A virtual try-on method and system supporting real-time processing of photos and videos

Abstract

The application discloses a kind of virtual try-on method and system supporting photo and video real-time processing, it is related to virtual try-on technical field, including the following steps: step S1, obtain image data, and image data is identified and feature extraction;Step S2, candidate virtual material is fused rendering with image data, and virtual experience effect drawing is generated and is shown in user end;Step S3, experience report containing user identity mark and selected material mark is generated, and interactive voucher is embedded in experience report;Step S4, obtain the service resource information of offline service provider, and call third party service interface to complete reservation operation;Step S5, offline service end obtains the information of user by identifying interactive voucher, to provide targeted service.The application realizes seamless connection from virtual experience to offline consumption, solves the problem of fragmented function and incoherent user experience in prior art, improves user experience, realizes service closed loop.

Description

Technical Field

[0001] This invention relates to the field of virtual launch technology, and in particular to a virtual launch method and system that supports real-time processing of photos and videos. Background Technology

[0002] With the rapid development of internet technology and mobile devices, online virtual makeup and virtual clothing try-ons have become increasingly popular, providing users with convenient shopping and experiential services. However, in the hairdressing industry, virtual hair try-ons technology still faces many challenges.

[0003] Existing technologies include several virtual hair trial solutions. For example, by acquiring images of the target face and the model's face, the model's hair outline is layered and deformed before being combined with the target face to achieve a hairstyle replacement effect. However, most existing virtual hair trial solutions only focus on the visual effect of the hairstyle replacement, offering limited functionality. They are mostly standalone applications or web tools, providing only static previews and lacking deep integration with offline physical store appointment and user management systems. Users still need to switch apps or make appointments by phone after seeing their desired hairstyle, resulting in a fragmented experience and a lack of a complete service loop from virtual experience to offline consumption, thus limiting the user experience. Summary of the Invention

[0004] The purpose of this invention is to provide a virtual test launch method and system that supports real-time processing of photos and videos, so as to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a virtual test launch method supporting real-time processing of photos and videos, specifically including the following steps:

[0006] Step S1: In response to the image acquisition operation of the user terminal, image data containing user feature regions is acquired, and the image data is identified and features are extracted to generate user feature data;

[0007] Step S2: Based on the user feature data, at least one candidate virtual material is matched from the material database, and the candidate virtual material is fused and rendered with the image data to generate a virtual experience effect image and display it on the user terminal;

[0008] Step S3: In response to the user's confirmation of the virtual experience effect image, generate an experience report containing the user's identity identifier and the selected material identifier. The experience report contains an interaction credential that can be recognized by the offline server.

[0009] Step S4: In response to the reservation request triggered based on the experience report, obtain the service resource information of the offline service provider and call the third-party service interface to complete the reservation operation;

[0010] Step S5: When the user arrives at the offline service provider, the offline service provider obtains the user's material selection information and / or reservation information by recognizing the interaction credential in order to provide targeted services.

[0011] Preferably, in step S1, the identification and feature extraction of the image data includes:

[0012] Extract user facial features, facial feature distribution, hairline position, and current hairstyle outline;

[0013] Based on the facial shape features and facial feature distribution features, facial feature classification is performed to generate user-specific facial shape tags and / or style tags.

[0014] Preferably, in step S2, the material database contains multiple hairstyle attribute tags, which at least include hairstyle length, hairstyle curl, hair color, and style category; matching at least one candidate hairstyle includes:

[0015] Calculate the suitability score for each candidate hairstyle based on the user's face shape tags and / or style tags;

[0016] Candidate hairstyles are recommended in descending order of suitability score;

[0017] In response to the user's filtering instructions, a filtering search is performed based on the hairstyle attribute tags.

[0018] Preferably, in step S3, the experience report further includes at least one of the following:

[0019] The attribute description information of the selected virtual material;

[0020] Usage or maintenance instructions that accompany the selected virtual assets;

[0021] Location information and / or contact details of the offline service provider.

[0022] Preferably, in step S4, obtaining service resource information from the offline service provider and completing the reservation operation includes:

[0023] Based on the user's geographic location information, filter and display a list of offline service providers within a preset range and their available booking time slots;

[0024] In response to the user's confirmation of the target service provider and the reservation time slot, the third-party service interface is invoked to generate a reservation order.

[0025] Preferably, in step S3, the interaction credential is a machine-readable identification code. The offline server scans the identification code to parse the user's identity and material selection information, and displays the corresponding virtual experience effect image and / or reservation information to the user.

[0026] Preferably, the experience report in step S3 is generated in image or webpage format and supports users to share it through social platforms; the interaction credential is output along with the experience report so that non-users can trigger an appointment or in-store consumption through the experience report.

[0027] Preferably, in step S3, the user identity identifier in the experience report is associated with the reservation order generated by the reservation operation. After the offline service terminal identifies the interaction credential, it automatically retrieves the historical virtual experience records and / or historical consumption records corresponding to the user identity identifier to assist the offline service provider in making personalized service recommendations.

[0028] Preferably, after the reservation operation is completed by calling the third-party service interface in step S4, reservation confirmation information is generated and pushed to the user's terminal; the reservation confirmation information includes a copy of the interaction voucher and / or navigation information of the offline service provider, so that the user can display or use it in advance before arriving at the store.

[0029] A virtual launch system that supports real-time processing of photos and videos includes:

[0030] The image acquisition module is used to respond to the image acquisition operation of the user terminal and acquire image data containing the user's feature regions;

[0031] The experience generation module is used to identify and extract features from the image data, match candidate virtual materials from the material database based on the extracted user feature data, and fuse and render the candidate virtual materials with the image data to generate a virtual experience effect image.

[0032] The report generation module is used to generate an experience report containing user identification and selected material identification in response to the user's confirmation operation of the virtual experience effect image. The experience report contains an interaction credential that can be recognized by the offline server.

[0033] The appointment docking module is used to respond to appointment requests triggered based on the experience report, obtain service resource information of offline service providers, and call third-party service interfaces to complete the appointment operation.

[0034] The offline service module is used to obtain the user's material selection information and / or reservation information by recognizing the interaction credentials, so as to provide targeted services.

[0035] The technical effects and advantages of this invention are as follows:

[0036] (1) By constructing a complete technical link from image acquisition, intelligent hairstyle matching and virtual try-on, styling report generation to offline store appointment, this invention achieves seamless connection from virtual experience to offline consumption, solves the problems of functional fragmentation and inconsistent user experience in the prior art, improves user experience, and realizes service closed loop.

[0037] (2) By embedding interactive credentials that can be scanned and identified offline in the styling report, this invention provides merchants with an effective technical means to guide online traffic to offline stores or private traffic pools. The business model is clear and has strong commercial practical value. At the same time, it supports real-time processing of static photos and dynamic video streams. In video mode, it can render frame by frame to achieve dynamic trial preview, which improves the interactive experience and the realism of trying on clothes.

[0038] (3) This invention deeply integrates the store appointment function with the virtual hair trial process. Users can directly select the store and appointment time online after confirming their favorite hairstyle, without switching applications or contacting the store separately, which greatly improves the conversion efficiency from online experience to offline consumption. Attached Figure Description

[0039] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention, but do not constitute a limitation thereof. In the drawings:

[0040] Figure 1 This is a diagram illustrating the method steps of the present invention;

[0041] Figure 2 This is a diagram illustrating the system platform design management of the present invention. Detailed Implementation

[0042] 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.

[0043] This invention provides, for example Figures 1-2 This illustrates a virtual test launch method that supports real-time processing of photos and videos.

[0044] Example 1: Specifically includes the following steps:

[0045] Step S1: In response to the image acquisition operation on the user's end, image data containing the user's feature area is acquired, and the image data is identified and features are extracted to generate user feature data. The user searches for and enters the virtual try-on function page through the WeChat mini program on their mobile phone. When using it for the first time, the system prompts the user to authorize the use of camera permissions. After the user authorizes, they can input image data by clicking the photo button, the upload from album button, and the video try-on button. The photo button calls the mobile phone camera to take a real-time photo containing the front face and head area. Uploading from album selects an existing personal photo from the mobile phone album. The video try-on opens the camera to acquire real-time video stream. When the video stream mode is used, the system automatically detects the face in the video frame and starts frame-by-frame processing after detecting the complete face area.

[0046] It should be noted that all three image acquisition methods mentioned above require explicit authorization from the user before execution. The system strictly adheres to relevant regulations on data privacy protection, and the acquired image data is processed only locally on the user's device, or uploaded to the cloud server for processing with the user's consent.

[0047] Image data recognition and feature extraction include:

[0048] Extract user facial features, facial feature distribution, hairline position, and current hairstyle outline;

[0049] Facial features are classified based on facial shape and facial feature distribution characteristics, generating user-specific facial shape tags and / or style tags.

[0050] Specifically, for face recognition and head feature extraction, after the image data is input, the system calls a pre-trained face detection model to perform face detection on the image. Specifically, this embodiment uses the MTCNN model for face detection and key point localization, extracting the coordinates of 68 key points, including eyes, nose, mouth, eyebrows, and facial contours; and based on the extracted key points, the system further performs the following analysis:

[0051] Face shape classification: Based on the key points of the facial contour, the width-to-height ratio of the face, the angle of the jaw, and other parameters are calculated to classify the user's face shape into one of the following: round face, square face, long face, heart-shaped face, or oval face.

[0052] Hairline detection: Locate the current hairline position based on key points in the forehead area, which is used to determine the boundary of hair replacement during subsequent hairstyle blending.

[0053] Skin color analysis: Extract skin pixels from the forehead and cheek areas, perform color space conversion, and generate the user's skin color feature vector.

[0054] At the same time, the system generates style tags for users based on face shape classification results and the proportion of facial features. For example, users with softer facial features and rounder faces may be labeled as having a sweet style, while users with more defined facial features and more square faces may be labeled as having a neutral style.

[0055] Step S2: Based on user feature data, at least one candidate virtual material is matched from the material database, and the candidate virtual material is fused and rendered with image data to generate a virtual experience effect image and display it on the user's end.

[0056] The resource database contains multiple hairstyle attribute tags, which include at least hairstyle length, curl, hair color, and style category. The hairstyle database pre-stores a large number of hairstyle resources, and each hairstyle record is labeled with multi-dimensional attribute tags, such as hairstyle length, curl, hair color, style, and suitable face shape.

[0057] The user matches at least one candidate hairstyle, including:

[0058] Based on the user's face shape tags and / or style tags, the system calculates the suitability score for each candidate hairstyle. Then, based on the user's face shape tags, the system filters the hairstyle candidate set from the hairstyle database to match that face shape. For example, square-faced users are given priority for layered hairstyles that fall below the jawline to soften facial lines; round-faced users are given priority for short or medium-length hair that adds height to the crown to visually lengthen the face; long-faced users are given priority for hairstyles with bangs to visually shorten the face; and heart-shaped-faced users are given priority for hairstyles with more volume to balance the proportion between the forehead and jawline.

[0059] The system recommends candidate hairstyles by ranking them from highest to lowest based on their suitability scores. It also generates a suitability score by weighting the hairstyles in the candidate set according to the user's style tags. The formula for calculating the suitability score is: Suitability = α × Face Shape Matching Degree + β × Style Matching Degree + γ × Popularity, where α, β, and γ are preset weight coefficients, and α + β + γ = 1. Specifically, face shape matching degree is the degree of matching between the hairstyle's labeled suitable face shape and the user's face shape. If the hairstyle label includes the user's face shape, the matching degree is 1.0; if it is a full face shape match, it is 0.8; if it is an approximate face shape match, it is 0.5; and if there is no match, it is 0. Style matching degree is the semantic similarity between the hairstyle's labeled style tag and the user's style tag, obtained by looking up a table using a predefined style similarity matrix. Popularity is a popularity value calculated based on behavioral data such as the number of times the hairstyle is viewed, tried on, and booked on the platform, and the popularity value is normalized to the [0,1] interval. The default values ​​for α, β, and γ are 0.4, 0.3, and 0.3, respectively. Users can adjust the values ​​of each weight in the settings interface.

[0060] In response to the user's filtering instructions, the system filters and searches based on hairstyle attribute tags; the system displays a list of recommended hairstyles to the user in descending order of suitability score, and the user can also browse and select hairstyles by filtering conditions (such as length, curl, color).

[0061] After a user selects a target hairstyle, the system performs a blending rendering process. This involves aligning the user's facial area with the target hairstyle image to determine the hairstyle's coverage position and range on the face. The system then adjusts the hairstyle image's lighting consistency based on the user's global illumination conditions, ensuring the hairstyle's highlights and shadows match the user's facial lighting direction. Global illumination conditions are obtained by analyzing the image's brightness histogram and the direction of the main light source. The system also fine-tunes the hair color based on the user's skin tone to ensure the coloring effect harmonizes with their complexion. Finally, it performs multi-layer feathering and dynamic deformation processing on the area where the hairstyle meets the head's edge, eliminating harsh stitching marks and creating a more natural blending effect. By comprehensively utilizing facial feature recognition, multi-dimensional hairstyle attribute tags, and a suitability scoring algorithm in hairstyle matching, the system provides highly personalized hairstyle recommendations, unlike existing technologies that only perform coarse matching based on face shape, thus improving recommendation accuracy.

[0062] Step S3: In response to the user's confirmation of the virtual experience rendering, an experience report is generated, containing the user's identity identifier and the identifier of the selected materials. The experience report embeds an interaction credential that can be recognized by the offline server. The interaction credential is a machine-readable identification code. The offline server scans the identification code to parse the user's identity identifier and material selection information, and displays the corresponding virtual experience rendering and / or reservation information to the user. The experience report also includes at least one of the following information:

[0063] The attribute description information of the selected virtual material;

[0064] Usage or maintenance instructions that accompany the selected virtual assets;

[0065] Location information and / or contact details of the offline service provider.

[0066] The experience report is generated in image or webpage format and can be shared by users through social media platforms. An interaction credential is also output along with the experience report, allowing users other than the account holder to trigger reservations or in-store purchases. The user's identity in the experience report is linked to the reservation order generated by the reservation action. After recognizing the interaction credential, the offline service provider automatically retrieves the historical virtual experience records and / or historical consumption records corresponding to that user identity to assist the offline service provider in making personalized service recommendations.

[0067] It should be noted that after finding a satisfactory hairstyle in the virtual try-on interface, users can click the confirm button or share button. In response to this action, the system generates a personalized styling report, presented in page or image format, which includes:

[0068] The user's currently selected recommended hairstyle name, attribute description, and effect image. The effect image is a virtual trial hair fusion effect image seen by the user when confirming. When generating the report, the system performs high-definition processing on the effect image, such as using super-resolution reconstruction algorithms to improve the image resolution, in order to adapt to offline display or printing needs.

[0069] This home styling tutorial includes recommendations for necessary products such as essential oils and styling mousse, as well as styling steps. For example, it might provide a complete step-by-step tutorial with pictures or videos, from applying essential oils to blow-drying techniques. Specifically, the home styling tutorials are stored in the system database, with each hairstyle image associated with a set of preset styling tutorial content. The tutorials are stored in a structured data format, including fields such as product list, operating steps, and precautions. When generating a report, the system retrieves the corresponding tutorial content from the database based on the selected hairstyle's identifier and embeds it into the report.

[0070] Furthermore, a unique QR code is generated for each user, serving as an interaction credential. This QR code encodes the user's hairstyle preference identifier and user ID. Users can share the styling report to social media platforms or save it to their local photo album. The offline service provider scans this QR code to parse the user's identity and material selection information, and then displays the corresponding virtual experience rendering and / or appointment information to the user.

[0071] Step S4: In response to the reservation request triggered by the experience report, obtain the service resource information of the offline service provider and call the third-party service interface to complete the reservation operation;

[0072] Obtaining service resource information from offline service providers and completing the reservation process includes:

[0073] Based on the user's geographic location information, filter and display a list of offline service providers within a preset range and their available booking time slots;

[0074] In response to the user's confirmation of the target service provider and the reservation time slot, the system calls the third-party service interface to generate a reservation order.

[0075] After the reservation is completed by calling the third-party service interface, a reservation confirmation message is generated and pushed to the user's terminal; the reservation confirmation message includes a copy of the interaction voucher and / or the navigation information of the offline service provider, so that the user can display or use it in advance before arriving at the store;

[0076] The appointment process is as follows:

[0077] (1) When a user clicks the appointment button in the styling report, the system obtains the user's current geographical location and calls a third-party map or store management interface to filter out a list of cooperative stores within a preset distance range;

[0078] (2) After the user selects a target store from the list, the system displays the available booking times for that store for the next 7 days;

[0079] (3) After the user selects a specific date and time period and confirms the reservation information, the system calls the reservation interface of the store management system to generate a reservation order and returns a reservation success confirmation message.

[0080] Step S5: When the user arrives at the offline service provider, the offline service provider obtains the user's material selection information and / or reservation information by recognizing the interaction credentials in order to provide targeted services.

[0081] It should be explained in detail that the interaction voucher is generated along with the experience report, allowing users other than the account holder to trigger appointments or in-store consumption through the report. In other words, the recipient of the experience report can also scan the QR code or click the appointment link within the report to access the appointment page and complete the offline service reservation, achieving social-driven user acquisition.

[0082] The user's identity in the experience report is associated with the appointment order generated by the appointment operation. Specifically, when a user triggers an appointment through the experience report and completes the appointment operation, the system establishes a mapping record between the user's identity and the appointment order ID in the database. This mapping record is stored in the system database and includes fields such as user ID, appointment order ID, selected hairstyle identifier, appointment store ID, and appointment time. After the offline service terminal recognizes the interaction credentials, it automatically retrieves the historical virtual experience records and / or historical consumption records corresponding to the user's identity by querying the mapping record, in order to assist the offline service provider in making personalized service recommendations. For example, after a hairstylist scans a user's QR code through a store-side device, the store-side system automatically displays all the hairstyles the user has previously tried on, the trial time for each hairstyle, the user's rating, and the user's historical in-store consumption records, helping the hairstylist understand the user's preferences and consumption habits, and provide targeted service suggestions.

[0083] Example 2: Based on Example 1, a virtual test launch system supporting real-time processing of photos and videos includes:

[0084] The image acquisition module is used to respond to image acquisition operations from the user terminal and acquire image data containing user-featured regions, including still image data and dynamic video stream data. This module interacts with the mobile terminal's camera hardware and photo storage space.

[0085] The experience generation module is used for image data recognition and feature extraction. Based on the extracted user feature data, it matches candidate virtual materials from the material database, merges the candidate virtual materials with the image data, and renders them to generate a virtual experience effect image. Specifically, the experience generation module includes a face detection unit to perform face detection and key point localization on the image; a feature extraction unit to extract features such as face shape, facial feature distribution, hairline, and skin tone; a matching unit to calculate the fit score and select candidate hairstyles; and a rendering unit to perform image processing operations such as lighting consistency adjustment, hair color adaptation, and edge blending. This module can adopt a local computing mode or a cloud computing mode. In the local computing mode, all processing is completed on the user's device; in the cloud computing mode, the image data is uploaded to the cloud server for processing after user consent, and the processing results are returned to the user's device for display.

[0086] The report generation module is used to generate an experience report containing user identification and selected material identification in response to the user's confirmation operation of the virtual experience effect image. The experience report contains interaction credentials that can be recognized by the offline server.

[0087] The appointment integration module is used to respond to appointment requests triggered by experience reports, obtain service resource information from offline service providers, and call third-party service interfaces to complete the appointment operation.

[0088] The offline service module is used to obtain users' material selection information and / or appointment information by recognizing interaction credentials in order to provide targeted services. The offline service module includes a QR code scanning and recognition unit, a data query unit, and a service assistance unit. The QR code scanning and recognition unit scans and decodes the QR code displayed by the user using the camera of the in-store device. The data query unit retrieves the user's complete experience record and appointment information from the cloud server based on the decoded user identifier. The service assistance unit displays user information in the store and assists staff in providing services, including information display interface, historical record query, and service record update functions. This offline service module runs on tablets, smartphones, or dedicated scanning terminals equipped in the store and communicates with the cloud server via wireless network.

[0089] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A virtual test launch method supporting real-time processing of photos and videos, characterized in that, Specifically, the following steps are included: Step S1: In response to the image acquisition operation of the user terminal, image data containing user feature regions is acquired, and the image data is identified and features are extracted to generate user feature data; Step S2: Based on the user feature data, at least one candidate virtual material is matched from the material database, and the candidate virtual material is fused and rendered with the image data to generate a virtual experience effect image and display it on the user terminal; Step S3: In response to the user's confirmation of the virtual experience effect image, generate an experience report containing the user's identity identifier and the selected material identifier. The experience report contains an interaction credential that can be recognized by the offline server. Step S4: In response to the reservation request triggered based on the experience report, obtain the service resource information of the offline service provider and call the third-party service interface to complete the reservation operation; Step S5: When the user arrives at the offline service provider, the offline service provider obtains the user's material selection information and / or reservation information by recognizing the interaction credential in order to provide targeted services.

2. The virtual test launch method supporting real-time processing of photos and videos according to claim 1, characterized in that, In step S1, the identification and feature extraction of the image data includes: Extract user facial features, facial feature distribution, hairline position, and current hairstyle outline; Based on the facial shape features and facial feature distribution features, facial feature classification is performed to generate user-specific facial shape tags and / or style tags.

3. The virtual test launch method supporting real-time processing of photos and videos according to claim 1, characterized in that, In step S2, the material database contains multiple hairstyle attribute tags, which include at least hairstyle length, hairstyle curl, hair color, and style category; matching at least one candidate hairstyle includes: Calculate the suitability score for each candidate hairstyle based on the user's face shape tags and / or style tags; Candidate hairstyles are recommended in descending order of suitability score; In response to the user's filtering instructions, a filtering search is performed based on the hairstyle attribute tags.

4. The virtual test launch method supporting real-time processing of photos and videos according to claim 1, characterized in that, In step S3, the experience report further includes at least one of the following: The attribute description information of the selected virtual material; Usage or maintenance instructions that accompany the selected virtual assets; Location information and / or contact details of the offline service provider.

5. The virtual test launch method supporting real-time processing of photos and videos according to claim 1, characterized in that, In step S4, obtaining service resource information from the offline service provider and completing the reservation operation includes: Based on the user's geographic location information, filter and display a list of offline service providers within a preset range and their available booking time slots; In response to the user's confirmation of the target service provider and the reservation time slot, the third-party service interface is invoked to generate a reservation order.

6. The virtual test launch method supporting real-time processing of photos and videos according to claim 1, characterized in that, In step S3, the interaction credential is a machine-readable identification code. The offline server scans the identification code to parse the user's identity and material selection information, and displays the corresponding virtual experience effect image and / or reservation information to the user.

7. The virtual test launch method supporting real-time processing of photos and videos according to claim 1, characterized in that, The experience report in step S3 is generated in image or webpage format and can be shared by users through social platforms; the interaction credential is output along with the experience report so that non-users can trigger an appointment or in-store consumption through the experience report.

8. The virtual test launch method supporting real-time processing of photos and videos according to claim 1, characterized in that, In step S3, the user identity identifier in the experience report is associated with the reservation order generated by the reservation operation. After the offline service terminal identifies the interaction credential, it automatically retrieves the historical virtual experience records and / or historical consumption records corresponding to the user identity identifier to assist the offline service provider in making personalized service recommendations.

9. The virtual test launch method supporting real-time processing of photos and videos according to claim 1, characterized in that, After the reservation operation is completed by calling the third-party service interface in step S4, reservation confirmation information is generated and pushed to the user's terminal; the reservation confirmation information includes a copy of the interaction voucher and / or navigation information of the offline service provider, so that the user can display or use it in advance before arriving at the store.

10. A virtual test launch system supporting real-time processing of photos and videos, characterized in that, The virtual launch system supporting real-time photo and video processing includes a virtual launch method supporting real-time photo and video processing as described in any one of claims 1-9, comprising: The image acquisition module is used to respond to the image acquisition operation of the user terminal and acquire image data containing the user's feature regions; The experience generation module is used to identify and extract features from the image data, match candidate virtual materials from the material database based on the extracted user feature data, and fuse and render the candidate virtual materials with the image data to generate a virtual experience effect image. The report generation module is used to generate an experience report containing user identification and selected material identification in response to the user's confirmation operation of the virtual experience effect image. The experience report contains an interaction credential that can be recognized by the offline server. The appointment docking module is used to respond to appointment requests triggered based on the experience report, obtain service resource information of offline service providers, and call third-party service interfaces to complete the appointment operation. The offline service module is used to obtain the user's material selection information and / or reservation information by recognizing the interaction credentials, so as to provide targeted services.

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