WO2023066412A1

WO2023066412A1 - Dynamic processing method and apparatus based on unmanned aerial vehicle video pyramid model

Info

Publication number: WO2023066412A1
Application number: PCT/CN2022/136213
Authority: WO
Inventors: 简洪登; 范湘涛; 杜小平
Original assignee: 中国科学院空天信息创新研究院
Priority date: 2022-08-17
Filing date: 2022-12-02
Publication date: 2023-04-27
Also published as: CN115065867B; CN115065867A

Abstract

The present disclosure relates to the field of video data real-time transmission and processing. Disclosed are a dynamic processing method and apparatus based on an unmanned aerial vehicle video pyramid model, which are used for solving the problems of the rendering efficiency of an unmanned aerial vehicle video being low, the system operation not being smooth, etc. The method comprises: constructing an unmanned aerial vehicle video pyramid model; and by using the unmanned aerial vehicle video pyramid model and according to a video loading request, performing resampling and segmentation by means of a video server, and performing dynamic scheduling and rendering, loading and displaying on a processed unmanned aerial vehicle video by means of a client. By means of the dynamic processing method for an unmanned aerial vehicle video provided in the present disclosure, unmanned aerial vehicle video data similar to the current map resolution can be dynamically loaded by using an unmanned aerial vehicle video pyramid model and according to a viewpoint distance and a field-of-vision range of the current scene view camera, such that high-performance on-demand rendering of a multi-resolution unmanned aerial vehicle video is realized, thereby ensuring the high efficiency of scene displaying and the smoothness of system operation.

Description

Dynamic processing method and device based on UAV video pyramid model

technical field

The present disclosure relates to the field of real-time transmission and processing of video data, and in particular to a dynamic processing method, device, electronic equipment and storage medium based on a UAV video pyramid model.

Background technique

During the real-time viewing of UAV video in the UAV image transmission system or other software, due to the influence of the large amount of UAV video data and the limited performance of computer hardware and software, the UAV video rendering efficiency is not high and the system Running is not smooth and other issues. Especially in the fusion process of UAV video and 2D and 3D geographic information system (Geographic Information System, GIS), there are many GIS scene elements, especially the 3D GIS scene contains such as high-precision terrain, images, real-scene 3D models, three-dimensional annotations, etc. Complex elements, the smooth operation of the system requires high scene rendering efficiency, the access and fusion of UAV video and ultra-high-definition (4K or higher resolution) UAV video into an efficient 2D and/or 3D GIS scene Rendering posed quite a challenge.

public content

According to a first aspect of the present disclosure, a dynamic processing method based on a UAV video pyramid model is provided, including:

Obtain the view point distance and field of view range of the scene view camera, query the current map level through the client, and obtain the current map resolution according to the correspondence between the map level and map resolution and the view point distance of the scene view camera;

According to the resolution of the current map, UAV flight parameters and preset grading rules, the UAV video pyramid model is constructed, wherein the UAV video pyramid model includes multiple levels, and the level of each UAV video pyramid model corresponds to a resolution;

Calculate the video range within the field of view of the scene view camera based on the field of view of the scene view camera and the video range of the drone;

Send the UAV video loading request to the video server through the client, wherein the UAV video loading request includes the attribute information of the UAV video pyramid model and the video range within the field of view of the scene view camera;

Resampling and segmenting the UAV video by the video server in response to the UAV video loading request through the client, and dynamically scheduling and rendering the processed UAV video on the client , load and display;

When the viewpoint distance of the scene view camera changes, repeat the above steps to resample, segment, dynamically schedule and render, load and display the UAV video according to preset requirements.

According to an embodiment of the present disclosure, the above preset classification rules are determined by formulas (1)-(3):

H _i =360×P _i (1),

Among them, W is the original width pixel value of the UAV video, H is the original height pixel value of the UAV video, P _i (i=1,2,3...) is the level of the UAV video pyramid model, H _i is the corresponding video height pixel value of the P _i -level UAV video pyramid model, W _i is the corresponding video width pixel value of the P _i- level UAV video pyramid model, R is the actual resolution of the UAV image, α is the vertical field of view of the drone, and Height is the current flying height of the drone.

According to an embodiment of the present disclosure, the attribute information of the UAV video pyramid model includes the level of the UAV video pyramid model and the resolution corresponding to the level;

Among them, the resolution of the UAV video pyramid model increases sequentially from the top to the bottom.

According to an embodiment of the present disclosure, the above-mentioned video server performs resampling and segmentation processing on the UAV video in response to the UAV video loading request including:

Determine the resolution and level of the drone video according to the drone video loading request;

According to the visual range coordinates of the scene view camera, using the resolution and level of the UAV video, determine the quadtree segmentation range of the UAV video pyramid model where the outsourcing rectangle of the visual range coordinates is located;

According to the quadtree segmentation range, the drone video is segmented through the video server, and the segmented drone video is sent to the client and/or browser for rendering.

According to an embodiment of the present disclosure, the above-mentioned dynamic scheduling and rendering of drone video according to preset requirements includes:

When the field of view of the scene view camera is smaller than the range of the current UAV video image, part of the UAV video data is loaded according to the location information of the scene view camera.

According to an embodiment of the present disclosure, the above-mentioned drone video pyramid model includes multiple resolutions of 360P, 720P, 1080P, 4K and 8K.

According to an embodiment of the present disclosure, the minimum map tile unit of the current map is 256×256 or 512×512 pixels.

According to a second aspect of the present disclosure, a dynamic processing device based on a UAV video pyramid model is provided, including:

The obtaining module is used to obtain the view point distance and field of view range of the scene view camera, query the level of the current map through the client, and obtain the current map according to the correspondence between the map level and map resolution and the view point distance of the scene view camera resolution;

The model construction module is used to construct the UAV video pyramid model on the video server according to the resolution of the current map, the UAV flight parameters and the preset classification rules, wherein the UAV video pyramid model includes multiple levels, each The level of the UAV video pyramid model corresponds to a resolution;

Calculation module, for calculating the video range in the field of view range of the scene view camera according to the field of view range of the scene view camera and the video range of the unmanned aerial vehicle;

The request sending module is used to send the UAV video loading request to the video server through the client, wherein the UAV video loading request includes the attribute information of the UAV video pyramid model and the video range within the field of view of the scene view camera ;

The video dynamic processing module is used to receive the UAV video after the video server responds to the UAV video loading request through the client to resample and segment the UAV video, and to process the UAV video in the The client performs dynamic scheduling and rendering, loading and display;

The video on-demand processing module is used to repeat the above steps when the viewpoint distance of the scene view camera changes, and resample, segment, dynamically schedule and render, load and display the UAV video according to preset requirements.

According to a third aspect of the present disclosure, an electronic device is provided, including:

one or more processors;

storage means for storing one or more programs,

Wherein, when the one or more programs are executed by the one or more processors, the one or more processors are made to execute the above multi-resolution UAV video dynamic processing method.

According to a fourth aspect of the present disclosure, there is provided a computer-readable storage medium, on which executable instructions are stored, and when the instructions are executed by a processor, the processor executes the above-mentioned multi-resolution drone video dynamic processing method.

The disclosure provides a multi-resolution UAV video dynamic processing method, which can dynamically load UAV video data similar to the current map resolution according to the viewpoint distance and field of view range of the current scene view camera to achieve multi-resolution High-performance on-demand rendering of UAV video ensures efficient scene display and smooth system operation.

Description of drawings

Fig. 1 is the flowchart of the dynamic processing method based on unmanned aerial vehicle video pyramid model according to the embodiment of the present disclosure;

Fig. 2 is a schematic structural diagram of a dynamic processing method based on a UAV video pyramid model according to an embodiment of the present disclosure;

3 is a schematic diagram of a general video format of a UAV video pyramid model according to an embodiment of the present disclosure;

4 is a schematic diagram of a 16:9 drone video format of a drone video pyramid model according to an embodiment of the present disclosure;

FIG. 5 is a flow chart of resampling and segmenting drone video according to an embodiment of the disclosure;

6 is a schematic diagram of quadtree segmentation of a UAV video pyramid model of the same level according to an embodiment of the present disclosure;

Fig. 7 is a schematic diagram of calculating a video range according to an embodiment of the disclosure;

8 is a schematic structural diagram of a dynamic processing system based on a UAV video pyramid model according to an embodiment of the present disclosure;

Fig. 9 schematically shows a block diagram of an electronic device adapted to implement a dynamic processing method based on a UAV video pyramid model according to an embodiment of the present disclosure.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present disclosure clearer, the present disclosure will be further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

FIG. 1 is a flowchart of a dynamic processing method based on a UAV video pyramid model according to an embodiment of the present disclosure.

As shown in FIG. 1 , the above dynamic processing method based on the UAV video pyramid model includes operation S110 to operation S160.

In operation S110, obtain the view point distance and view range of the scene view camera, query the level of the current map through the client, and obtain the current map level according to the correspondence between the map level and the map resolution and the view point distance of the scene view camera. resolution.

Optionally, the above-mentioned scene view camera can be a two-dimensional scene camera or a three-dimensional scene camera. Therefore, the above-mentioned UAV video dynamic processing method provided by the present disclosure can be applied to UAV video in a two-dimensional GIS scene Dynamic processing, also applicable to UAV video dynamic processing in 3D GIS scene

In operation S120, according to the resolution of the current map, the flight parameters of the drone, and the preset classification rules, a UAV video pyramid model is constructed, wherein the UAV video pyramid model includes multiple levels, and each of the UAVs The level of the video pyramid model corresponds to a resolution.

Optionally, the above-mentioned UAV video pyramid model can be constructed on the client or video server according to user requirements.

The UAV video pyramid model includes multiple levels (i.e. the levels of the pyramid model), and each level represents a video resolution; since the UAV video pyramid model can represent multiple resolutions, the above-mentioned unmanned aerial vehicles provided by this disclosure The UAV video dynamic processing method is capable of processing UAV video at multiple resolutions.

The above-mentioned flight parameters of the UAV include the flight height of the UAV and the vertical field of view of the UAV.

In operation S130, a video range within the view range of the scene view camera is calculated according to the view range of the scene view camera and the drone video range.

In operation S140, the client sends a UAV video loading request to the video server, wherein the UAV video loading request includes the attribute information of the UAV video pyramid model and the video range within the field of view of the scene view camera.

The attribute information of the pyramid model of the UAV video includes the level of the pyramid model and the resolution corresponding to the level.

In operation S150, the video server receives the UAV video after resampling and segmenting the UAV video in response to the UAV video loading request through the client, and performs the processing of the UAV video on the client. Dynamic scheduling and rendering, loading and displaying.

In operation S160, when the viewpoint distance of the scene view camera changes, the above steps are repeated, and the UAV video is resampled, segmented, dynamically scheduled and rendered, loaded and displayed according to preset requirements.

Fig. 2 is a schematic structural diagram of a dynamic processing method based on a UAV video pyramid model according to an embodiment of the present disclosure.

The multi-resolution drone video dynamic processing method provided by the present disclosure will be further described in detail below in conjunction with FIG. 2 .

Figure 2 shows that the client/browser side runs the UAV image transmission system to load and display the UAV video, the server side stores the UAV video data, and the UAV video pyramid model construction rules and methods. Use the client and/or browser to obtain the scene view camera viewpoint distance and field of view range, query the current map level, and obtain the current map resolution according to the currently commonly used map level and map resolution correspondence; according to the preset classification rules, no Calculate the level and resolution of the UAV video pyramid model based on the flight parameters of the man-machine and the resolution of the current map; and calculate the video range in the field of view according to the video range and field of view of the UAV; send a request to the video server to retrieve UAV video with the corresponding resolution; the server resamples and segments the UAV video according to the parameters in the UAV video request, such as grade, resolution, and video range, and returns the resampled UAV Video: Obtain the resampled UAV video in the 3D scene, load and display the UAV video; when the viewpoint of the 3D scene changes, repeat the above steps to perform multi-resolution UAV video on-demand scheduling and render.

It should be understood that the structural diagram shown in FIG. 2 is only schematic, and users can construct the UAV video pyramid model on the client side according to their own needs.

H _i =360×P _i (1),

The construction of the UAV video pyramid model is determined by formulas (1) to (3). From the above formulas, it can be concluded that the UAV video pyramid model provided by this disclosure has multiple levels and multiple resolutions, and can cover the video field Various commonly used video resolutions. Optionally, the user can determine the UAV video pyramid model with other video resolutions according to the above formula provided in the present disclosure according to their own needs.

According to an embodiment of the present disclosure, the above UAV video pyramid model includes multiple levels, and each level of the UAV video pyramid model corresponds to a resolution.

Wherein, the attribute information of the UAV video pyramid model includes the level of the UAV video pyramid model and the resolution corresponding to the level.

Fig. 3 is a schematic diagram of a general video format of a UAV video pyramid model according to an embodiment of the present disclosure.

4 is a schematic diagram of a 16:9 drone video format of a drone video pyramid model according to an embodiment of the disclosure.

The UAV video pyramid model provided by the present disclosure will be further described in detail below with reference to FIG. 3 and FIG. 4 .

Fig. 3 schematically shows the resolution of the unmanned aerial vehicle video pyramid model and the pyramid model at all levels, wherein, the resolution of the first level image 310 of the unmanned aerial vehicle video pyramid model is 360P, namely 360*W/H; The resolution of the second level image 320 of the UAV video pyramid model is 720P, i.e. 720*W/H; the resolution of the third level image 330 of the UAV video pyramid model is 1080P, i.e. 1080*W/H; The resolution of the sixth-level image 340 of the UAV video pyramid model is 4K, that is, 2160*W/H. Among them, the above W/H represents the ratio of the width and height of the drone video, for example, the ratio of width to height can be 1:1 or 16:9, and those skilled in the art should understand that Figure 3 is only schematic , those skilled in the art can build N (N is a positive integer) levels (such as P ₁ , P ₂ , P ₃ , P ₄ , P ₅ , P ₆ ... P _N ) UAV video pyramids according to actual needs Model. Considering that the smallest unit of a map tile in a 3D GIS system is usually 256×256 or 512×512 pixels, this disclosure builds a multi-resolution UAV video pyramid step by step based on 360P video, which can cover 720P, 1080P, 4K, 8K and other commonly used video resolutions. The correspondence between the multi-resolution UAV video pyramid level and the UAV video pixel height and width is shown in the above formulas (1) and (2).

H _i =360×P _i (1),

Fig. 4 shows 16: 9 (W/H, video width/video height) the UAV video pyramid model of UAV video format and the resolution of each level of pyramid model, wherein, the UAV video pyramid model's first The resolution of the first-level image 410 is 360P, i.e. 640×360; the resolution of the second-level image 420 of the UAV video pyramid model is 720P, i.e. 1280×720; the third-level image 430 of the UAV video pyramid model The resolution is 1080P, that is, 1920×1080; the resolution of the sixth-level image 440 of the UAV video pyramid model is 4K, that is, 3840×2160; Figure 4 is only schematic, and users can construct multiple Pyramid model in 16:9 video format for levels (eg P ₁ , P ₂ , P ₃ , P ₄ , P ₅ , P _{6 .} . . P _N ). As shown in Figure 4, for the 16:9 UAV video format, the UAV video width is determined by formula (4):

W _i =640×P _i (4).

Fig. 3 and Fig. 4 schematically show the structural diagram of the UAV video pyramid model according to the embodiment of the present disclosure. From Fig. 3 and Fig. 4, it can be seen without doubt that the UAV video dynamic processing provided by the present disclosure method, capable of processing UAV videos with different resolutions, and has a wide range of application scenarios. It should be particularly noted that although Figures 3 and 4 are schematic diagrams of 3D GIS scenes, the above-mentioned UAV video dynamic processing provided by this disclosure The method is also applicable to two-dimensional GIS scene. In addition, combined with the above pyramid model building process, users can build UAV video pyramid models with multiple other resolutions.

FIG. 5 is a flow chart of resampling and segmenting drone video according to an embodiment of the disclosure.

As shown in FIG. 5 , the video server resampling and segmenting the UAV video in response to the UAV video loading request includes operation S510 to operation S530 .

In operation S510, the resolution and grade of the drone video are determined according to the loading request of the drone video.

In operation S520, according to the visible range coordinates of the scene view camera, using the resolution and level of the drone video, determine the quadtree segmentation range of the drone video pyramid model where the outer rectangle of the visible range coordinates is located.

In operation S530, according to the quadtree segmentation range, the drone video is segmented by the video server, and the segmented drone video is sent to the client and/or the browser for rendering.

Those skilled in the art should understand that users are usually only interested in some drone videos, so it is not necessary to load and display all the drone videos in all the sight areas covered by the drone. , enabling the client to dynamically load or display UAV videos according to user needs. At the same time, because the UAV videos are segmented according to user needs, the pressure on dynamic scheduling and rendering of the client can be greatly reduced, so that UAV videos can be Faster loading and display improves user experience.

In the case that the field of view of the scene view camera is smaller than the range of the current UAV video image, part of the UAV video data is loaded according to the position information of the scene view camera, wherein the UAV video has multiple resolutions.

The above UAV video pyramid model provided by this disclosure samples and divides UAV videos step by step according to certain classification rules, taking into account the size of GIS map tiles, and can cover commonly used videos such as 720P, 1080P, 4K, 8K, etc. Resolution, it is possible to load multi-resolution UAV video on demand.

Fig. 6 is a schematic diagram of quadtree splitting of the UAV video pyramid model at the same level according to an embodiment of the present disclosure.

FIG. 7 is a schematic diagram of calculating a video range according to an embodiment of the disclosure.

The above-mentioned multi-resolution drone video dynamic processing method provided by the present disclosure will be further described in detail below with reference to FIGS. 6 and 7 .

For the UAV video of the same level in the UAV video pyramid model, it can be segmented according to the quadtree, as shown in Figures 6 and 7, which is convenient for small-scale video data to be loaded on demand, that is, when the scene When the field of view of the view camera is smaller than the current UAV image range, part of the video data can be loaded according to the scene camera position, thereby reducing the amount of video data and improving scene rendering efficiency. Figures 6 and 7 schematically show a schematic view of displaying part of the UAV video or segmenting the UAV video according to the user's needs according to the present disclosure, wherein those skilled in the art can use Figures 6 and 7 according to the user's needs The background of the drone is replaced by the drone video and/or the current map, which facilitates the dynamic processing of the drone video. Among them, in Figure 6, W _i represents the width of the UAV video corresponding to the i-th level of the UAV video pyramid model, and W _i /4 and W _i /2 represent 1/4 and 1/2 of the UAV video The width of the video; H _i represents the height of the UAV video corresponding to the i-th level of the UAV video pyramid model, and H _i /4 and H _i /2 represent the video of 1/4 and 1/2 of the UAV video high. Fig. 7 shows a schematic diagram of quadtree segmentation of UAV video according to an embodiment of the present disclosure, as shown in Fig. 7, wherein the gray part of Fig. 7 is to perform quadtree segmentation on target UAV video according to user requirements Segmentation results; for the video images segmented by the above quadtree, the client can dynamically schedule and render, load and display.

The 2D or 3D GIS scene will dynamically load different levels of terrain, image and map data according to the current viewpoint distance, so during the dynamic scheduling process of UAV video, UAVs with the same resolution can be dynamically requested according to the current map level video data. When the UAV video hardware remains unchanged, the UAV’s field of view and video size remain unchanged, and the actual resolution of the UAV’s image is related to its flight height, as shown in formula (3):

After determining the actual resolution and level of the current UAV video, according to the visual range coordinates of the scene view camera (scene view), calculate the video pyramid quadtree segmentation range where its outsourcing rectangle is located, and the server will follow this range Part of the video data is split and sent to the client for rendering.

In the process of loading and displaying the UAV video in the 2D or 3D scene of the UAV image transmission system, dynamically calculate the required UAV video resolution and the video in the current level according to the current viewpoint distance and field of view range Range, call low-resolution video at a long distance, call high-resolution video at a short distance, and call a small-scale video image in a small field of view, thereby reducing the pressure of 2D or 3D scene rendering and improving scene rendering performance.

Fig. 8 is a schematic structural diagram of a multi-resolution drone video dynamic processing device according to an embodiment of the present disclosure.

As shown in FIG. 8 , the multi-resolution UAV video dynamic processing system includes an acquisition module 810 , a model building module 820 , a calculation module 830 , a request sending module 840 , a video dynamic processing module 850 and a video on-demand processing module 860 .

Obtaining module 810, used to obtain the viewpoint distance and field of view range of the scene view camera, query the level of the current map through the client, and obtain the current the resolution of the map;

The model construction module 820 is used to construct the UAV video pyramid model according to the resolution of the current map, the flight parameters of the UAV and the preset grading rules, wherein the UAV video pyramid model includes multiple levels, each unmanned The level of the machine video pyramid model corresponds to a resolution;

Calculation module 830, for calculating the video range within the range of view of the scene view camera according to the range of view of the scene view camera and the video range of the drone;

The request sending module 840 is used to send a UAV video loading request to the video server through the client, wherein the UAV video loading request includes the attribute information of the UAV video pyramid model and the video within the field of view of the scene view camera scope;

The video dynamic processing module 850 is used to receive, through the client, the UAV video after the UAV video is resampled and segmented in response to the UAV video loading request by the video server, and the processed UAV video Perform dynamic scheduling and rendering, loading and display on the client side;

The video on-demand processing module 860 is used to repeat the above steps when the viewpoint distance of the scene view camera changes, and perform resampling, segmentation, dynamic scheduling and rendering, loading and display of the UAV video according to preset requirements .

The dynamic processing method and device based on the UAV video pyramid model provided by this disclosure can sample and segment the UAV video step by step according to certain classification rules, and at the same time develop a multi-resolution UAV video high-performance press Rendering methods and devices are required to dynamically load drone video data of different resolutions and ranges according to distance, so as to ensure the on-demand dynamic loading and display of drone videos, especially ultra-high-definition drone videos.

As shown in FIG. 9, an electronic device 900 according to an embodiment of the present disclosure includes a processor 901, which can be loaded into a random access memory (RAM) 903 according to a program stored in a read-only memory (ROM) 902 or from a storage section 908. Various appropriate actions and processing are performed by the program. The processor 901 may include, for example, a general-purpose microprocessor (eg, a CPU), an instruction set processor and/or related chipsets, and/or a special-purpose microprocessor (eg, an application-specific integrated circuit (ASIC)), and the like. Processor 901 may also include on-board memory for caching purposes. The processor 901 may include a single processing unit or multiple processing units for executing different actions of the method flow according to the embodiments of the present disclosure.

In the RAM 903, various programs and data necessary for the operation of the electronic device 900 are stored. The processor 901, ROM 902, and RAM 903 are connected to each other through a bus 904. The processor 901 executes various operations according to the method flow of the embodiment of the present disclosure by executing programs in the ROM 902 and/or RAM 903. It should be noted that the program can also be stored in one or more memories other than ROM 902 and RAM 903. The processor 901 may also perform various operations according to the method flow of the embodiments of the present disclosure by executing programs stored in the one or more memories.

According to an embodiment of the present disclosure, the electronic device 900 may further include an input/output (I/O) interface 905 which is also connected to the bus 904 . The electronic device 900 may also include one or more of the following components connected to the I/O interface 905: an input section 906 including a keyboard, a mouse, etc.; including a cathode ray tube (CRT), a liquid crystal display (LCD), etc. An output section 907 of a speaker or the like; a storage section 908 including a hard disk or the like; and a communication section 909 including a network interface card such as a LAN card, a modem, or the like. The communication section 909 performs communication processing via a network such as the Internet. A drive 910 is also connected to the I/O interface 905 as needed. A removable medium 911 such as a magnetic disk, optical disk, magneto-optical disk, semiconductor memory, etc. is mounted on the drive 910 as necessary so that a computer program read therefrom is installed into the storage section 908 as necessary.

The present disclosure also provides a computer-readable storage medium. The computer-readable storage medium may be included in the device/apparatus/system described in the above embodiments; it may also exist independently without being assembled into the device/system device/system. The above-mentioned computer-readable storage medium carries one or more programs, and when the above-mentioned one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, such as may include but not limited to: portable computer disk, hard disk, random access memory (RAM), read-only memory (ROM) , erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to an embodiment of the present disclosure, a computer-readable storage medium may include one or more memories other than the above-described ROM 902 and/or RAM 903 and/or ROM 902 and RAM 903.

Those skilled in the art can understand that various combinations and/or combinations of the features described in the various embodiments and/or claims of the present disclosure can be made, even if such combinations or combinations are not explicitly recorded in the present disclosure. In particular, without departing from the spirit and teaching of the present disclosure, the various embodiments of the present disclosure and/or the features described in the claims can be combined and/or combined in various ways. All such combinations and/or combinations fall within the scope of the present disclosure.

The specific embodiments described above have further described the purpose, technical solutions and beneficial effects of the present disclosure in detail. It should be understood that the above descriptions are only specific embodiments of the present disclosure, and are not intended to limit the present disclosure. Within the spirit and principles of the present disclosure, any modifications, equivalent replacements, improvements, etc., shall be included in the protection scope of the present disclosure.

Claims

A dynamic processing method based on the UAV video pyramid model, comprising:

Obtain the view point distance and view range of the scene view camera, query the level of the current map through the client, and obtain the view point distance of the scene view camera according to the correspondence between the map level and map resolution and the view point distance of the scene view camera. resolution;

According to the resolution of the current map, the flight parameters of the unmanned aerial vehicle and the preset classification rules, the unmanned aerial vehicle video pyramid model is constructed, wherein the unmanned aerial vehicle video pyramid model includes multiple levels, each of the unmanned aerial vehicles The level of the video pyramid model corresponds to a resolution;

calculating the video range within the field of view of the scene view camera according to the field of view of the scene view camera and the video range of the drone;

The UAV video loading request is sent to the video server by the client, wherein the UAV video loading request includes the attribute information of the UAV video pyramid model and the field of view of the scene view camera. video range;

Receive the UAV video after the UAV video is resampled and segmented by the video server in response to the UAV video loading request through the client, and process the UAV video in the The client performs dynamic scheduling and rendering, loading and displaying;

When the viewpoint distance of the scene view camera changes, the above steps are repeated, and the UAV video is resampled, segmented, dynamically scheduled and rendered, loaded and displayed according to preset requirements.
The method according to claim 1, wherein the preset classification rules are determined by formulas (1) to (3):

H i =360×P i (1),

Wherein, W is the original width pixel value of the UAV video, H is the original height pixel value of the UAV video, P i (i=1,2,3...) is the UAV video pyramid The level of the model, H i is the corresponding video height pixel value of the P i level UAV video pyramid model, W i is the corresponding video width pixel value of the P i level UAV video pyramid model, and R is unmanned The actual resolution of the drone image, α is the vertical field of view of the drone, and Height is the current flying height of the drone.
The method according to claim 1, wherein the attribute information of the unmanned aerial vehicle video pyramid model includes the level of the unmanned aerial vehicle video pyramid model and the resolution corresponding to the level;

Wherein, the resolution of the UAV video pyramid model increases sequentially from the top to the bottom.
The method according to claim 1, wherein the video server performs resampling and segmentation processing on the UAV video in response to the UAV video loading request comprising:

According to the UAV video loading request, determine the resolution and level of the UAV video;

According to the visible range coordinates of the scene view camera, using the resolution and level of the drone video, determine the quadtree segmentation range of the drone video pyramid model where the outer rectangle of the visible range coordinates is located ;

According to the quadtree segmentation range, the video server is used to segment the drone video, and the segmented drone video is sent to the client and/or browser for rendering.
The method according to claim 1, wherein said performing dynamic scheduling and rendering of said UAV video according to preset requirements comprises:

In the case that the field of view of the scene view camera is smaller than the range of the current UAV video image, part of the UAV video data is loaded according to the position information of the scene view camera.
The method according to claim 1, wherein the drone video pyramid model includes multiple resolutions of 360P, 720P, 1080P, 4K and 8K.
The method according to claim 1, wherein the minimum map tile unit of the current map is 256×256 or 512×512 pixels.
A dynamic processing device based on the UAV video pyramid model, comprising:

The obtaining module is used to obtain the viewpoint distance and the field of view range of the scene view camera, query the level of the current map through the client, and obtain the resolution of the current map;

A model construction module, configured to construct a UAV video pyramid model according to the resolution of the current map, UAV flight parameters and preset classification rules, wherein the UAV video pyramid model includes multiple levels, each The level of each described unmanned aerial vehicle video pyramid model corresponds to a resolution;

A calculation module, configured to calculate the video range within the field of view of the scene view camera according to the field of view of the scene view camera and the video range of the drone;

A request sending module, configured to send a UAV video loading request to a video server through the client, wherein the UAV video loading request includes attribute information of the UAV video pyramid model and the scene view camera The range of video within the field of view of ;

The video dynamic processing module is used to receive, through the client, the UAV video after the UAV video has been resampled and segmented by the video server in response to the UAV video loading request, and processed The UAV video is dynamically scheduled and rendered, loaded and displayed at the client;

The video on-demand processing module is used to repeat the above steps when the viewpoint distance of the scene view camera changes, and perform resampling, segmentation, dynamic scheduling and rendering of the drone video according to preset requirements, Load and display.
An electronic device comprising:

one or more processors;

storage means for storing one or more programs,

Wherein, when the one or more programs are executed by the one or more processors, the one or more processors are made to execute the method according to any one of claims 1-7.
A computer-readable storage medium, on which executable instructions are stored, and the instructions, when executed by a processor, cause the processor to perform the method according to any one of claims 1-7.