A method and system for posture monitoring for aerial photography data collection

Abstract

The present application relates to the field of videography, and in particular to a posture monitoring method and system for aerial photography data acquisition, the method steps are: obtaining multiple frames of images acquired by aerial equipment in flight, and interpreting the images of adjacent frames, the interpretation method is: taking the edge of the target area of ​​the previous frame image as the edge of the window, using the window to traverse the subsequent frame image, setting a matching function, and taking the area corresponding to the maximum value of the matching function as the target area of ​​the subsequent frame image; calculating the deviation coefficient of the target area at each moment, when the deviation coefficient is less than a preset threshold, the interpretation fails and the image at the corresponding moment is deleted, and when consecutive preset frame images all fail to be interpreted, the shooting is stopped and the flight is returned. The present application has the effect of real-time monitoring whether the photo data collected by the aerial equipment has a large deviation due to the change of the aerial equipment's posture.

Description

Technical Field

[0001] The present application relates to the field of videography, and in particular to a posture monitoring method and system for aerial photography data collection. Background Art

[0002] Aerial photogrammetry data refers to surface image data obtained through aerial photography. These data are usually used to make maps, topographic maps, 3D models and other Geographic Information System (GIS) related applications. Flight attitude usually refers to the relative position and orientation of the aircraft in the air. Flight attitude can be measured by various sensors (such as gyroscopes, accelerometers, magnetometers, etc.) and adjusted by the flight control system.

[0003] In the prior art, the change of flight attitude is an important factor affecting the quality of aerial images taken by aviation equipment. Abnormal changes in flight attitude are mainly due to the ambient wind speed. For example, a sudden strong side wind during flight will cause the image to deviate from the original shooting target, affecting the effect of the aerial image. And when the aircraft is turning, if the turn is too large, the flight attitude of the aircraft will change, thereby affecting the captured image and causing image distortion. Therefore, how to judge whether the collected photo data has a large deviation due to the change of the attitude of the aviation equipment during the flight has become an urgent problem to be solved. Summary of the invention

[0004] In order to solve the above technical problems, the present application provides a posture monitoring method and system for aerial photography data collection.

[0005] In a first aspect, the present application provides a posture monitoring method for aerial photography data collection, which adopts the following technical solution:

[0006] A posture monitoring method for aerial photography data collection includes the following steps: obtaining multiple frames of images collected by an aerial device in flight, and interpreting images of adjacent frames, wherein the interpretation method is: taking the edge of a target area of ​​a previous frame image as the edge of a window, using the window to traverse a subsequent frame image, setting a matching function, and taking an area corresponding to a maximum value of the matching function as a target area of ​​a subsequent frame image; calculating a deviation coefficient of the target area at each moment, and when the deviation coefficient is less than a preset threshold, the interpretation fails and the image at the corresponding moment is deleted; when consecutive preset frame images all fail to be interpreted, shooting is stopped and the flight is returned; the expression of the deviation coefficient is:

[0007] ,in, represents the coefficient of deviation, express The first vector composed of the geometric centers of the target area of ​​the previous frame image and the target area of ​​the next frame image at the time instant, express The second vector is composed of the coordinates of the aviation equipment when the previous frame image is collected and the coordinates of the aviation equipment when the next frame image is collected. Indicates the time difference between the previous frame image and the next frame image. express The flight speed of the aircraft at the moment, For the The rotation angle of the aviation equipment at the moment, for Time has come At the moment, the displacement of the aviation equipment on the horizontal plane in the direction perpendicular to the flight direction, represents the hyperbolic tangent function, It indicates the degree of synchronization between the deviation of the aircraft and the change in the flight angle of the aircraft. Represents the cosine degree function.

[0008] Optionally, the expression for the matching function is:

[0009] ,in, represents the matching function, Indicates the number of pixels that overlap between the subsequent frame image and the previous frame image. Indicates the number of pixels in the target area in the previous frame image. Indicates the next frame image The horizontal coordinate of the pixel point, Indicates the next frame image The vertical coordinate of the pixel point, Indicates the first The horizontal coordinate of the pixel point, Indicates the first The vertical coordinate of the pixel point, Represents the total number of target pixels in the previous frame image. Indicates the next frame image The horizontal coordinate of the pixel point, Indicates the next frame image The vertical coordinate of the pixel point, Indicates the first The horizontal coordinate of the pixel point, Indicates the first The vertical coordinate of the pixel point, Indicates the total number of pixels in the target area.

[0010] Optionally, the expression for the matching function is:

[0011] ,in, represents the matching function, Indicates the number of pixels that overlap between the subsequent frame image and the previous frame image. Indicates the number of pixels in the target area in the previous frame image. Indicates the first The horizontal coordinate of the pixel point, Indicates the first The vertical coordinate of the pixel point, Indicates the first The horizontal coordinate of the pixel point, Indicates the first The vertical coordinate of the pixel point, Represents the total number of target pixels in the previous frame image. Indicates the first The horizontal coordinate of the pixel point, Indicates the first The vertical coordinate of the pixel point, Indicates the first The horizontal coordinate of the pixel point, Indicates the first The vertical coordinate of the pixel point, Indicates the total number of pixels in the target area.

[0012] Optionally, the method for setting the target area includes: determining a central rectangle; clustering the pixels within the central rectangle to obtain multiple clusters, each cluster corresponding to a connected domain, calculating the absolute difference between the mean value of the pixels in each connected domain and the mean value of the pixels in the central rectangle, and taking the connected domain corresponding to the maximum value of the absolute difference as the target area.

[0013] Optionally, the method for determining the center rectangle is: overlapping adjacent frame images in the historical data according to the SWIF algorithm, and calculating the overlap ratio of adjacent frame images in the historical data; taking the average of the overlap ratios of all adjacent frames as the area ratio of the center rectangle of the image, to obtain the area of ​​the center rectangle, and obtaining the length and width of the center rectangle according to the area and aspect ratio of the center rectangle, the aspect ratio of the center rectangle is the same as the aspect ratio of the image, and the geometric center of the center rectangle coincides with the geometric center of the image.

[0014] Optionally, a response function of the minimum reachable density of clustering and the minimum number of samples in the cluster is set, and clustering is performed according to the minimum reachable density distance and the minimum number of samples in the cluster corresponding to the maximum value of the response function; the expression of the response function is: ,in, represents the response function, represents the minimum number of samples in a cluster, Indicates the number of pixels in the center rectangle. represents the minimum achievable density distance, Represents the set of pixel values ​​within the central rectangle, max represents the maximum function, and min represents the minimum function.

[0015] Optionally, when consecutive preset frame images are all judged to be unread, the shooting is stopped and the flight is returned, and the shooting is repeated at the target point, where the target point is the position of the aviation equipment corresponding to the first frame image in the consecutive frame images that are judged to be unread.

[0016] In a second aspect, the present application provides a posture monitoring system for aerial photography data collection, which adopts the following technical solution:

[0017] A posture monitoring system for aerial photography data collection includes: a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the posture monitoring method for aerial photography data collection is implemented.

[0018] The beneficial effect is that the above-mentioned attitude monitoring method for aerial photography data collection is generated into a computer program and stored in a memory so as to be loaded and executed by a processor, thereby making a system based on the memory and the processor for easy use.

[0019] This application has the following technical effects:

[0020] 1. In the process of collecting images by the aerial equipment, the deviation coefficient of adjacent frame images is calculated. The deviation coefficient is a measure that combines the displacement of the target area, the displacement of the aerial equipment, the time difference, the flight speed and the rotation angle. It is used to determine whether the image has a large deviation due to the change of the attitude of the aerial equipment. If the deviation coefficient exceeds the preset threshold, it indicates that the image quality does not meet the requirements and the image at the corresponding moment needs to be deleted.

[0021] 2. Real-time monitoring of the aviation equipment during the flight determines whether the collected photo data has a large deviation due to the change of the aviation equipment's posture. If large deviations occur continuously, it means that the aviation equipment's posture is abnormal. Stop the current collection behavior and return to the starting position where the continuous abnormality occurs to re-shoot. Compared with interpreting and re-collecting photos after the flight is completed, this improves efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] By reading the detailed description below with reference to the accompanying drawings, the above and other purposes, features and advantages of the exemplary embodiments of the present application will become easily understood. In the accompanying drawings, several embodiments of the present application are shown in an exemplary and non-restrictive manner, and the same or corresponding numbers represent the same or corresponding parts.

[0023] Figure 1It is a flow chart of a method for photo interpretation in a posture monitoring method for aerial photography data collection according to an embodiment of the present application.

[0024] Figure 2 It is a method flow chart of setting a target area in a posture monitoring method for aerial photography data collection according to an embodiment of the present application. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0026] It should be understood that when the terms "first", "second", etc. are used in the claims, specification and drawings of the present application, they are only used to distinguish different objects, rather than to describe a specific order. The terms "include" and "comprise" used in the specification and claims of the present application indicate the presence of the described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or their collections.

[0027] An embodiment of the present application discloses a posture monitoring method for aerial photography data collection, which can monitor the aerial equipment in real time during flight to determine whether the collected photo data has large deviations due to changes in the aerial equipment's posture. If large deviations occur continuously, it means that the aerial equipment's posture is abnormal and the current collection behavior needs to be stopped.

[0028] Specifically, the method includes: obtaining multiple frames of images collected by the aviation equipment during flight, and interpreting the images of adjacent frames. When the consecutive preset frame images are all judged to be unsuccessful, the shooting is stopped and the aircraft returns to the destination.

[0029] In one embodiment, the aircraft can return to the target point for reshooting, the target point being the location of the aerial device corresponding to the first frame of the image that failed the continuous frame interpretation, and the reshooting route can be the planned route of the previous flight. The aerial device of the present application is a drone.

[0030] Reference Figure 2 The method for photo interpretation includes steps S1 and S2, which are as follows:

[0031] S1: Take the edge of the target area of ​​the previous frame image as the edge of the window, use the window to traverse the next frame image, set the matching function, and take the area corresponding to the maximum value of the matching function as the target area of ​​the next frame image.

[0032] Reference Figure 2 The method for setting the target area includes steps S10 and S11, which are as follows:

[0033] S10: Determine the center rectangle.

[0034] In one embodiment, adjacent frame images in the historical data are overlapped according to the SWIF algorithm, and the overlap ratio of adjacent frame images in the historical data is calculated. The average of the overlap ratios of all adjacent frames is used as the area ratio of the central rectangle of the image to obtain the area of ​​the central rectangle. According to the area and aspect ratio of the central rectangle, the length and width of the central rectangle are obtained. The aspect ratio of the central rectangle is the same as the aspect ratio of the image, and the geometric center of the central rectangle coincides with the geometric center of the image. The SWIF algorithm is a prior art and will not be described in detail here.

[0035] The overlap ratio refers to the ratio of the area of ​​the overlapping region of two adjacent frame images to the area of ​​each image in image processing. Since image A and image B are adjacent frames and have roughly the same area, the overlap ratio can be simplified to the ratio of the area of ​​the overlapping region to the area of ​​any image (image A or image B), thereby obtaining the area of ​​the central rectangle. In other embodiments, the area ratio of the central rectangle can be set by the user, such as 50%.

[0036] The length-to-width ratio of the center rectangle is the same as that of the image. If the image's length-to-width ratio is 2:1, then the length-to-width ratio of the center rectangle is 2:1. The length and width of the center rectangle are obtained based on the area of ​​the center rectangle and its length-to-width ratio. The length is calculated as the square root of the product of the area and the length-to-width ratio, and the width is calculated as the square root of the ratio of the area and the length-to-width ratio. Assuming the rectangle's length-to-width ratio is 2 and its area is 50 square centimeters, the length is 10 centimeters and the width is 5 centimeters.

[0037] When the aircraft is bumpy, pixels near the edge of the image may be missing. In order not to affect subsequent calculations, this application makes the geometric center of the central rectangle coincide with the geometric center of the image, so that the area of ​​the central rectangle is as close to the center of the image as possible.

[0038] S11: clustering the pixels in the central rectangle to obtain multiple clusters, each cluster corresponding to a connected domain, calculating the absolute difference between the mean value of the pixels in each connected domain and the mean value of the pixels in the central rectangle, and taking the connected domain corresponding to the maximum value of the absolute difference as the target area.

[0039] In one embodiment, the clustering algorithm adopts DBSCAN (Density-Based Spatial Clustering of Applications with Noise), sets a response function about the minimum reachable density of clustering and the minimum number of samples in the cluster, and performs clustering according to the minimum reachable density distance corresponding to the maximum value of the response function and the minimum number of samples in the cluster.

[0040] The expression of the response function is: ,in, represents the response function, represents the minimum number of samples in a cluster, Indicates the number of pixels in the center rectangle. represents the minimum achievable density distance, Represents the set of pixel values ​​within the central rectangle, max represents the maximum value function, and min represents the minimum value function.

[0041] The response function evaluates the effect of different clustering parameters by considering the number of samples in the cluster, the total number of pixels in the central rectangle, and the range of pixel values. The optimal clustering parameters can be determined by finding the parameter combination that maximizes the response function.

[0042] The minimum reachable density and the minimum number of samples in a cluster are clustering parameters. DBSCAN is an existing technology and will not be described here.

[0043] In one embodiment, the calculation formula of the matching function is:

[0044] ,in, represents the matching function, Indicates the number of pixels that overlap between the subsequent frame image and the previous frame image. Indicates the number of pixels in the target area in the previous frame image.

[0045] Indicates the first The horizontal coordinate of the pixel point, Indicates the first The vertical coordinate of the pixel point, Indicates the first The horizontal coordinate of the pixel point, Indicates the first The vertical coordinate of the pixel point, Indicates the total number of target pixels in the previous frame image.

[0046] Indicates the first The horizontal coordinate of the pixel point, Indicates the first The vertical coordinate of the pixel point, Indicates the first The horizontal coordinate of the pixel point, Indicates the first The vertical coordinate of the pixel point, Indicates the total number of pixels in the target area.

[0047] The matching function is used to evaluate the matching degree between adjacent frame images. The larger the value of the matching function, the higher the matching degree.

[0048] In one embodiment, the calculation formula of the matching function is:

[0049] ,in, represents the matching function, Indicates the number of pixels that overlap between the subsequent frame image and the previous frame image. Indicates the number of pixels in the target area in the previous frame image. Indicates the first The horizontal coordinate of the pixel point, Indicates the first The vertical coordinate of the pixel point, Indicates the first The horizontal coordinate of the pixel point, Indicates the first The vertical coordinate of the pixel point, Represents the total number of target pixels in the previous frame image. Indicates the first The horizontal coordinate of the pixel point, Indicates the first The vertical coordinate of the pixel point, Indicates the first The horizontal coordinate of the pixel point, Indicates the first The vertical coordinate of the pixel point, Indicates the total number of pixels in the target area.

[0050] For the calculation formula of the above matching function, the calculation method of the formula in the latter embodiment focuses more on the matching quality between each pixel point, and is suitable for scenes where the target area may change, while the formula in the former embodiment focuses more on the overall matching degree, and is suitable for scenes where the target is relatively stable. In practical applications, which formula to choose depends on the specific application requirements and the characteristics of the target area. If the target area does not change much, the former formula is simpler and more effective; if the target area changes greatly, the latter formula can better capture the subtle differences in matching quality.

[0051] S2: Calculate the deviation coefficient of the target area at each moment. When the deviation coefficient is less than the preset threshold, the image at the corresponding moment is deemed unread and deleted. When consecutive preset frame images are deemed unread, stop shooting and return.

[0052] The expression of the deviation coefficient is:

[0053] ,in, represents the coefficient of deviation, express The first vector composed of the geometric centers of the target area of ​​the previous frame image and the target area of ​​the next frame image at the time instant, express The second vector is composed of the coordinates of the aviation equipment when the previous frame image is collected and the coordinates of the aviation equipment when the next frame image is collected. Indicates the time difference between the previous frame image and the next frame image. express The flight speed of the aircraft at the moment, For the The rotation angle of the aviation equipment at the moment, for Time has come At the moment, the displacement of the aviation equipment on the horizontal plane in the direction perpendicular to the flight direction, represents the hyperbolic tangent function, It indicates the degree of synchronization between the deviation of the aircraft and the change in the flight angle of the aircraft. Represents the cosine degree function.

[0054] When the aircraft is in a vertical direction, there is no displacement of the aircraft in the direction perpendicular to the flight direction.

[0055] The difference between the displacement of the target area and the expected displacement of the aerial device (based on the speed and time difference) is calculated. The hyperbolic tangent function maps the input value between 0 and 1. If the actual displacement of the target area is very different from the expected displacement, it indicates a large deviation.

[0056] when At this time, the aviation equipment has displacement in the direction perpendicular to the flight direction, so it is necessary to consider the comprehensive displacement in the vertical and horizontal directions. The relationship between the deviation degree and the rotation angle of the aviation equipment was calculated. The larger the deviation coefficient is, the more out of sync the displacement of the target area is with the rotation angle of the aerial equipment; the larger the deviation coefficient is, the greater the degree of deviation is.

[0057] The deviation coefficient is a measure that combines the displacement of the target area, the displacement of the aircraft, the time difference, the flight speed and the rotation angle. It is used to determine whether the image has a large deviation due to the change of the attitude of the aircraft. If the deviation coefficient exceeds the preset threshold, it indicates that the image quality does not meet the requirements and the image at the corresponding moment needs to be deleted.

[0058] For example, the preset threshold value may be 0.1, the preset frame may be 30 frames, and when the deviation coefficient is less than 0.1, the image at the corresponding moment fails to be interpreted and the image is deleted, otherwise, the interpretation passes and the aircraft continues to fly. The values ​​of the preset threshold value and the preset frame can be adjusted according to the application scenario, which will not be elaborated here.

[0059] An embodiment of the present application also discloses a posture monitoring system for aerial photography data collection, including a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the posture monitoring method for aerial photography data collection according to the present application is implemented.

[0060] The above system also includes other components well known to those skilled in the art, such as a communication bus and a communication interface, and their configuration and functions are known in the art, so they will not be described in detail here.

[0061] In the present application, the aforementioned memory may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, apparatus, or device. For example, a computer-readable storage medium may be any appropriate magnetic storage medium or magneto-optical storage medium, such as a resistive random access memory RRAM (Resistive Random Access Memory), a dynamic random access memory DRAM (Dynamic Random Access Memory), a static random access memory SRAM (Static Random Access Memory), an enhanced dynamic random access memory EDRAM (Enhanced Dynamic Random Access Memory), a high bandwidth memory HBM (High Bandwidth Memory), a hybrid memory cube HMC (Hybrid Memory Cube), etc., or any other medium that can be used to store the required information and can be accessed by an application, a module, or both. Any such computer storage medium may be part of a device or accessible or connectable to a device.

[0062] Although this specification has shown and described a plurality of embodiments of the present application, it is obvious to those skilled in the art that such embodiments are provided by way of example only. Those skilled in the art will think of many changes, modifications and alternatives without departing from the thought and spirit of the present application. It should be understood that in the process of practicing the present application, various alternatives to the embodiments of the present application described herein may be adopted.

[0063] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A posture monitoring method for aerial photography data collection, characterized in that: The method comprises the following steps: obtaining multiple frames of images collected by the aviation equipment in flight, and interpreting the images of adjacent frames, wherein the interpretation method is: taking the edge of the target area of ​​the previous frame image as the edge of the window, using the window to traverse the subsequent frame image, setting a matching function, and taking the area corresponding to the maximum value of the matching function as the target area of ​​the subsequent frame image; Calculate the deviation coefficient of the target area at each moment. When the deviation coefficient is less than the preset threshold, the image at the corresponding moment is not judged to be passed and deleted. When consecutive preset frame images are not judged to be passed, stop shooting and return. The expression of the deviation coefficient is: ,in, represents the coefficient of deviation, express The first vector composed of the geometric centers of the target area of ​​the previous frame image and the target area of ​​the next frame image at the time instant, express The second vector is composed of the coordinates of the aviation equipment when the previous frame image is collected and the coordinates of the aviation equipment when the next frame image is collected. Indicates the time difference between the previous frame image and the next frame image. express The flight speed of the aircraft at the moment, For the The rotation angle of the aviation equipment at the moment, for Time has come At the moment, the displacement of the aviation equipment on the horizontal plane in the direction perpendicular to the flight direction, represents the hyperbolic tangent function, It indicates the degree of synchronization between the deviation of the aircraft and the change in the flight angle of the aircraft. Represents the cosine degree function.

2. The method for posture monitoring for aerial photography data collection according to claim 1, characterized in that: The expression for the matching function is: ,in, represents the matching function, Indicates the number of pixels that overlap between the subsequent frame image and the previous frame image. Indicates the number of pixels in the target area in the previous frame image. Indicates the next frame image The horizontal coordinate of the pixel point, Indicates the next frame image The vertical coordinate of the pixel point, Indicates the first The horizontal coordinate of the pixel point, Indicates the first The vertical coordinate of the pixel point, Represents the total number of target pixels in the previous frame image. Indicates the first The horizontal coordinate of the pixel point, Indicates the next frame image The vertical coordinate of the pixel point, Indicates the first The horizontal coordinate of the pixel point, Indicates the first The vertical coordinate of the pixel point, Indicates the total number of pixels in the target area.

3. The method for posture monitoring for aerial photography data collection according to claim 1, characterized in that: The expression for the matching function is: ,in, represents the matching function, Indicates the number of pixels that overlap between the subsequent frame image and the previous frame image. Indicates the number of pixels in the target area in the previous frame image. Indicates the next frame image The horizontal coordinate of the pixel point, Indicates the next frame image The vertical coordinate of the pixel point, Indicates the first The horizontal coordinate of the pixel point, Indicates the first The vertical coordinate of the pixel point, Represents the total number of target pixels in the previous frame image. Indicates the first The horizontal coordinate of the pixel point, Indicates the next frame image The vertical coordinate of the pixel point, Indicates the first The horizontal coordinate of the pixel point, Indicates the first The vertical coordinate of the pixel point, Indicates the total number of pixels in the target area.

4. The method for posture monitoring for aerial photography data collection according to any one of claims 1 to 3, characterized in that: The method for setting the target area includes: determining a central rectangle; clustering the pixels in the central rectangle to obtain multiple clusters, each cluster corresponding to a connected domain, calculating the absolute difference between the mean value of the pixels in each connected domain and the mean value of the pixels in the central rectangle, and taking the connected domain corresponding to the maximum value of the absolute difference as the target area.

5. The method for posture monitoring for aerial photography data collection according to claim 4, characterized in that: The method for determining the central rectangle is: overlapping adjacent frame images in the historical data is performed according to the SWIF algorithm, and the overlap ratio of adjacent frame images in the historical data is calculated; the average of the overlap ratios of all adjacent frames is used as the area ratio of the central rectangle of the image to obtain the area of ​​the central rectangle; according to the area and the aspect ratio of the central rectangle, the length and width of the central rectangle are obtained; the aspect ratio of the central rectangle is the same as that of the image, and the geometric center of the central rectangle coincides with the geometric center of the image.

6. The method for posture monitoring for aerial photography data collection according to claim 4, characterized in that: Set the response function of the minimum reachable density of clustering and the minimum number of samples in the cluster, and cluster according to the minimum reachable density distance and the minimum number of samples in the cluster corresponding to the maximum value of the response function; the expression of the response function is: ,in, represents the response function, represents the minimum number of samples in a cluster, Indicates the number of pixels in the center rectangle. represents the minimum achievable density distance, Represents the set of pixel values ​​within the central rectangle, max represents the maximum function, and min represents the minimum function.

7. The method for posture monitoring for aerial photography data collection according to claim 1, characterized in that: When all consecutive preset frame images are judged as unread, the shooting is stopped and the aircraft returns to the target point for reshooting. The target point is the position of the aviation equipment corresponding to the first frame image among the consecutive frames that fail to be judged.

8. A posture monitoring system for aerial photography data collection, characterized in that: include: A processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the attitude monitoring method for aerial photography data acquisition according to any one of claims 1 to 7 is implemented.

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