acquisition planning method and system based on significance calculation Withdrawn CN113124824A (en)

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Cited By (3)

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CN114217618A (en) * 2021-12-14 2022-03-22 重庆富沛和科技有限公司 Method for performing automatic cruise within selected range in three-dimensional map
CN114481770A (en) * 2022-03-31 2022-05-13 中大检测(湖南)股份有限公司 Method and system for detecting flatness of highway bridge
CN114608527A (en) * 2022-03-08 2022-06-10 内蒙古银宏能源开发有限公司 D-InSAR and UAV photogrammetry fusion method based on coal mining surface subsidence characteristics

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114217618A (en) * 2021-12-14 2022-03-22 重庆富沛和科技有限公司 Method for performing automatic cruise within selected range in three-dimensional map
CN114217618B (en) * 2021-12-14 2024-04-16 重庆富沛和科技有限公司 Method for automatically cruising in selected range in three-dimensional map
CN114608527A (en) * 2022-03-08 2022-06-10 内蒙古银宏能源开发有限公司 D-InSAR and UAV photogrammetry fusion method based on coal mining surface subsidence characteristics
CN114608527B (en) * 2022-03-08 2024-03-26 内蒙古银宏能源开发有限公司 D-InSAR and UAV photogrammetry fusion method based on coal mining earth surface subsidence characteristics
CN114481770A (en) * 2022-03-31 2022-05-13 中大检测(湖南)股份有限公司 Method and system for detecting flatness of highway bridge

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