Indoor decoration design optimization method based on virtual reality

Abstract

The invention relates to the field of decoration design, and particularly discloses an indoor decoration design optimization method based on virtual reality, and the method comprises the steps: S1, obtaining a three-dimensional image of an indoor space structure, carrying out the deconstruction analysis of the three-dimensional image, and obtaining an indoor space element image; s2, dividing the indoor element image into different space element image areas by disassembling the indoor element image, setting different sensors to respectively identify contour information of the different space element image areas, and collecting a virtual contour image; s3, matching different virtual contour images according to indoor element information of the historical database, performing color filling, performing matching analysis according to a color filling result, and updating the historical database according to a matching analysis result; s4, using the updated historical database to realize a user indoor space remodeling system based on the virtual reality technology; according to the method, the accurate matching and synchronous updating process of the prediction virtual system and the real space element information is realized; and meanwhile, the immersive experience effect of the user is improved.

Description

Technical Field

[0001] This invention relates to the field of interior design, and more specifically to an optimization method for interior design based on virtual reality. Background Technology

[0002] Virtual reality (VR) technology represents a significant technological breakthrough in the 21st-century computer field. As a technology that integrates knowledge from multiple disciplines, including computer graphics principles, sensors, and optics, it aims to organically integrate the virtual and real worlds. Introducing VR technology into interior design offers significant advantages over traditional methods. It allows clients to realistically see the finished interior and largely replicates the final design. VR technology serves as a bridge between the virtual and real worlds, enabling the promotion and application of interior design while saving costs.

[0003] However, the current development of virtual technology has not considered the visual needs of designers and virtual experience users during the block division process. It only uses existing design templates to perform simple environmental simulation and visually maps environmental elements to create an impression. This results in the final virtual space and display matching not being precise enough, and the details are not handled well. It also ignores the problem of mismatch between the matching and synchronous prediction of virtual system and real element information, resulting in the inability to update the virtual data system in a timely manner. In addition, the lack of mature visual change design in the spatial visualization process of indoor space reshaping in the virtual environment makes the changes of visual points during user visual observation not flexible enough, affecting the user's immersive experience. Summary of the Invention

[0004] The purpose of this invention is to provide an interior design optimization method based on virtual reality, and to solve the following technical problems:

[0005] (1) How to predict the precise matching and synchronous update process of virtual system and real space element information;

[0006] (2) How to flexibly collect visual images based on the changes in visual points during the user's visual observation process, so as to achieve the effect of "changing scenery with each step" and thus improve the user's immersive experience.

[0007] The objective of this invention can be achieved through the following technical solutions:

[0008] A virtual reality-based method for optimizing interior design, the method comprising:

[0009] S1. Obtain a three-dimensional image of the interior space structure, and perform deconstruction analysis on the three-dimensional image to obtain images of interior space elements;

[0010] S2. By decomposing the indoor element images into different spatial element image regions, different sensors are set up to identify the contour information of different spatial element image regions and collect virtual contour images.

[0011] S3. Match different virtual contour images with indoor element information in the historical database and fill them with color. Perform matching analysis based on the color filling results and update the historical database based on the matching analysis results.

[0012] S4. Implement a user indoor space reshaping system based on virtual reality technology using an updated historical database.

[0013] Preferably, the color filling process is as follows:

[0014] S311. Set the RGB parameters of the unit pixels corresponding to different colors of different elements in the historical database.

[0015] S312. Based on the element information corresponding to the different virtual contour images identified by the machine recognition engine, compare them with the different element information of the indoor space in the historical database, and calculate the shape overlap.

[0016] S313. If the shape overlap is greater than the preset threshold, fill the corresponding virtual contour image with the RGB parameters of the pixel corresponding to the current color; if the shape overlap is less than the preset threshold, do not fill, perform grayscale processing on the current virtual contour image and extract the target element information.

[0017] S314. Obtain the number and area of ​​the grayscale processed virtual contour image and predict the number of color fills in the target element region.

[0018] Preferably, the prediction method for the number of color fills in the target element region is as follows:

[0019] SS1. Calculate the proportion P1 of the number of grayscale processed virtual contour images to the total number of indoor elements;

[0020] SS2, Calculate the ratio P2 of the area of ​​the grayscale processed virtual contour image to the total area of ​​indoor elements;

[0021] SS3, through formula Calculate the standard fill ratio coefficient P sy Where, P1≠P2≠0; β se This refers to the specific gravity parameter for indoor filling.

[0022] SS4, according to the standard filling ratio coefficient P sy Predict the number of color fills n in the target element region.

[0023] Preferably, the matching analysis process is as follows:

[0024] S321. Compare the number of target element colors filled (n) with a preset threshold:

[0025] If n is less than the preset threshold, the prediction result is determined to be without deviation, and the process continues.

[0026] If n is greater than the preset threshold, the prediction result is judged to have a deviation, and visual image matching is performed.

[0027] S322. Select the visual center point of different virtual contour images corresponding to the target element based on the visualization image matching results;

[0028] S323. Determine the intersection points of each POI based on the straight-line distance between the visual center point of different virtual contour images and the preset visual point at each time.

[0029] S323. Determine the degree of overlap between each POI intersection point and the preset POI intersection point: If the degree of overlap is greater than the preset threshold, update the historical database; otherwise, repeat step S322.

[0030] Preferably, the method for selecting the visual center point in step S322 is as follows:

[0031] Time periods [t1, t2, ..., t] are obtained using GIS positioning technology. n The curve S showing the change in the trajectory of the moving visual point. v ;

[0032] Get any time point t i The visual point mapping presets the curve S of the movement trajectory of the virtual object on the visual plane. pi ;

[0033] curve S v With curve S pi Correlation analysis is performed to obtain strong correlation coefficients. Based on the strong correlation coefficients, visual center point parameters are obtained through fitting, and the visual center points of different virtual contour images are determined.

[0034] Preferably, the indoor space reshaping system specifically includes:

[0035] The virtual scene generation unit is used to build, render, and manage virtual scene models;

[0036] Visual tracking devices are used to track changes in a user's gaze using various sensors, receivers, and virtual reality technology.

[0037] Displays are used to present signals formed by the fusion of virtual and reality;

[0038] Interactive devices for inputting and outputting signals for manipulation and sensory purposes in a real environment.

[0039] Preferably, the interactive device further includes scene roaming, which includes: automatic pathfinding roaming and interactive roaming;

[0040] The automatic pathfinding roaming allows users to tour an interior design simulation scene along a preset route;

[0041] The interactive roaming allows users to wear visual display devices and independently select routes, adjust directions and viewpoints to tour simulated interior design scenes.

[0042] The beneficial effects of this invention are:

[0043] (1) This invention matches different virtual contour images with indoor element information in historical database and fills them with color. It performs matching analysis based on the color filling results and updates the historical database based on the matching analysis results. Based on different virtual contour images, it fills the target area with color using image recognition technology. Then, it performs matching analysis based on the color filling results and updates the historical database based on the matching analysis results. This ensures the synchronous matching process between the historical database and the data in the display space, thereby improving the accuracy of building a database-based virtualization framework.

[0044] (2) This invention utilizes an updated historical database to realize a user indoor space reshaping system based on virtual reality technology; through the updated historical database, the space is visualized and analyzed to realize the connection between the user's vision and the virtual space, realize the refined construction of the indoor design scene, ensure the high matching effect between the constructed virtual scene and the real experience, so that the user can flexibly use the virtual scene for visual experience and design analysis, achieve the visual experience effect of "changing scenery with every step", and improve the user's immersive experience satisfaction.

[0045] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0046] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 This is a flowchart illustrating the steps of the virtual reality-based interior design optimization method of the present invention.

[0048] Figure 2 This is a schematic diagram of the color filling process steps of the present invention;

[0049] Figure 3 This is a schematic diagram of the matching analysis process steps of the present invention. Detailed Implementation

[0050] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0051] The current development of virtual technology has failed to consider the visual needs of designers and virtual experience users during the block division process. It only uses existing design templates to perform simple environmental simulations and visually maps environmental elements to create an impression. This results in insufficient precision in the matching between the virtual space and the display, and inadequate attention to detail. It also ignores the problem of mismatch between the matching and synchronous prediction of information between the virtual system and real elements, which leads to the inability to update the virtual data system in a timely manner. In addition, the lack of flexible visual change design in the spatial visualization process of indoor space reconstruction in the virtual environment results in unnatural and inflexible changes in visual points during the user's visual observation.

[0052] To resolve the above technical issues, please refer to Figure 1 As shown, this invention is an interior decoration design optimization method based on virtual reality, the method comprising:

[0053] S1. Obtain a three-dimensional image of the interior space structure, and perform deconstruction analysis on the three-dimensional image to obtain images of interior space elements;

[0054] S2. By decomposing the indoor element images into different spatial element image regions, different sensors are set up to identify the contour information of different spatial element image regions and collect virtual contour images.

[0055] S3. Match different virtual contour images with indoor element information in the historical database and fill them with color. Perform matching analysis based on the color filling results and update the historical database based on the matching analysis results.

[0056] S4. Implement a user indoor space reshaping system based on virtual reality technology using an updated historical database.

[0057] Based on the above technical solution, this embodiment considers the interior decoration design optimization process and designs an interior decoration design optimization method based on virtual reality. The specific method includes: First, acquiring a three-dimensional image of the interior space structure and performing deconstruction analysis on the three-dimensional image to obtain images of interior space elements; the images of interior space elements include the size of the interior space, spatial layout, topology, environmental type, spatial function positioning, etc.; the interior space elements are further specified based on the layout of walls, doors, corridors, and stairs to determine, restrict, and divide them; the information presented by the three-dimensional image includes spatial information, area information, coordinate information, etc., all information types that can be obtained by existing technologies. Commonly available technologies for obtaining three-dimensional images include GPS positioning and wireless mobile image acquisition.

[0058] It should be noted that the process of deconstructing and analyzing 3D images is based on the application of virtual reality technology. The model construction, data information management, data delineation, and signal composition of the virtual scene are all based on the deconstruction of the interior space, the control of various details in the scene, and various types of spatial sensory elements to display the spatial layout, thereby providing important support for immersive interior design.

[0059] Then, the interior element images are decomposed into different spatial element image regions. Different sensors are set up to identify the contour information of different spatial element image regions and collect virtual contour images. The decomposition of image elements requires the use of different sensors to identify the contour information of different spatial element image regions based on the display. Multiple individual spatial elements are generated based on the decomposition of information. The decomposition process involves logical circuit reference, space category refinement and other processing. Image processing is designed in the process of forming spatial element image regions. Image information is obtained and feedback is provided through information acquisition and feedback with interior decoration design technicians and relevant users to update the spatial element information in a timely manner and ensure the accuracy of the decomposition information of interior element images.

[0060] Next, different virtual outline images are matched with indoor element information from the historical database and filled with color. Matching analysis is performed based on the color filling results, and the historical database is updated accordingly. Data information related to the interior design space is obtained from relevant interior design data departments to form a historical database, providing virtual outline images of different designs. Image recognition technology is used to fill the target area with color, and matching analysis is performed based on the color filling results. The historical database is updated accordingly to ensure the synchronous matching process between the historical database and the data in the display space, thereby improving the accuracy of the database-based virtualization framework construction.

[0061] Finally, an indoor space reshaping system based on virtual reality technology is implemented using the updated historical database. The updated historical database is used to perform visual analysis of the space to connect the user's vision with the virtual space, realize the refined construction of the indoor design scene, and ensure that the virtual scene changes naturally and flexibly with the scene within the visual point during the user's visual observation, achieving the visual effect of "changing scenery with every step", and ultimately achieving an immersive scene experience.

[0062] As one embodiment of the present invention, the color filling process is as follows:

[0063] S311. Set the RGB parameters of the unit pixels corresponding to different colors of different elements in the historical database.

[0064] S312. Based on the element information corresponding to different virtual contour images identified by the machine recognition engine, compare them with different element information in the historical database to calculate the shape overlap.

[0065] S313. If the shape overlap is greater than the preset threshold, fill the corresponding virtual contour image with the RGB parameters of the pixel corresponding to the current color; if the shape overlap is less than the preset threshold, do not fill, perform grayscale processing on the current virtual contour image and extract the target element information.

[0066] S314. Obtain the number and area of ​​the grayscale processed virtual contour image and predict the number of color fills in the target element region.

[0067] Through the above technical solution, this embodiment fills the virtual contour image with color. The specific color filling process is as follows: First, the RGB parameters of the unit pixel point corresponding to different element information in the historical database are set; different colors are filled for virtual objects corresponding to different element information. The content of color filling is to set the RGB parameter value of the unit pixel point. The setting method is random, or the RGB parameter value is set according to requirements.

[0068] Then, the machine recognition engine identifies the element information corresponding to different virtual contour images and compares it with different element information in the historical database to calculate the shape overlap. It should be noted that the shape overlap matching here is the result obtained by parameterization based on element information parameters and recognition features such as application field. Shape overlap includes the overlap rate of the outer contour of the element information images under the same proportion under the same application field, and the overlap rate of the same type of information parameters under certain specifications, but is not limited to the case of complete overlap.

[0069] Next, if the shape overlap is greater than a preset threshold, the RGB parameters of the pixels corresponding to the current color are filled into the corresponding virtual contour image; if the shape overlap is less than the preset threshold, no filling is performed, the current virtual contour image is grayscaled, and the target element information is extracted; by judging the shape overlap, element information that does not match the historical database is filtered, and the target element information is extracted to ensure the matching degree of the historical database information.

[0070] Finally, the number and area of ​​the grayscale processed virtual contour image are obtained to predict the number of color fills in the target element region; based on the selected target, the process of accurately recognizing the virtual contour image is achieved, as well as predicting the number of colors in different types of regions of the target element, ensuring the technical update of the data and the dynamic prediction process of virtual space matching information.

[0071] As an embodiment of the present invention, the prediction method for the number of color fills in the target element region is as follows:

[0072] SS1. Calculate the proportion P1 of the number of grayscale processed virtual contour images to the total number of indoor elements;

[0073] SS2, Calculate the ratio P2 of the area of ​​the grayscale processed virtual contour image to the total area of ​​indoor elements;

[0074] SS3, through formula Calculate the standard fill ratio coefficient P sy Where, P1≠P2≠0; β se This refers to the specific gravity parameter for indoor filling.

[0075] SS4, according to the standard filling ratio coefficient P sy Predict the number of color fills n in the target element region.

[0076] Through the above technical solution, in this embodiment, the specific process of predicting the number of color-filled areas of the target element region includes: First, calculating the ratio P1 of the number of grayscale processed virtual contour images to the total number of indoor elements; then, calculating the ratio P2 of the area of ​​the grayscale processed virtual contour images to the area of ​​the total indoor elements; next, using the formula... Calculate the standard fill ratio coefficient P sy Where, P1≠P2≠0; β se The indoor fill density parameter is determined; finally, the standard fill ratio coefficient P is used. sy Predict the number of color fills n in the target element region.

[0077] It should be noted that the indoor filling density parameter β seIt was obtained by fitting and statistically analyzing the proportion of the interior color-filled area to the total interior space area in other similar spaces of the same type in the historical virtual space. It will not be described in detail here.

[0078] As one embodiment of the present invention, the matching analysis process is as follows:

[0079] S321. Compare the number of target element colors filled (n) with a preset threshold:

[0080] If n is less than the preset threshold, the prediction result is determined to be without deviation, and the process continues.

[0081] If n is greater than the preset threshold, the prediction result is judged to have a deviation, and visual image matching is performed.

[0082] S322. Select the visual center point of different virtual contour images corresponding to the target element based on the visualization image matching results;

[0083] S323. Determine the intersection points of each POI based on the straight-line distance between the visual center point of different virtual contour images and the preset visual point at each time.

[0084] S323. Determine the degree of overlap between each POI intersection point and the preset POI intersection point: If the degree of overlap is greater than the preset threshold, update the historical database; otherwise, repeat step S322.

[0085] Through the above technical solution, in this embodiment, the matching analysis is for timely updating of historical database information. The specific matching analysis process is as follows: First, the number of target element color fills n is compared with a preset threshold. If n is less than the preset threshold, the prediction result is judged to have no deviation, and the process continues. If n is greater than the preset threshold, the prediction result is judged to have a deviation, and visual image matching is performed. Second, the visual center point of different virtual contour images corresponding to the target element is selected according to the visual image matching result. Third, the intersection point of each POI is determined according to the straight-line distance between the visual center point of different virtual contour images and the preset visual point at each time. Fourth, the trajectory overlap degree of each POI intersection point and the preset POI intersection point is judged: if the overlap degree is greater than the preset threshold, the historical database is updated; otherwise, step two is repeated until the trajectory overlap degree requirement is met.

[0086] As an embodiment of the present invention, the method for selecting the visual center point in step S322 is as follows:

[0087] Time periods [t1, t2, ..., t] are obtained using GIS positioning technology. n The curve S showing the change in the trajectory of the moving visual point. v ;

[0088] Get any time point ti The visual point mapping presets the curve S of the movement trajectory of the virtual object on the visual plane. pi ;

[0089] curve S v With curve S pi Correlation analysis is performed to obtain strong correlation coefficients. Based on the strong correlation coefficients, visual center point parameters are obtained through fitting, and the visual center points of different virtual contour images are determined.

[0090] Through the above technical solution, this embodiment specifies the method for selecting the visual center point in step S322. The specific method is as follows: First, obtain the time period [t1, t2, ..., t] using GIS positioning technology. n The curve S showing the change in the trajectory of the moving visual point. v Next, obtain any time point t. i The visual point mapping presets the curve S of the movement trajectory of the virtual object on the visual plane. pi Finally, curve S v With curve S pi Correlation analysis is performed to obtain visual center point parameters through fitting, thereby determining the visual center point of different virtual contour images.

[0091] It should be noted that the curve S representing the change in the visual point's movement trajectory... v Mapping the virtual object to the visual point to preset the trajectory change curve S of the virtual object on the visual plane pi The relationship includes: multiple visual points mapping to the curve S of the movement trajectory of a preset virtual object on the visual plane. p1 S p2 ...S pk (where k≥i) is a manifestation of the change in the trajectory of a visual point. Of course, this change in movement is related to time. Through correlation analysis, strong correlation terms can be obtained, and dominant features can be obtained by combining the strong correlation terms.

[0092] As one embodiment of the present invention, the indoor space reshaping system specifically includes:

[0093] The virtual scene generation unit is used to build, render, and manage virtual scene models;

[0094] Visual tracking devices are used to track changes in a user's gaze using various sensors, receivers, and virtual reality technology.

[0095] Displays are used to present signals formed by the fusion of virtual and reality;

[0096] Interactive devices for inputting and outputting signals for manipulation and sensory purposes in a real environment.

[0097] Through the above technical solution, the relevant structure and settings of the indoor space reshaping system in this embodiment include a virtual scene generation unit for constructing, drawing, and managing virtual scene models; a visual tracking device for tracking changes in the user's gaze through various sensors and receivers and virtual reality technology; a display for presenting signals formed by the fusion of virtual and reality; and an interactive device for inputting and outputting signals for real-world environment manipulation and sensory experience. This ensures a high degree of matching between the constructed virtual scene and the real-world experience, allowing users to flexibly utilize the virtual scene for visual experience and design analysis, thereby improving user immersive experience satisfaction.

[0098] As an embodiment of the present invention, the interactive device further includes scene roaming, which includes automatic pathfinding roaming and interactive roaming;

[0099] Automatic pathfinding and roaming allows users to explore a simulated interior design scene along a preset route;

[0100] Interactive roaming allows users to wear visual display devices and independently select routes, adjust directions and viewpoints to explore simulated interior design scenes.

[0101] In conclusion, this embodiment ultimately achieves a "changing scenery with each step" visual experience, enhancing user satisfaction with the immersive experience.

[0102] The above description is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined in the claims, they should all fall within the protection scope of the present invention.

Claims

1. A virtual reality-based method for optimizing interior design, characterized in that, The method includes: S1. Obtain a three-dimensional image of the interior space structure, and perform deconstruction analysis on the three-dimensional image to obtain images of interior space elements; S2. By decomposing the indoor element images into different spatial element image regions, different sensors are set up to identify the contour information of different spatial element image regions and collect virtual contour images. S3. Match different virtual contour images with indoor element information in the historical database and fill them with color. Perform matching analysis based on the color filling results and update the historical database based on the matching analysis results. S4. Implement a user indoor space reshaping system based on virtual reality technology using an updated historical database.

2. The virtual reality-based interior design optimization method according to claim 1, characterized in that, The color filling process is as follows: S311. Set the RGB parameters of the unit pixels corresponding to different colors of different elements in the historical database. S312. Based on the element information corresponding to the different virtual contour images identified by the machine recognition engine, compare them with the different element information of the indoor space in the historical database, and calculate the shape overlap. S313. If the shape overlap is greater than the preset threshold, fill the corresponding virtual contour image with the RGB parameters of the pixel corresponding to the current color; if the shape overlap is less than the preset threshold, do not fill, perform grayscale processing on the current virtual contour image and extract the target element information. S314. Obtain the number and area of ​​the grayscale processed virtual contour image and predict the number of color fills in the target element region.

3. The virtual reality-based interior design optimization method according to claim 2, characterized in that, The method for predicting the number of color fills in the target element region is as follows: SS1. Calculate the proportion P1 of the number of grayscale processed virtual contour images to the total number of indoor elements; SS2, Calculate the ratio P2 of the area of ​​the grayscale processed virtual contour image to the total area of ​​indoor elements; SS3, through formula Calculate the standard fill ratio coefficient P sy ; Where P1≠P2≠0; β se This refers to the specific gravity parameter for indoor filling. SS4, according to the standard filling ratio coefficient P sy Predict the number of color fills n in the target element region.

4. The virtual reality-based interior design optimization method according to claim 2, characterized in that, The matching analysis process is as follows: S321. Compare the number of target element colors filled (n) with a preset threshold: If n is less than the preset threshold, the prediction result is determined to be without deviation, and the process continues. If n is greater than the preset threshold, the prediction result is judged to have a deviation, and visual image matching is performed. S322. Select the visual center point of different virtual contour images corresponding to the target element based on the visualization image matching results; S323. Determine the intersection points of each POI based on the straight-line distance between the visual center point of different virtual contour images and the preset visual point at each time. S323. Determine the degree of overlap between each POI intersection point and the preset POI intersection point: If the degree of overlap is greater than the preset threshold, update the historical database; otherwise, repeat step S322.

5. The virtual reality-based interior design optimization method according to claim 4, characterized in that, The method for selecting the visual center point in step S322 is as follows: Time periods [t1, t2, ..., t] are obtained using GIS positioning technology. n The curve S showing the change in the trajectory of the moving visual point. v ; Get any time point t i The visual point mapping presets the curve S of the movement trajectory of the virtual object on the visual plane. pi ; curve S v With curve S pi Correlation analysis is performed to obtain strong correlation coefficients. Based on the strong correlation coefficients, visual center point parameters are obtained through fitting, and the visual center points of different virtual contour images are determined.

6. The virtual reality-based interior design optimization method according to claim 1, characterized in that, The indoor space reshaping system specifically includes: The virtual scene generation unit is used to build, render, and manage virtual scene models; Visual tracking devices are used to track changes in a user's gaze using various sensors, receivers, and virtual reality technology. Displays are used to present signals formed by the fusion of virtual and reality; Interactive devices for inputting and outputting signals for manipulation and sensory purposes in a real environment.

7. The virtual reality-based interior design optimization method according to claim 6, characterized in that, The interactive device also includes scene roaming, which includes automatic pathfinding roaming and interactive roaming; The automatic pathfinding roaming allows users to tour an interior design simulation scene along a preset route; The interactive roaming allows users to wear visual display devices and independently select routes, adjust directions and viewpoints to tour simulated interior design scenes.

Images