Generation graph matching evaluation method and system for XR shed

Abstract

The invention provides a generated graph matching evaluation method and system for an XR shed, and relates to the technical field of image processing. The system comprises an XR shed, a user information capture unit, a virtual scene simulation unit, a display content generation unit, a playing module division unit, a perspective image processing unit, an image matching evaluation unit and a playing module management unit. In cooperation with the method steps, user information is positioned and perspective image processing is performed in a targeted manner according to different positions and visual angles of users, so that a soft module processing image meeting the film watching experience of the users is obtained, whether the original soft module generation image is good or the effect of the soft module processing image is better is judged through the image matching evaluation unit, and the user experience is improved. And the soft module processing graph is controlled to be played and displayed, so that the film watching requirement of a user at a specific visual angle is met.

Description

Technical Field

[0001] The present invention relates to the field of image processing technology, and in particular to a generated graph matching evaluation method and system for an XR studio. Background Art

[0002] The XR tent is a new type of content display device. It looks like a box with one side opened, and there is a display wall / display screen inside the box for displaying content. Viewers can get an immersive viewing experience by standing at the opening.

[0003] Due to the special design of the XR studio, the content it displays is also different from traditional single-plane images. At some transition positions (such as corners and edges), image processing is required based on perspective relationships to make the image transition between different planes natural, smooth and reasonable.

[0004] Existing image processing usually uses manual frame-by-frame processing or image processing models for batch processing; among them, the manual frame-by-frame processing method can meet the visual needs of specific scenes, making it more adaptable and having better display effects, but the disadvantages are slow processing speed and high cost.

[0005] The use of image processing models can process images quickly and at low cost, and can continuously optimize the amount of generated drawings as the algorithm improves, which is the trend of future development; however, the disadvantage is that the use of fixed processing models has poor adaptability, and users often view the display content of the XR studio from different angles, positions, and heights, which makes the content after fixed optimization unable to adapt.

[0006] Therefore, it is necessary to provide a generated graph matching evaluation method and system for the XR studio to solve the technical problem that users watch the display content of the XR studio from different angles, positions, and heights, resulting in the inability to adapt to the fixed optimized content. Summary of the invention

[0007] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a generated graph matching evaluation method and system for an XR studio, aiming to solve the technical problem that fixed optimized content cannot adapt to different viewing needs of users.

[0008] To achieve the above objectives, this application proposes a generated graph matching evaluation system for an XR studio, comprising: XR studio, used for playing and displaying content through a playback module; wherein the playback module includes a hard module and a soft module; A user information capturing unit, used to capture user information in the viewing area in front of the XR studio; A virtual scene simulation unit, used to simulate virtual scenes of the XR studio and viewing area; A display content generation unit, used to generate a plane generation image that can be played by the XR studio according to the prepared display content; The playback module division unit is used to divide the plane generation graph into playback modules to obtain a hard module generation graph and a soft module generation graph; A perspective image processing unit, used for selecting and performing perspective image processing on the soft module generated image according to a target viewing angle to obtain a corresponding soft module processed image; An image matching evaluation unit is used to perform image matching evaluation on the soft module processing image to obtain a matching evaluation score; The playback module management unit is used to determine whether the XR studio plays and displays the soft module processing image based on the matching evaluation score.

[0009] As a further solution, the user information capture unit includes a personnel identification module, a behavior identification module and a spatial positioning module; wherein the personnel identification module is used to identify personnel in the viewing area; the behavior identification module is used to identify the behavior of personnel and mark the personnel with viewing behavior as users; the spatial positioning module is used to spatially locate the user's head position to obtain user positioning information.

[0010] As a further solution, the user information capturing unit further includes an eye movement capturing module; wherein the eye movement capturing module is used to capture the user's eye perspective to obtain the user's perspective information.

[0011] As a further solution, the virtual scene simulation unit includes a virtual space simulation module, a virtual XR studio simulation module and a virtual perspective simulation module; wherein the virtual space simulation module is used to provide a virtual simulation space, including a virtual viewing area and a virtual XR studio area; the virtual XR studio simulation module is used to perform XR studio simulation playback in the virtual simulation space, and the virtual perspective simulation module is used to perform virtual perspective simulation according to user information.

[0012] As a further solution, the virtual XR studio simulation module includes a virtual XR studio model and a virtual playback module; wherein, the virtual XR studio model is used to simulate the physical structure of the XR studio, and the virtual playback module includes a virtual hard module and a virtual soft module, and is placed in the virtual XR studio model according to the actual installation position.

[0013] On the other hand, the present invention further provides a generation graph matching evaluation method for an XR studio, which is applied to a generation graph matching evaluation system for an XR studio as described in any one of the above items, and comprises the following steps: Step 1: Obtain the prepared display content to generate a plane generation map that can be played in the XR studio, and generate a plane generation map that can be played in the XR studio through a display content generation unit; Step 2: The playback module division unit divides the plane generation graph into playback modules to obtain corresponding hard module generation graphs and soft module generation graphs; Step 3: Capture user information in the viewing area in front of the XR studio through a user information capture unit; Step 4: The perspective image processing unit selects the target field of view according to the preset selection logic and in combination with the user information; Step 5: The perspective image processing unit performs perspective image processing on the soft module generated image according to the target viewing angle to obtain a corresponding soft module processed image; Step 6: Perform virtual scene simulation on the XR studio and viewing area through the virtual scene simulation unit; Step 7: The image matching evaluation unit performs image matching evaluation on the soft module processing image in the virtual scene simulation to obtain a matching evaluation score; Step 8: The playback module management unit determines whether the matching evaluation score is greater than the replacement threshold; If yes, the XR studio is controlled to play and display the hard module generation diagram and the soft module processing diagram; If not, the XR studio is controlled to play and display the hard module generation image and the soft module generation image; Step 9: Repeat steps 1 to 8 until the XR studio completes the playback display.

[0014] As a further solution, the image matching evaluation unit performs image matching evaluation through the following steps: Obtain the target perspective and the soft module generation diagram and soft module processing diagram that need to be evaluated; Controlling the virtual perspective simulation module to perform virtual perspective simulation according to the target perspective; The image generated by the soft module is simulated and played through the virtual XR studio simulation module, and the virtual perspective image at this time is obtained through the virtual perspective simulation module to obtain the original perspective image; The soft module processing diagram is simulated and played through the virtual XR studio simulation module, and the virtual perspective image at this time is obtained through the virtual perspective simulation module to obtain the processing perspective diagram; Evaluate the deformation degree of the original view image relative to the image generated by the soft module to obtain the deformation parameters of the original image; Evaluate the deformation degree of the processed view graph relative to the graph generated by the soft module, and obtain the processed graph deformation parameters; By changing the parameters of the original image and the processed image, the matching evaluation score of the corresponding soft module processed image under the target perspective is obtained.

[0015] As a further solution, when the user is a single user, preset the selection logic: If there is a specified annotation perspective, the specified annotation perspective will be used as the target perspective; Otherwise, the viewing angle position is determined by the user positioning information of a single user. If an eye-movement capture module is provided, the user perspective information of a single user is used as the target perspective; If the eye-tracking module is not set, the default horizontal viewing angle is used as the target viewing angle.

[0016] As a further solution, when the user is multiple users, preset the selection logic: Obtain user location information and user perspective information of each user; The spatial position is averaged through the user positioning information to obtain the public positioning information; The spatial angle is averaged through the user's perspective information to obtain the public perspective information; The viewpoint position is determined through the public positioning information, and the public viewpoint information is used as the target viewpoint.

[0017] As a further solution, when there are multiple users, gaze selection logic is also set: Obtain user location information and user perspective information of each user; Determine the playback module that each user is looking at based on the user location information and the user viewing angle information; Divide users who are looking at the same software module into the same group; The spatial position is averaged through the positioning information of users in the same group to obtain the mass positioning information of the same group; The spatial angle is averaged through the user perspective information of the same group to obtain the public perspective information of the same group; Determine the viewpoint position through the mass positioning information of the same group, and use the mass viewpoint information of the same group as the target viewpoint of the same group; Each soft module replaces the target perspective separately according to the corresponding target perspective of the same group, and loops through steps 1 to 8 respectively until the XR studio completes the playback display.

[0018] Compared with related technologies, the method and system for generating image matching evaluation for XR studios provided by the present invention have the following advantages: The present invention locates user information and performs perspective image processing in a targeted manner according to the user's position and viewing angle, thereby obtaining a soft module processing image that satisfies the user's viewing experience, and then uses an image matching evaluation unit to determine whether the original soft module generated image or the soft module processed image has a better effect, and then controls the soft module processed image to be played and displayed, thereby meeting the user's viewing needs from a specific viewing angle. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0021] Figure 1 A schematic diagram of the structure of a generated graph matching evaluation system for an XR shed provided by the present invention; Figure 2 A schematic diagram of the structure of the playback module provided by the present invention; Figure 3 A scene schematic diagram of a virtual scene simulation unit provided by the present invention; Figure 4 A schematic diagram of a scene in the front viewing area of ​​the XR studio provided by the present invention; Figure 5 A schematic diagram of the steps of a generation graph matching evaluation method for an XR studio provided by the present invention.

[0022] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0024] Example 1 See also Figure 1 , the embodiment of the present application provides a generation graph matching evaluation system for an XR studio, including: XR studio, used for playing and displaying content through a playback module; wherein the playback module includes a hard module and a soft module; A user information capturing unit, used to capture user information in the viewing area in front of the XR studio; A virtual scene simulation unit, used to simulate virtual scenes of the XR studio and viewing area; A display content generation unit, used to generate a plane generation image that can be played by the XR studio according to the prepared display content; The playback module division unit is used to divide the plane generation graph into playback modules to obtain a hard module generation graph and a soft module generation graph; A perspective image processing unit, used for selecting and performing perspective image processing on the soft module generated image according to a target viewing angle to obtain a corresponding soft module processed image; An image matching evaluation unit is used to perform image matching evaluation on the soft module processing image to obtain a matching evaluation score; The playback module management unit is used to determine whether the XR studio plays and displays the soft module processing image based on the matching evaluation score.

[0025] It should be noted that: Figure 2 As shown in the figure, a hard module refers to a playback module that does not need to be bent or deformed. This module can directly play the desired material without considering the deformation problem. A soft module is a playback module that is bent or deformed at the edge or diagonal. Since the soft module has certain deformation and bending, etc., when the image content is directly displayed, there will be certain deformation, which will affect the user's viewing experience. Existing XR studios often do not distinguish between soft modules and hard modules. Even if the deformation and bending of the soft modules are processed, perspective transformation is performed through a fixed perspective to offset the impact of the deformation and bending. This can only provide a better viewing experience at a fixed perspective and cannot meet the viewing needs of users with different perspectives.

[0026] To this end, this embodiment locates the user information and performs targeted perspective image processing according to the user's position and viewing angle, so as to obtain a soft module processing image that satisfies the user's viewing experience, and then uses the image matching evaluation unit to determine whether the original soft module generated image or the soft module processed image has a better effect, and then controls the soft module processed image to play and display, thereby meeting the user's viewing needs from a specific perspective.

[0027] Specifically, the user information capture unit includes a person identification module, a behavior identification module and a space positioning module; Figure 4 As shown in the figure, we will use the personnel recognition module to identify the people in the viewing area, and then use the behavior recognition module to identify the people's behavior, and mark the people with viewing behavior as users (because some people are not watching, such as passers-by, security personnel, etc.). Finally, the spatial positioning module will spatially locate the user's head position to obtain the user positioning information.

[0028] In addition, in some demanding scenarios, we also set up an eye-tracking module, through which we can not only accurately obtain the user's perspective, but also further locate the playback module they are watching ( Figure 4 The red box part is the soft module that is positioned according to the user's perspective), and then performs more targeted perspective transformation processing.

[0029] Among them, the prepared display content can be 3D scene materials and 2D static materials prepared in advance, or it can be materials generated based on AI, such as Wensheng pictures, etc. The display content is not limited here.

[0030] The virtual scene simulation unit is mainly set up to simulate the real scene, so as to extract the relevant information we want in the simulation scene. It mainly includes a virtual space simulation module, a virtual XR studio simulation module and a virtual perspective simulation module; wherein, the virtual space simulation module is used to provide a virtual simulation space, including a virtual viewing area and a virtual XR studio area; the virtual XR studio simulation module is used to perform XR studio simulation playback in the virtual simulation space, and the virtual perspective simulation module is used to perform virtual perspective simulation according to user information.

[0031] like Figure 3 As shown, the virtual XR studio simulation module includes a virtual XR studio model and a virtual playback module; wherein, the virtual XR studio model is used to simulate the physical structure of the XR studio, and the virtual playback module includes a virtual hard module and a virtual soft module, and is placed in the virtual XR studio model according to the actual installation position.

[0032] Through the cooperation of the virtual XR studio model and the virtual playback module, we can accurately obtain the display effect of the image in the virtual scene, and further provide data basis for subsequent judgments.

[0033] Example 2 See also Figure 5 Based on Example 1, this embodiment provides a generation graph matching evaluation method for an XR studio, comprising the following steps: Step 1: Obtain the prepared display content to generate a plane generation map that can be played in the XR studio, and generate a plane generation map that can be played in the XR studio through a display content generation unit; Step 2: The playback module division unit divides the plane generation graph into playback modules to obtain corresponding hard module generation graphs and soft module generation graphs; Step 3: Capture user information in the viewing area in front of the XR studio through a user information capture unit; Step 4: The perspective image processing unit selects the target field of view according to the preset selection logic and in combination with the user information; Step 5: The perspective image processing unit performs perspective image processing on the soft module generated image according to the target viewing angle to obtain a corresponding soft module processed image; Step 6: Perform virtual scene simulation on the XR studio and viewing area through the virtual scene simulation unit; Step 7: The image matching evaluation unit performs image matching evaluation on the soft module processing image in the virtual scene simulation to obtain a matching evaluation score; Step 8: The playback module management unit determines whether the matching evaluation score is greater than the replacement threshold; If yes, the XR studio is controlled to play and display the hard module generation diagram and the soft module processing diagram; If not, the XR studio is controlled to play and display the hard module generation image and the soft module generation image; Step 9: Repeat steps 1 to 8 until the XR studio completes the playback display.

[0034] Furthermore, the image matching evaluation unit needs to evaluate the image generated by the software module and the image processed by the software module to determine which one better matches the user's viewing needs, that is, which image is closer to the original viewing content from the user's perspective. The specific execution is through the following steps: Obtain the target perspective and the soft module generation diagram and soft module processing diagram that need to be evaluated; Controlling the virtual perspective simulation module to perform virtual perspective simulation according to the target perspective; Here, we use the virtual XR studio simulation module to simulate and play the image generated by the soft module, and use the virtual perspective simulation module to obtain the virtual perspective image at this time to obtain the original perspective image. This original perspective image is the image seen by the user without processing; Then we simulate and play the soft module processing image through the virtual XR studio simulation module, and obtain the virtual perspective image at this time through the virtual perspective simulation module to obtain the processing perspective image. This processing perspective image is the image seen from the user's perspective during processing; Evaluate the deformation degree of the original view image relative to the image generated by the soft module to obtain the deformation parameters of the original image; Evaluate the deformation degree of the processed view graph relative to the graph generated by the soft module, and obtain the processed graph deformation parameters; The degree of deformation here can be selectively set according to different focuses. If we focus on content similarity, we use a pixel-based metric to directly compare the pixel value differences of the image before and after deformation. The parameters can be as follows: MSE (Mean Squared Error) Calculate the mean square error of the pixel values ​​of the two images. The smaller the value, the smaller the difference after deformation.

[0035] Mean Absolute Error (MAE) Calculates the absolute mean of pixel value differences, which is more robust to outliers than MSE.

[0036] Peak Signal-to-Noise Ratio (PSNR) The logarithmic index based on MSE is often used to evaluate the quality of image compression or reconstruction.

[0037] In some scenarios that focus more on structural relevance (such as building display), it is necessary to measure the degree of structural information retention of the image content, which can be the following parameters: Structural Similarity Index (SSIM) The integrated brightness, contrast and structure information is more in line with human visual perception.

[0038] Multi-Scale SSIM (MS-SSIM) SSIM is calculated at multiple scales to enhance robustness to complex deformations.

[0039] In some scenarios that focus on geometric relationships (such as vehicle mechanics simulation diagrams), it is suitable for analyzing the geometric deformation of images (such as affine transformation and elastic deformation), such as: Displacement Field Describes the displacement vector of each pixel, often used in non-rigid registration (such as medical imaging).

[0040] Jacobian Determinant Analyze the volume change of the local area (determinant > 1 means expansion, < 1 means contraction).

[0041] Strain Tensor Describes the degree of tension or shear in local deformation (such as Green-Lagrange strain in engineering mechanics).

[0042] Curvature Used to analyze changes in the curvature of a surface or contour.

[0043] After we selected the appropriate parameters for measurement, we obtained the matching evaluation score of the corresponding soft module processed image under the target perspective by changing the parameters of the original image - the processed image. If the score (positive) exceeds the replacement threshold, it means that the processed soft module processed image better meets the viewing needs of the current perspective and is replaced.

[0044] Furthermore, when the user is a single user, the selection logic is preset: If there is a specified annotation perspective, the specified annotation perspective will be used as the target perspective; Otherwise, the viewing angle position is determined by the user positioning information of a single user. If an eye-movement capture module is provided, the user perspective information of a single user is used as the target perspective; If the eye-tracking module is not set, the default horizontal viewing angle is used as the target viewing angle.

[0045] Furthermore, when the user is multiple users, the selection logic is preset: Obtain user location information and user perspective information of each user; The spatial position is averaged through the user positioning information to obtain the public positioning information; The spatial angle is averaged through the user's perspective information to obtain the public perspective information; The viewpoint position is determined through the public positioning information, and the public viewpoint information is used as the target viewpoint.

[0046] When there are multiple users and an eye-tracking capture module is set, we can obtain the soft modules that each user is looking at. Different soft modules use different target perspectives to meet the viewing needs of different users at the same time, such as Figure 4 As shown in the figure, the user wearing hoodie No. 1 is looking at the ceiling; therefore, the corresponding soft module of the ceiling is adapted according to the user's perspective; similarly, another user is looking at the soft module on the right, and the soft module is also adapted according to the other user's perspective; the specific logic of the attention selection is: Obtain user location information and user perspective information of each user; Determine the playback module that each user is looking at based on the user location information and the user viewing angle information; Divide users who are looking at the same software module into the same group; The spatial position is averaged through the positioning information of users in the same group to obtain the mass positioning information of the same group; The spatial angle is averaged through the user perspective information of the same group to obtain the public perspective information of the same group; Determine the viewpoint position through the mass positioning information of the same group, and use the mass viewpoint information of the same group as the target viewpoint of the same group; Each soft module replaces the target perspective separately according to the corresponding target perspective of the same group, and loops through steps 1 to 8 respectively until the XR studio completes the playback display.

[0047] This solution can further subdivide different soft modules to further meet the different viewing needs of different users, different perspectives, and different viewing areas.

[0048] The above are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect application in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A generated graph matching evaluation system for XR studio, characterized in that: include: XR studio, used for playing and displaying content through a playback module; wherein the playback module includes a hard module and a soft module; A user information capturing unit, used to capture user information in the viewing area in front of the XR studio; A virtual scene simulation unit, used to simulate virtual scenes of the XR studio and viewing area; A display content generation unit, used to generate a plane generation image that can be played by the XR studio according to the prepared display content; The playback module division unit is used to divide the plane generation graph into playback modules to obtain a hard module generation graph and a soft module generation graph; A perspective image processing unit, used for selecting and performing perspective image processing on the soft module generated image according to a target viewing angle to obtain a corresponding soft module processed image; An image matching evaluation unit is used to perform image matching evaluation on the soft module processing image to obtain a matching evaluation score; The playback module management unit is used to determine whether the XR studio plays and displays the soft module processing image based on the matching evaluation score.

2. The generated graph matching evaluation system for XR studio according to claim 1, characterized in that: The user information capture unit includes a personnel identification module, a behavior identification module and a spatial positioning module; wherein the personnel identification module is used to identify personnel in the viewing area; the behavior identification module is used to identify the behavior of personnel and mark the personnel with viewing behavior as users; the spatial positioning module is used to spatially locate the user's head position to obtain user positioning information.

3. The generated graph matching evaluation system for XR studio according to claim 2, characterized in that: The user information capturing unit further includes an eye movement capturing module; wherein the eye movement capturing module is used to capture the user's eye perspective to obtain user perspective information.

4. The generated graph matching evaluation system for XR studio according to claim 1, characterized in that: The virtual scene simulation unit includes a virtual space simulation module, a virtual XR studio simulation module and a virtual perspective simulation module; wherein the virtual space simulation module is used to provide a virtual simulation space, including a virtual viewing area and a virtual XR studio area; the virtual XR studio simulation module is used to perform XR studio simulation playback in the virtual simulation space, and the virtual perspective simulation module is used to perform virtual perspective simulation according to user information.

5. The generated graph matching evaluation system for XR studio according to claim 4, characterized in that: The virtual XR studio simulation module includes a virtual XR studio model and a virtual playback module; wherein the virtual XR studio model is used to simulate the physical structure of the XR studio, and the virtual playback module includes a virtual hard module and a virtual soft module, and is placed in the virtual XR studio model according to the actual installation position.

6. A generation graph matching evaluation method for an XR studio, applied to a generation graph matching evaluation system for an XR studio as claimed in any one of claims 1 to 5, characterized in that: The steps include: Step 1: Obtain the prepared display content to generate a plane generation map that can be played in the XR studio, and generate a plane generation map that can be played in the XR studio through a display content generation unit; Step 2: The playback module division unit divides the plane generation graph into playback modules to obtain corresponding hard module generation graphs and soft module generation graphs; Step 3: Capture user information in the viewing area in front of the XR studio through a user information capture unit; Step 4: The perspective image processing unit selects the target field of view according to the preset selection logic and in combination with the user information; Step 5: The perspective image processing unit performs perspective image processing on the soft module generated image according to the target viewing angle to obtain a corresponding soft module processed image; Step 6: Perform virtual scene simulation on the XR studio and viewing area through the virtual scene simulation unit; Step 7: The image matching evaluation unit performs image matching evaluation on the soft module processing image in the virtual scene simulation to obtain a matching evaluation score; Step 8: The playback module management unit determines whether the matching evaluation score is greater than the replacement threshold; If yes, the XR studio is controlled to play and display the hard module generation diagram and the soft module processing diagram; If not, the XR studio is controlled to play and display the hard module generation image and the soft module generation image; Step 9: Repeat steps 1 to 8 until the XR studio completes the playback display.

7. The generation graph matching evaluation method for an XR studio according to claim 6, characterized in that: The image matching evaluation unit performs image matching evaluation through the following steps: Obtain the target perspective and the soft module generation diagram and soft module processing diagram that need to be evaluated; Controlling the virtual perspective simulation module to perform virtual perspective simulation according to the target perspective; The image generated by the soft module is simulated and played through the virtual XR studio simulation module, and the virtual perspective image at this time is obtained through the virtual perspective simulation module to obtain the original perspective image; The soft module processing diagram is simulated and played through the virtual XR studio simulation module, and the virtual perspective image at this time is obtained through the virtual perspective simulation module to obtain the processing perspective diagram; Evaluate the deformation degree of the original view image relative to the image generated by the soft module to obtain the deformation parameters of the original image; Evaluate the deformation degree of the processed view graph relative to the graph generated by the soft module, and obtain the processed graph deformation parameters; By changing the parameters of the original image and the processed image, the matching evaluation score of the corresponding soft module processed image under the target perspective is obtained.

8. The generation graph matching evaluation method for an XR studio according to claim 6, characterized in that: When the user is a single user, the default selection logic is: If there is a specified annotation perspective, the specified annotation perspective will be used as the target perspective; Otherwise, the viewing angle position is determined by the user positioning information of a single user. If an eye-movement capture module is provided, the user perspective information of a single user is used as the target perspective; If the eye-tracking module is not set, the default horizontal viewing angle is used as the target viewing angle.

9. The generation graph matching evaluation method for an XR studio according to claim 6, characterized in that: When the user is multiple users, the default selection logic is: Obtain user location information and user perspective information of each user; The spatial position is averaged through the user positioning information to obtain the public positioning information; The spatial angle is averaged through the user's perspective information to obtain the public perspective information; The viewpoint position is determined through the public positioning information, and the public viewpoint information is used as the target viewpoint.

10. The generation graph matching evaluation method for an XR studio according to claim 9, characterized in that: When there are multiple users, gaze selection logic is also set: Obtain user location information and user perspective information of each user; Determine the playback module that each user is looking at based on the user location information and the user viewing angle information; Divide users who are looking at the same software module into the same group; The spatial position is averaged through the positioning information of users in the same group to obtain the mass positioning information of the same group; The spatial angle is averaged through the user perspective information of the same group to obtain the public perspective information of the same group; Determine the viewpoint position through the mass positioning information of the same group, and use the mass viewpoint information of the same group as the target viewpoint of the same group; Each soft module replaces the target perspective separately according to the corresponding target perspective of the same group, and loops through steps 1 to 8 respectively until the XR studio completes the playback display.

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