Integral marketing content rendering method, device and system in AR multi-screen scenario

Abstract

The application relates to the technical field of credit card point marketing, and discloses a rendering method, device and system for point marketing content in an AR multi-split screen scenario. The rendering method comprises the following steps: in the case that a UI needs to be refreshed, obtaining a current interaction immersion degree of a user and a main interface and a current linkage immersion degree of the user and a reference interface; determining a target consistency degree and a target highlighting degree according to the current interaction immersion degree and the current linkage immersion degree; rendering the reference interface according to the target consistency degree and the target highlighting degree, so that the real-time consistency degree of the reference interface and the main interface and the real-time highlighting degree of the reference interface are constrained by the target consistency degree and the target highlighting degree. The rendering method, device and system for point marketing content in the AR multi-split screen scenario can ensure user experience and help achieve a marketing target.

Description

Technical Field

[0001] This application relates to the field of credit card points marketing technology, specifically to a method, device, and system for rendering points marketing content in an AR multi-screen scenario. Background Technology

[0002] With the deep integration of the digital economy and the real economy, interactive marketing has become crucial for maintaining or enhancing brand competitiveness. Credit card points marketing can be conducted through credit card apps, websites, WeChat mini-programs, and offline terminals. Users can check their credit card points, earn points, and redeem goods or benefits on any of these terminals, and user data and points information can be synchronized across multiple terminals.

[0003] Meanwhile, the continuous development of wireless communication technology and its ever-increasing speeds provide a foundation for the practical application of Augmented Reality (AR) technology. Specifically, high communication speeds enable AR devices to receive high-definition, high-refresh-rate video data, while the wireless communication technology itself allows AR devices to operate without data cables, making them portable and easy to wear (e.g., AR glasses). Based on these technological foundations, AR technology is currently being applied in scenarios such as shopping and exhibitions.

[0004] In the process of implementing the embodiments of this application, at least the following problems were found in the related technology:

[0005] When using AR technology in credit card points marketing scenarios, existing interface generation and rendering technologies can support displaying only one interface on devices such as AR glasses. In credit card points marketing, product benefits, points-earning tasks, and existing points are key factors in the points redemption process. AR glasses also have the function of expanding the screen, allowing the display of product benefits, points-earning tasks, and existing points on two or three screens simultaneously, which can improve user immersion and user experience. However, current technology only supports rendering one interface on the AR glasses. If multiple interfaces within the AR glasses are rendered independently, inconsistencies can easily occur, potentially reducing the user experience. Rendering multiple interfaces with the same parameters results in homogenization, hindering users' ability to simultaneously focus on product benefits, points-earning tasks, and existing points, thus hindering the achievement of marketing goals. Summary of the Invention

[0006] To provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not intended as a general commentary, nor is it intended to identify key / important components or describe the scope of protection of these embodiments, but rather as a prelude to the detailed description that follows.

[0007] This application provides a method, apparatus, and system for rendering points marketing content in an AR multi-screen scenario. In the AR multi-screen scenario, combined with the credit card points marketing scenario, the rendering parameters are determined to balance the interactive immersion and linkage immersion of the user experience and the marketing goals. This ensures that the user experience also allows the user to take into account information such as product benefits, points earning tasks, and existing points, which is conducive to achieving marketing goals.

[0008] In some embodiments, two or more credit card points marketing interfaces are displayed in the AR field of view. The rendering method of points marketing content in AR multi-screen scenarios includes:

[0009] When the user interface (UI) of the reference interface needs to be refreshed, obtain the current interaction immersion between the user and the main interface and the current linkage immersion between the user and the reference interface. The main interface is the interface that the user mainly interacts with among two or more credit card points marketing interfaces. The main interface displays one of the following: the existing points value, points-earning tasks, and product benefits. The reference interface is the interface that supplements the information displayed on the main interface in the product benefit redemption scenario. The reference interface displays one or two of the following: the existing points value, points-earning tasks, and product benefits, excluding the content displayed on the main interface. The current interaction immersion is used to indicate the degree of interaction between the user and the main interface, and the current linkage immersion is used to indicate the frequency of the user switching between the main interface and the reference interface.

[0010] Determine the target consistency and target salience based on the current interaction immersion and the current linkage immersion, so that:

[0011] When the current level of interactive immersion is high and the current level of interactive immersion is low, the consistency of the target is low and the prominence of the target is high; when the current level of interactive immersion is high and the current level of interactive immersion is high, the consistency of the target is high and the prominence of the target is low; when the current level of interactive immersion is low and the current level of interactive immersion is high, the consistency of the target is high and the prominence of the target is low; when the current level of interactive immersion is low and the current level of interactive immersion is low, the consistency of the target is high and the prominence of the target is high.

[0012] Among them, target consistency is the similarity between the UI style of the reference interface and the main interface, and target prominence is the degree to which the UI elements of the reference interface are prominent.

[0013] The reference interface is rendered based on the target consistency and target salience, so that the real-time consistency between the reference interface and the main interface, and the real-time salience of the reference interface are constrained by the target consistency and target salience.

[0014] Optionally, target consistency and target salience are determined based on the current interactive immersion and the current linkage immersion, including:

[0015] Four core centers are constructed for the following scenarios: the current interaction immersion is too high and the current linkage immersion is too low; the current interaction immersion is too high and the current linkage immersion is too high; the current interaction immersion is too low and the current linkage immersion is too high; and the current interaction immersion is too low and the current linkage immersion is too low. A fifth core center is constructed for the scenario where the current interaction immersion is just right and the current linkage immersion is just right.

[0016] Get the first difference between the current interactive immersion and the preset interactive immersion, and get the second difference between the current linkage immersion and the preset linkage immersion;

[0017] The first immersion difference and the second immersion difference are input into the Gaussian activation function corresponding to each kernel center to obtain five smooth activation values;

[0018] Five smooth activation values ​​are input into the softmax function to obtain the smooth membership probabilities of the five kernel centers;

[0019] The consistency adjustment value is determined based on the consistency adjustment range, the smooth membership probability, and the consistency weight corresponding to each kernel center; the salience adjustment value is determined based on the salience adjustment range, the smooth membership probability, and the salience weight corresponding to each kernel center; the salience adjustment range is greater than the consistency adjustment range.

[0020] The target consistency is determined based on the consistency adjustment value and the preset consistency, and the target salience is determined based on the salience adjustment value and the preset salience.

[0021] Optionally, the five core centers are as follows:

[0022] ;

[0023] in, , , , , They represent five core centers respectively. This represents the maximum value within the range of interactive immersion values. To preset the level of interactive immersion, This represents the minimum value within the range of interactive immersion levels. To preset the level of immersion in the interaction, This represents the minimum value within the range of values ​​for the immersive engagement level. This represents the maximum value within the range of values ​​for the immersive engagement level.

[0024] Optionally, the first immersion difference and the second immersion difference are input into a Gaussian activation function corresponding to each kernel center to obtain five smooth activation values, including:

[0025] ;

[0026] in, For the first A smooth activation value, This is the difference in immersion level. This is the second immersion difference. For the first Each core center for The width of the core center.

[0027] Optionally, five smooth activation values ​​are input into the softmax function to obtain the smooth membership probabilities of the five kernel centers, including:

[0028] ;

[0029] in, For the first Smooth membership degree of each core center For the first A smooth activation value, These are the weighting coefficients. For the first A smooth activation value, These are the weighting coefficients.

[0030] Optionally, the consistency weights and salience weights corresponding to the five core centers are determined based on the following five cases:

[0031] Scenario 1: The consistency of the objectives is low, while the salience of the objectives is high;

[0032] Scenario 2: The consistency of the objectives is too high, while the salience of the objectives is too low;

[0033] Scenario 3: The consistency of the objectives is too high, while the prominence of the objectives is too low;

[0034] Scenario 4: The consistency of the objectives is relatively high, and the prominence of the objectives is relatively high;

[0035] Scenario 5: The consistency of objectives remains unchanged and the salience of objectives remains unchanged;

[0036] Among them, semantic "too large" corresponds to a positive weight, and semantic "too small" corresponds to a negative weight; "target consistency biased by x" corresponds to consistency weight, and "target salience biased by x" corresponds to target salience weight; "x" represents "large" or "small".

[0037] Optionally, the consistency weights and salience weights corresponding to the five core centers are as follows:

[0038] ;

[0039] That is, the nuclear center The corresponding consistency weight is -1, and the salience weight is 1; core center The corresponding consistency weight is 1, and the salience weight is -1; kernel center The corresponding consistency weight is 1, and the salience weight is -1; kernel center The corresponding consistency weight is 1, and the salience weight is 1; core center The corresponding consistency weight and salience weight are both 0.

[0040] Optionally, the consistency adjustment value is determined based on a preset consistency adjustment range, the consistency weights corresponding to each smooth membership probability and each kernel center, and the salience adjustment value is determined based on a preset salience adjustment range, the salience weights corresponding to each smooth membership probability and each kernel center, including:

[0041] Calculate the first product of each smooth membership probability and the consistency weight corresponding to the same kernel center, and calculate the first sum of the five first products. The product of the preset consistency adjustment range and the first sum is determined as the consistency adjustment value.

[0042] Calculate the second product of each smooth membership probability and the salience weight corresponding to the same kernel center, and calculate the second sum of the five second products. The product of the preset salience adjustment range and the second sum is determined as the salience adjustment value.

[0043] Optionally, the target consistency is determined based on the consistency adjustment value and the preset consistency, and the target salience is determined based on the salience adjustment value and the preset salience, including:

[0044] The first smoothing boundary cutoff value is determined based on the consistency adjustment value and the consistency adjustment magnitude;

[0045] The target consistency is determined by the sum of the product of the consistency adjustment value and the first smooth boundary cutoff value and the consistency benchmark value.

[0046] The second smoothing boundary cutoff value is determined based on the salience adjustment value and the salience adjustment range;

[0047] The target salience is determined by the sum of the product of the salience adjustment value and the second smooth boundary truncation value, and the salience reference value.

[0048] Optionally, target consistency and target salience can be calculated as follows:

[0049] ;

[0050] ;

[0051] in, For the sake of goal consistency, As the benchmark value for consistency, Adjustment value for consistency. For the sigmoid function, To adjust the coefficient, Adjust the range for consistency; To enhance the prominence of the target, As the reference value for salience, Adjust the salience value. Adjust the range to enhance prominence; This is the first smooth boundary cutoff value. This is the second smooth boundary cutoff value.

[0052] Optionally, a reference interface is rendered based on target consistency and target salience, including:

[0053] Interpolation is performed based on the refresh frame rate and the time interval for calculating target consistency and target saliency to obtain multiple intermediate consistency and intermediate saliency values ​​that meet the frame rate requirements and are arranged in chronological order.

[0054] The reference interface is rendered sequentially based on each intermediate consistency and intermediate prominence.

[0055] In some embodiments, two or more credit card points marketing interfaces are displayed in the AR field of view. The rendering device for points marketing content in the AR multi-screen scenario includes an acquisition module, a determination module and a rendering module.

[0056] The acquisition module is used to acquire the current interaction immersion between the user and the main interface and the current linkage immersion between the user and the reference interface when the UI of the reference interface needs to be refreshed. The main interface is the interface that the user mainly interacts with among two or more credit card points marketing interfaces. The main interface displays one of the following: the existing points value, points-earning tasks, and product benefits. The reference interface is the interface that supplements the information displayed on the main interface in the product benefit redemption scenario. The reference interface displays one or two of the following: the existing points value, points-earning tasks, and product benefits, excluding the content displayed on the main interface. The current interaction immersion is used to indicate the degree of interaction between the user and the main interface, and the current linkage immersion is used to indicate the frequency of the user switching between the main interface and the reference interface.

[0057] The determination module is used to determine target consistency and target salience based on the current interaction immersion and the current linkage immersion, so that:

[0058] When the current level of interactive immersion is high and the current level of interactive immersion is low, the consistency of the target is low and the prominence of the target is high; when the current level of interactive immersion is high and the current level of interactive immersion is high, the consistency of the target is high and the prominence of the target is low; when the current level of interactive immersion is low and the current level of interactive immersion is high, the consistency of the target is high and the prominence of the target is low; when the current level of interactive immersion is low and the current level of interactive immersion is low, the consistency of the target is high and the prominence of the target is high.

[0059] Among them, target consistency is the similarity between the UI style of the reference interface and the main interface, and target prominence is the degree to which the UI elements of the reference interface are prominent.

[0060] The rendering module is used to render the reference interface based on the target consistency and target salience, so that the real-time consistency between the reference interface and the main interface, and the real-time salience of the reference interface are constrained by the target consistency and target salience.

[0061] In some embodiments, the rendering apparatus for points-based marketing content in an AR multi-screen scenario includes a processor and a memory storing program instructions. The processor is configured to execute the rendering method for points-based marketing content in an AR multi-screen scenario provided in the foregoing embodiments when executing the program instructions.

[0062] In some embodiments, the rendering system for points-based marketing content in AR multi-screen scenarios includes the rendering device for points-based marketing content in AR multi-screen scenarios provided in the foregoing embodiments.

[0063] The rendering method, apparatus, and system for points-based marketing content in AR multi-screen scenarios provided in this application embodiment can achieve the following technical effects:

[0064] When two or more credit card points marketing interfaces are displayed in the AR view (for banks or merchants, this is the interface within a credit card points marketing scenario), the main interface is the primary user interaction interface among the two or more credit card points marketing interfaces. The main interface displays one of the following: existing points, points-earning tasks, and product benefits. The reference interface is an interface that supplements the information displayed on the main interface in the product benefit redemption scenario (for users, this is a points consumption scenario or a product benefit redemption scenario). The reference interface displays one or two of the following: existing points, points-earning tasks, and product benefits, excluding those displayed on the main interface. For example, the main interface displays existing points, and the reference interface displays points-earning tasks and / or product benefits; the main interface displays points-earning tasks, and the reference interface displays existing points and / or product benefits; the main interface displays product benefits, and the reference interface displays existing points and / or points-earning tasks.

[0065] In scenarios where more than two credit card points marketing interfaces are displayed in an AR field of view, the user experience is determined by the user's current interaction immersion with the main interface and the user's current linkage immersion with the reference interface. The current interaction immersion indicates the user's level of interest in the main interface, while the current linkage immersion indicates the user's level of reference to supplementary information. In credit card points redemption scenarios, the supplementary information provided by the current linkage immersion helps users to promptly grasp the difference between their existing points and product benefits, as well as the path to make up for that difference. This multi-dimensional data enhances the convenience of redeeming product benefits in credit card points redemption scenarios, ultimately improving the user experience in this specific scenario.

[0066] Meanwhile, in this points marketing scenario, the level of engagement can also indicate the level of expectation for redeemed goods and benefits. If the level of interaction engagement is good, but the level of engagement engagement is too low, it means that users are only focused on interacting with the main interface and ignoring the points consumption process, which is contrary to the goal of credit card points marketing.

[0067] In this regard, the following objectives are achieved in determining the consistency and salience of the objectives based on the current level of interactive immersion and the current level of interactive immersion:

[0068] Given the current high level of interactive immersion and low level of engagement with related content, it indicates that users are focused on interacting with the main interface and neglecting the product redemption path, which contradicts the objectives of a credit card points marketing scenario. Therefore, a lower degree of goal consistency and a higher degree of goal salience are necessary. Lower goal consistency increases the overall difference between the reference interface and the main interface, making the reference interface initially attract user attention. Conversely, higher goal salience indicates a higher degree of prominence for the reference interface's elements, making them more likely to attract user attention. Rendering the reference interface based on this goal consistency and salience maintains the user's interactive experience by keeping the main interface unchanged, while the difference and enhanced display of the reference interface draws user attention to the core elements of the credit card points redemption scenario, encouraging users to complete the redemption and achieving the marketing objectives of the credit card points marketing scenario.

[0069] Given the current high level of immersion in both interactive and linked content, it indicates that users are interested in the main interface content but also in the credit card points redemption feature, suggesting a distraction that negatively impacts the user experience. In this case, a higher degree of goal consistency and lower goal salience is preferable. Higher goal consistency improves the alignment between the reference interface and the main interface, reducing overall differences and preventing user distraction due to discrepancies. Conversely, lower goal salience reduces the visual appeal of the reference interface itself. Rendering the reference interface with this balance of goal consistency and salience minimizes user distraction at the display level. If the user is genuinely interested in redeeming related goods, rather than the display method, then even with increased goal consistency and decreased goal salience, their willingness to redeem will not be affected.

[0070] When the current interactive immersion is relatively low while the current linked immersion is relatively high, it indicates that the user has less interest in the main interface content but some interest in the reference interface content. In this case, the goal consistency is also high while the goal salience is low. However, unlike the situation where both interactive and linked immersion are high, the purpose of high goal consistency here is to create a strong overall atmosphere of consistency between the two or more interfaces, thereby improving the overall user experience of the multi-interface composition. Simultaneously, the purpose of low goal salience is to make the reference interface itself look more harmonious, thus improving the viewing experience of the reference interface alone. This allows users to obtain a better overall multi-interface atmosphere and a better overall viewing experience of the reference interface, driven by their interest. Since the user has already focused on several key elements of the credit card points redemption process, improving the user experience is sufficient to achieve the marketing goals.

[0071] If the current interaction immersion and the current interactive immersion are both low, it indicates that users are generally uninterested in the credit card points redemption scenario. In this case, increasing goal consistency and goal salience is crucial. High goal consistency maximizes the overall experience across multiple interfaces, reducing user churn due to poor performance. Furthermore, the main interface represents the user's primary interaction point; since both interaction and interactive immersion are low, it suggests that users are paying more attention to the main interface than to the reference interface. In this situation, increasing goal salience makes the reference interface more attractive, maximizing its information to pique user interest and improve the overall experience of redeeming credit card points, thus minimizing user churn.

[0072] In summary, when faced with the above four situations, the technical solution of this application can adjust the rendering level of the reference interface in a targeted manner, achieving a balance between user experience and marketing goals, so as to take both into account and achieve a win-win situation.

[0073] The above general description and the description below are exemplary and illustrative only and are not intended to limit this application. Attached Figure Description

[0074] One or more embodiments are illustrated by way of example with reference to the accompanying drawings. These illustrative descriptions and drawings do not constitute a limitation on the embodiments. Elements having the same reference numerals in the drawings are considered similar elements, and wherein:

[0075] Figure 1 This is a flowchart illustrating a method for rendering points-based marketing content in an AR multi-screen scenario, as provided in an embodiment of this application.

[0076] Figure 2 This is a schematic diagram illustrating the process of determining target consistency and target prominence based on the current interactive immersion and the current linkage immersion, as provided in an embodiment of this application.

[0077] Figure 3 This is a schematic diagram of a rendering device for points-based marketing content in an AR multi-screen scenario provided in an embodiment of this application;

[0078] Figure 4 This is a schematic diagram of a rendering device for points-based marketing content in an AR multi-screen scenario provided in an embodiment of this application. Detailed Implementation

[0079] To provide a more detailed understanding of the features and technical content of the embodiments of this application, the implementation of the embodiments of this application will be described in detail below with reference to the accompanying drawings. The accompanying drawings are for illustrative purposes only and are not intended to limit the embodiments of this application. In the following technical description, for ease of explanation, several details are used to provide a full understanding of the disclosed embodiments. However, one or more embodiments may still be implemented without these details. In other cases, well-known structures and devices may be simplified in their depiction to simplify the drawings.

[0080] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion.

[0081] Unless otherwise stated, the term "multiple" means two or more.

[0082] In this embodiment, the character " / " indicates that the objects before and after it are in an "or" relationship. For example, A / B means: A or B.

[0083] The term "and / or" describes an association between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or A and B.

[0084] Figure 1 This is a flowchart illustrating a method for rendering points-based marketing content in an AR multi-screen scenario, as provided in an embodiment of this application.

[0085] The AR device can be AR glasses. Two or more credit card points marketing interfaces are displayed within the AR field of view.

[0086] Furthermore, in order to display more than two credit card points marketing screens in the AR field of view, two or more video sources can be connected to the AR glasses, with each split screen of the AR glasses corresponding to one video source.

[0087] Alternatively, if a terminal used for credit card points marketing supports multitasking (e.g., a mobile credit card app or a computer credit card webpage or software), two or more credit card points marketing interfaces in the AR field of view can be supported by a single terminal.

[0088] Alternatively, the AR glasses can display one or more virtual credit card points marketing interfaces, while one or more terminals within its real-world field of view can provide other credit card points marketing interfaces. The virtual credit card points marketing interfaces within the AR glasses can be displayed by terminals within the real-world field of view or by other terminals.

[0089] Furthermore, when two or more credit card points marketing interfaces are displayed in the AR viewpoint, corresponding to two or more terminals, and the same user logs in to both terminals simultaneously, a multi-terminal user identity association mechanism can be established if the identity information used by the user when logging in on different terminals differs. This mechanism utilizes multi-dimensional information such as user account, device fingerprint, and facial features to enable the same user to log in simultaneously on different terminals.

[0090] The rendering method for points-based marketing content in AR multi-screen scenarios provided in this application embodiment can be executed on the AR device or on the cloud / local server.

[0091] Combination Figure 1 As shown, the rendering methods for points-based marketing content in AR multi-screen scenarios include:

[0092] S101. When it is necessary to refresh the UI of the reference interface, obtain the current interaction immersion between the user and the main interface and the current linkage immersion between the user and the reference interface.

[0093] The main interface is the primary interface for user interaction among two or more credit card points marketing interfaces. The main interface displays one of the following: existing points, points-earning tasks, and product benefits. The reference interface is an interface that supplements the information displayed on the main interface in the context of redeeming product benefits. The reference interface displays one or two of the following: existing points, points-earning tasks, and product benefits, excluding those displayed on the main interface. Current interaction immersion indicates the degree of user interaction with the main interface, while current linkage immersion indicates the frequency with which the user switches between the main interface and the reference interface.

[0094] Specifically, when the main interface displays the existing points value, the reference interface displays points-earning tasks, product benefits, or both. Typically, points-earning tasks and product benefits are displayed simultaneously by default, through one or two interfaces. When the main interface displays points-earning tasks, the reference interface displays the existing points value, product benefits, or both. Typically, both are displayed simultaneously by default, through one or two interfaces. When the main interface displays product benefits, the reference interface displays the existing points value, points-earning tasks, or both. Typically, both are displayed simultaneously by default, through one or two interfaces.

[0095] The main interface is the interface with the highest historical interaction immersion among all interfaces within the first preset time period, thus representing "the interface where the user primarily interacts". Other interfaces besides the main interface among two or more credit card points marketing interfaces serve as reference interfaces.

[0096] Optionally, the current interaction immersion between the user and the main interface and the current interactive immersion between the user and the reference interface are obtained, including:

[0097] Within the second preset duration up to the current moment, obtain the first dwell time and interaction frequency of the AR glasses on the main interface; the interaction frequency represents the frequency of user interaction with the main interface through gestures; the second preset duration is less than the first preset duration;

[0098] The current level of interaction immersion is determined based on the first dwell time and the frequency of interaction; the current level of interaction immersion is positively correlated with dwell time and interaction frequency.

[0099] Within the second preset duration up to the current moment, obtain the total duration of each transition cycle and the second dwell time of the AR glasses on the reference interface within a single transition cycle and / or the dwell ratio of the second dwell time to the total duration; a transition cycle refers to the process of the user starting to focus on the main interface, then switching to focus on the reference interface, and finally switching back to focus on the main interface;

[0100] The current level of engagement is determined based on the total duration, the second dwell time, and / or the dwell percentage; the current level of engagement is negatively correlated with the total duration and negatively correlated with the second dwell time and / or the dwell percentage.

[0101] The reference interface needs to be refreshed in real time, and each refresh time represents a situation where the UI of the reference interface needs to be refreshed.

[0102] S102. Determine the target consistency and target prominence based on the current interactive immersion and the current linkage immersion.

[0103] Among them, target consistency refers to the similarity between the UI style of the reference interface and the main interface, and target prominence refers to the degree to which the UI elements of the reference interface are prominent.

[0104] The similarity between the UI style of the reference interface and the main interface includes, but is not limited to, color values / transparency, rounded corners / strokes / shadow parameters, font rendering effects, anti-aliasing, texture sampling, shading logic, perspective correction, shading response, scaling logic when the camera view moves and scene lighting changes, as well as the similarity of the interaction logic rules of two buttons at the same level, such as hovering, clicking, disabling, and loading.

[0105] Factors influencing the prominence of UI elements include, but are not limited to, color contrast, brightness / saturation, depth of field, animation effects, UI depth ordering, close-range placement, perspective weight enhancement, full-resolution, high-quality anti-aliasing and shading rendering, and optimization of UI edge and texture features by oversaliency detection algorithms to amplify their visual differences from the background.

[0106] The above steps need to achieve the following objectives:

[0107] When the current level of interactive immersion is relatively high and the current level of interactive immersion is relatively low, the consistency of the goals is relatively low and the prominence of the goals is relatively high; when the current level of interactive immersion is relatively high and the current level of interactive immersion is relatively high, the consistency of the goals is relatively high and the prominence of the goals is relatively low; when the current level of interactive immersion is relatively low and the current level of interactive immersion is relatively high, the consistency of the goals is relatively high and the prominence of the goals is relatively low; when the current level of interactive immersion is relatively low and the current level of interactive immersion is relatively low, the consistency of the goals is relatively high and the prominence of the goals is relatively high.

[0108] The above objectives can be achieved using existing models such as multi-objective optimization models or fuzzy control models.

[0109] S103. Render the reference interface based on target consistency and target salience.

[0110] This step enables the real-time consistency between the reference interface and the main interface, and the real-time prominence of the reference interface to be constrained by the target consistency and target prominence.

[0111] Optionally, a reference interface is rendered based on target consistency and target saliency, including: interpolating based on the refresh frame rate and the time interval for calculating target consistency and target saliency to obtain multiple intermediate consistency and intermediate saliency values ​​that meet the frame rate requirements and are arranged in chronological order; and then rendering the reference interface sequentially based on each intermediate consistency and intermediate saliency value. This improves animation smoothness and avoids abrupt changes in the screen.

[0112] Using the technical solution provided in this application, when two or more credit card points marketing interfaces are displayed in the AR field of view (for banks or merchants, this is the interface in a credit card points marketing scenario), the main interface is the interface where the user primarily interacts among the two or more credit card points marketing interfaces. The main interface displays one of the following: existing points value, points-earning tasks, and product benefits. The reference interface is an interface that supplements the information displayed on the main interface in the product benefits redemption scenario (for users, this is a points consumption scenario or a product benefits redemption scenario). The reference interface displays one or two of the following: existing points value, points-earning tasks, and product benefits, excluding the content displayed on the main interface. For example, the main interface displays existing points value, and the reference interface displays points-earning tasks and / or product benefits; the main interface displays points-earning tasks, and the reference interface displays existing points value and / or product benefits; the main interface displays product benefits, and the reference interface displays existing points value and / or points-earning tasks.

[0113] In scenarios where more than two credit card points marketing interfaces are displayed in an AR field of view, the user experience is determined by the user's current interaction immersion with the main interface and the user's current linkage immersion with the reference interface. The current interaction immersion indicates the user's level of interest in the main interface, while the current linkage immersion indicates the user's level of reference to supplementary information. In credit card points redemption scenarios, the supplementary information provided by the current linkage immersion helps users to promptly grasp the difference between their existing points and product benefits, as well as the path to make up for that difference. This multi-dimensional data enhances the convenience of redeeming product benefits in credit card points redemption scenarios, ultimately improving the user experience in this specific scenario.

[0114] Meanwhile, in this points marketing scenario, the level of engagement can also indicate the level of expectation for redeemed goods and benefits. If the level of interaction engagement is good, but the level of engagement engagement is too low, it means that users are only focused on interacting with the main interface and ignoring the points consumption process, which is contrary to the goal of credit card points marketing.

[0115] In this regard, the following objectives are achieved in determining the consistency and salience of the objectives based on the current level of interactive immersion and the current level of interactive immersion:

[0116] Given the current high level of interactive immersion and low level of engagement with related content, it indicates that users are focused on interacting with the main interface and neglecting the product redemption path, which contradicts the objectives of a credit card points marketing scenario. Therefore, a lower degree of goal consistency and a higher degree of goal salience are necessary. Lower goal consistency increases the overall difference between the reference interface and the main interface, making the reference interface initially attract user attention. Conversely, higher goal salience indicates a higher degree of prominence for the reference interface's elements, making them more likely to attract user attention. Rendering the reference interface based on this goal consistency and salience maintains the user's interactive experience by keeping the main interface unchanged, while the difference and enhanced display of the reference interface draws user attention to the core elements of the credit card points redemption scenario, encouraging users to complete the redemption and achieving the marketing objectives of the credit card points marketing scenario.

[0117] Given the current high level of immersion in both interactive and linked content, it indicates that users are interested in the main interface content but also in the credit card points redemption feature, suggesting a distraction that negatively impacts the user experience. In this case, a higher degree of goal consistency and lower goal salience is preferable. Higher goal consistency improves the alignment between the reference interface and the main interface, reducing overall differences and preventing user distraction due to discrepancies. Conversely, lower goal salience reduces the visual appeal of the reference interface itself. Rendering the reference interface with this balance of goal consistency and salience minimizes user distraction at the display level. If the user is genuinely interested in redeeming related goods, rather than the display method, then even with increased goal consistency and decreased goal salience, their willingness to redeem will not be affected.

[0118] When the current interactive immersion is relatively low while the current linked immersion is relatively high, it indicates that the user has less interest in the main interface content but some interest in the reference interface content. In this case, the goal consistency is also high while the goal salience is low. However, unlike the situation where both interactive and linked immersion are high, the purpose of high goal consistency here is to create a strong overall atmosphere of consistency between the two or more interfaces, thereby improving the overall user experience of the multi-interface composition. Simultaneously, the purpose of low goal salience is to make the reference interface itself look more harmonious, thus improving the viewing experience of the reference interface alone. This allows users to obtain a better overall multi-interface atmosphere and a better overall viewing experience of the reference interface, driven by their interest. Since the user has already focused on several key elements of the credit card points redemption process, improving the user experience is sufficient to achieve the marketing goals.

[0119] If the current interaction immersion and the current interactive immersion are both low, it indicates that users are generally uninterested in the credit card points redemption scenario. In this case, increasing goal consistency and goal salience is crucial. High goal consistency maximizes the overall experience across multiple interfaces, reducing user churn due to poor performance. Furthermore, the main interface represents the user's primary interaction point; since both interaction and interactive immersion are low, it suggests that users are paying more attention to the main interface than to the reference interface. In this situation, increasing goal salience makes the reference interface more attractive, maximizing its information to pique user interest and improve the overall experience of redeeming credit card points, thus minimizing user churn.

[0120] In summary, when faced with the above four situations, the technical solution of this application can adjust the rendering level of the reference interface in a targeted manner, achieving a balance between user experience and marketing goals, so as to take both into account and achieve a win-win situation.

[0121] The following is a brief explanation of the construction process of the content of each interface in an AR multi-screen scenario:

[0122] Collect credit card user scenario data (login, points redemption, activity participation, etc.) and behavioral preferences, and build a multi-dimensional scenario tag library based on bank credit card marketing scenario classification standards; design a reusable interface component library, including dedicated components such as points redemption and activity entry; use an adaptive generation algorithm to dynamically combine components based on scenario tags and user profiles to generate an interactive interface adapted to the current scenario; add a real-time adaptation verification module to ensure the compatibility and smooth operation of the interface under different terminals and scenarios, link points and marketing data, and realize a closed loop between interface and function.

[0123] Figure 2 This is a schematic diagram illustrating the process of determining target consistency and target salience based on the current interactive immersion and the current linkage immersion, as provided in an embodiment of this application.

[0124] Combination Figure 2 As shown, target consistency and target salience are determined based on the current interactive immersion and the current linkage immersion, including:

[0125] S201. For the following scenarios, construct four core centers respectively: the current interaction immersion is too high and the current linkage immersion is too low; the current interaction immersion is too high and the current linkage immersion is too high; the current interaction immersion is too low and the current linkage immersion is too high; and the current interaction immersion is too low and the current linkage immersion is too low. Then, construct a fifth core center for the scenario where the current interaction immersion is just right and the current linkage immersion is just right.

[0126] Optionally, the five core centers are as follows:

[0127] ;

[0128] in, , , , , They represent five core centers respectively. This represents the maximum value within the range of interactive immersion values. To preset the level of interactive immersion, This represents the minimum value within the range of interactive immersion levels. To preset the level of immersion in the interaction, This represents the minimum value within the range of values ​​for the immersive engagement level. This represents the maximum value within the range of values ​​for the immersive engagement level.

[0129] The first four nuclear centers ( , , , These represent four mutually exclusive scenarios that cover all business scenarios. They are used to anchor the extreme boundary of each scenario, i.e., the maximum offset in each scenario, to ensure that each scenario has a unique corresponding anchor point.

[0130] Compared to the first four nuclear centers, the fifth nuclear center ( Detached from conventional interaction scenarios, this represents the optimal situation where both the current interaction immersion and the current linkage immersion are just right (equal to the preset interaction immersion) and are just right (equal to the preset linkage immersion). It can anchor the balance between user experience and marketing goals, reducing meaningless UI jitter. At the same time, the fifth core center provides a "stable" anchor point to ensure continuous global mapping without blind spots.

[0131] This solution employs a Gaussian radial basis function (RBF) framework to smooth the anchor points in the five cases mentioned above, ensuring that the input is smooth and differentiable in the four cases in the actual scenario. This provides a mathematical basis for the smooth gradient of the target consistency and target salience in the final output, thereby avoiding sudden changes in UI parameters of the reference interface and causing user dizziness.

[0132] S202, obtain the first immersion difference between the current interactive immersion and the preset interactive immersion, and obtain the second immersion difference between the current linkage immersion and the preset linkage immersion.

[0133] Preset interaction immersion and preset linkage immersion are the balance points between user experience and marketing goals. By statistically analyzing users' historical interaction immersion, historical linkage immersion, and historical redemption behavior (or historical consumption points behavior), the preset interaction immersion and preset linkage immersion of the target marketing group can be found with the highest historical interaction immersion, moderate historical linkage immersion, and the highest frequency of historical redemption behavior as the target.

[0134] S203. Input the first immersion difference and the second immersion difference into the Gaussian activation function corresponding to each kernel center to obtain five smooth activation values.

[0135] Optionally, the first immersion difference and the second immersion difference are input into a Gaussian activation function corresponding to each kernel center to obtain five smooth activation values, including:

[0136] ;

[0137] in, For the first A smooth activation value, This is the difference in immersion level. This is the second immersion difference. For the first Each core center for The width of the core center The default value can be 0.3.

[0138] Furthermore, the width of the kernel center is optimized for each specific user characteristic:

[0139] Given the current high level of interactive immersion and low level of collaboration immersion, if users do not engage in any redemption activity for an extended period, Optimize towards a smaller size to allow the reference interface to reduce consistency and increase prominence more quickly; if users frequently exit due to poor user experience, then... The design has been optimized for larger screen sizes, resulting in smoother transitions to the reference interface and improved user experience.

[0140] Given that the current level of interactive immersion is relatively high, and the current level of interactive immersion is also relatively high, the default setting is... Optimize towards a larger size to achieve a smooth transition in the reference interface, avoiding visual fatigue and dizziness caused by frequent UI changes; however, when users are indecisive for extended periods, Optimize towards a smaller size to allow the reference interface to change more quickly, thus enabling users to focus their attention more quickly.

[0141] Given the current low level of interactive immersion and the current high level of interactive immersion, The design has been optimized towards a larger size, making the adjustment process of the reference interface smoother and gradually returning to a comfortable viewing experience, reducing any abruptness for the user.

[0142] Given the current low level of interactive immersion and low level of interactive engagement, if user churn is severe, then... Optimize towards a smaller size to quickly capture the user's attention with the reference interface; if the user repeatedly exits the scene due to discomfort, then... Optimize for zooming in to make the reference interface transition smoothly.

[0143] For the width of the fifth core Then, optimization is performed in the direction of magnification to expand the transition range of the baseline state, ensuring that the changes in the reference interface are relatively smooth when the user is in normal interaction, thereby improving the user experience.

[0144] S204. Input the five smooth activation values ​​into the softmax function to obtain the smooth membership probabilities of the five kernel centers.

[0145] The softmax function is used to achieve soft switching between the four cases mentioned above, avoiding abrupt changes in the final calculated target consistency and target salience.

[0146] Optionally, five smooth activation values ​​are input into the softmax function to obtain the smooth membership probabilities of the five kernel centers, including:

[0147] ;

[0148] in, For the first Smooth membership degree of each core center For the first A smooth activation value, These are the weighting coefficients. For the first A smooth activation value, These are the weighting coefficients.

[0149] The above weighting coefficients or The purpose is to ensure that the four cases are sufficiently distinguishable and do not cause confusion, and also to ensure a smooth transition between the four cases.

[0150] In some application scenarios, the above weighting coefficients can be set to 8 to 11 by default. For example, the weighting coefficients can be set to 8, 9, 10 or 11 by default.

[0151] Furthermore, optimizations can be made based on specific user characteristics:

[0152] For new users or experienced users who frequently switch between interfaces, reduce the weighting factor to make the changes in the reference interface smoother.

[0153] For experienced users who don't switch interfaces frequently, increase the weighting factor to make the reference interface more responsive.

[0154] During the optimization process, the values ​​of the above weight coefficients should not be too small to avoid the phenomenon of ambiguous membership, nor should they be too large to avoid the phenomenon of softmax function overflow.

[0155] Typically, the weighting coefficients mentioned above take values ​​in the range of [5, 20] during the optimization process.

[0156] As mentioned in the preceding steps, the fifth core center can anchor the balance between user experience and marketing goals, and ensure continuous global mapping without blind spots. This function is mainly reflected in the process of calculating the smooth membership probability. In this calculation process, the smooth membership probability corresponding to the fifth core center is used as the denominator of the smooth membership probabilities corresponding to the other four core centers to maintain the denominator's stability and avoid drastic changes. This is because the fifth core center serves as a benchmark. During normal interaction, if the user has a good experience and it is conducive to achieving marketing goals, the current interaction immersion and current linkage immersion need to be ensured to hover around the benchmark point. That is, the probability of any smooth activation value belonging to the fifth core is greater than the probability of belonging to any of the other four core centers. This results in the smooth membership probability corresponding to the fifth core center being greater than the smooth membership probabilities corresponding to the other four core centers. Therefore, the smooth membership probability corresponding to the fifth core center can maintain the denominator's stability and avoid drastic changes, that is, avoid drastic changes in the smooth membership probabilities corresponding to the other four centers, which is conducive to the smooth changes in the subsequently calculated consistency adjustment value and salience adjustment value.

[0157] S205. Determine the consistency adjustment value based on the consistency adjustment range, the smooth membership probability, and the consistency weight corresponding to each kernel center. Determine the salience adjustment value based on the salience adjustment range, the smooth membership probability, and the salience weight corresponding to each kernel center.

[0158] The adjustment range for salience is greater than that for consistency.

[0159] Optionally, the consistency weights and salience weights corresponding to the five core centers are determined based on the following five cases:

[0160] Scenario 1: The consistency of the objectives is low, while the salience of the objectives is high;

[0161] Scenario 2: The consistency of the objectives is too high, while the salience of the objectives is too low;

[0162] Scenario 3: The consistency of the objectives is too high, while the prominence of the objectives is too low;

[0163] Scenario 4: The consistency of the objectives is relatively high, and the prominence of the objectives is relatively high;

[0164] Scenario 5: The consistency of objectives remains unchanged and the salience of objectives remains unchanged;

[0165] Among them, semantic "too large" corresponds to a positive weight, and semantic "too small" corresponds to a negative weight; "target consistency biased by x" corresponds to consistency weight, and "target salience biased by x" corresponds to target salience weight; "x" represents "large" or "small".

[0166] Optionally, the consistency weights and salience weights corresponding to the five core centers are as follows:

[0167] ;

[0168] That is, the nuclear center The corresponding consistency weight is -1, and the salience weight is 1; core center The corresponding consistency weight is 1, and the salience weight is -1; kernel center The corresponding consistency weight is 1, and the salience weight is -1; kernel center The corresponding consistency weight is 1, and the salience weight is 1; core center The corresponding consistency weight and salience weight are both 0.

[0169] S206. Determine the target consistency based on the consistency adjustment value and the preset consistency, and determine the target salience based on the salience adjustment value and the preset salience.

[0170] Optionally, the consistency adjustment value is determined based on a preset consistency adjustment range, the consistency weights corresponding to each smooth membership probability and each kernel center, and the salience adjustment value is determined based on a preset salience adjustment range, the salience weights corresponding to each smooth membership probability and each kernel center, including:

[0171] Calculate the first product of each smooth membership probability and the consistency weight corresponding to the same kernel center, and calculate the first sum of the five first products. The product of the preset consistency adjustment range and the first sum is determined as the consistency adjustment value.

[0172] Calculate the second product of each smooth membership probability and the salience weight corresponding to the same kernel center, and calculate the second sum of the five second products. The product of the preset salience adjustment range and the second sum is determined as the salience adjustment value.

[0173] Optionally, the target consistency is determined based on the consistency adjustment value and the preset consistency, and the target salience is determined based on the salience adjustment value and the preset salience, including:

[0174] The first smoothing boundary cutoff value is determined based on the consistency adjustment value and the consistency adjustment magnitude;

[0175] The target consistency is determined by the sum of the product of the consistency adjustment value and the first smooth boundary cutoff value and the consistency benchmark value.

[0176] The second smoothing boundary cutoff value is determined based on the salience adjustment value and the salience adjustment range;

[0177] The target salience is determined by the sum of the product of the salience adjustment value and the second smooth boundary truncation value, and the salience reference value.

[0178] Optionally, target consistency and target salience can be calculated as follows:

[0179] ;

[0180] ;

[0181] in, For the sake of goal consistency, As the benchmark value for consistency, Adjustment value for consistency. For the sigmoid function, To adjust the coefficient, Adjust the range for consistency; To enhance the prominence of the target, As the reference value for salience, Adjust the salience value. Adjust the range to enhance prominence; This is the first smooth boundary cutoff value. This is the second smooth boundary cutoff value.

[0182] Figure 3 This is a schematic diagram of a rendering device for points-based marketing content in an AR multi-screen scenario, provided in an embodiment of this application. The rendering device can be implemented through software, hardware, or a combination of both.

[0183] In the AR view, more than two credit card points marketing interfaces are displayed.

[0184] Combination Figure 3 As shown, the rendering device for points marketing content in an AR multi-screen scenario includes an acquisition module 31, a determination module 32, and a rendering module 33.

[0185] The acquisition module 31 is used to acquire the current interaction immersion between the user and the main interface and the current linkage immersion between the user and the reference interface when the UI of the reference interface needs to be refreshed. The main interface is the interface that the user mainly interacts with among two or more credit card points marketing interfaces. The main interface displays one of the existing points value, points-earning tasks, and product benefits. The reference interface is the interface that supplements the information displayed on the main interface in the product benefit redemption scenario. The reference interface displays one or two of the existing points value, points-earning tasks, and product benefits other than the content displayed on the main interface. The current interaction immersion is used to indicate the degree of interaction between the user and the main interface, and the current linkage immersion is used to indicate the frequency of the user switching between the main interface and the reference interface.

[0186] Module 32 is used to determine target consistency and target salience based on the current interaction immersion and the current linkage immersion, so that:

[0187] When the current level of interactive immersion is high and the current level of interactive immersion is low, the consistency of the target is low and the prominence of the target is high; when the current level of interactive immersion is high and the current level of interactive immersion is high, the consistency of the target is high and the prominence of the target is low; when the current level of interactive immersion is low and the current level of interactive immersion is high, the consistency of the target is high and the prominence of the target is low; when the current level of interactive immersion is low and the current level of interactive immersion is low, the consistency of the target is high and the prominence of the target is high.

[0188] Among them, target consistency is the similarity between the UI style of the reference interface and the main interface, and target prominence is the degree to which the UI elements of the reference interface are prominent.

[0189] The rendering module 33 is used to render the reference interface based on the target consistency and target salience, so that the real-time consistency between the reference interface and the main interface and the real-time salience of the reference interface are constrained by the target consistency and target salience.

[0190] Optionally, the determination module 32 includes a kernel center determination unit, an immersion difference calculation unit, an RBF unit, a Softmax unit, an adjustment value calculation unit, and a target value calculation unit;

[0191] The core center determination unit is used to construct four core centers for the following scenarios: the current interaction immersion is too high and the current linkage immersion is too low; the current interaction immersion is too high and the current linkage immersion is too high; the current interaction immersion is too low and the current linkage immersion is too high; and the current interaction immersion is too low and the current linkage immersion is too low. A fifth core center is constructed for the scenario where the current interaction immersion is just right and the current linkage immersion is just right.

[0192] The immersion difference calculation unit is used to obtain the first immersion difference between the current interactive immersion and the preset interactive immersion, and to obtain the second immersion difference between the current linkage immersion and the preset linkage immersion.

[0193] The RBF unit is used to input the first immersion difference and the second immersion difference into the Gaussian activation function corresponding to each kernel center to obtain five smooth activation values;

[0194] The Softmax unit is used to input five smooth activation values ​​into the softmax function to obtain the smooth membership probabilities of the five kernel centers;

[0195] The adjustment value calculation unit is used to determine the consistency adjustment value based on the consistency adjustment range, the smooth membership probability, and the consistency weight corresponding to each kernel center; and to determine the salience adjustment value based on the salience adjustment range, the smooth membership probability, and the salience weight corresponding to each kernel center; the salience adjustment range is greater than the consistency adjustment range;

[0196] The target value calculation unit is used to determine the target consistency based on the consistency adjustment value and the preset consistency, and to determine the target salience based on the salience adjustment value and the preset salience.

[0197] Optionally, the RBF unit is specifically used for:

[0198] ;

[0199] in, For the first A smooth activation value, This is the difference in immersion level. This is the second immersion difference. For the first Each core center for The width of the core center.

[0200] Optionally, the Softmax unit is specifically used for:

[0201] ;

[0202] in, For the first Smooth membership degree of each core center For the first A smooth activation value, These are the weighting coefficients. For the first A smooth activation value, These are the weighting coefficients.

[0203] Optionally, in the kernel center determination unit, the consistency weight and salience weight corresponding to the five kernel centers are determined according to the following five cases:

[0204] Scenario 1: The consistency of the objectives is low, while the salience of the objectives is high;

[0205] Scenario 2: The consistency of the objectives is too high, while the salience of the objectives is too low;

[0206] Scenario 3: The consistency of the objectives is too high, while the prominence of the objectives is too low;

[0207] Scenario 4: The consistency of the objectives is relatively high, and the prominence of the objectives is relatively high;

[0208] Scenario 5: The consistency of objectives remains unchanged and the salience of objectives remains unchanged;

[0209] Among them, semantic "too large" corresponds to a positive weight, and semantic "too small" corresponds to a negative weight; "target consistency biased by x" corresponds to consistency weight, and "target salience biased by x" corresponds to target salience weight; "x" represents "large" or "small".

[0210] Optionally, the adjustment value calculation unit is specifically used for:

[0211] Calculate the first product of each smooth membership probability and the consistency weight corresponding to the same kernel center, and calculate the first sum of the five first products. The product of the preset consistency adjustment range and the first sum is determined as the consistency adjustment value.

[0212] Calculate the second product of each smooth membership probability and the salience weight corresponding to the same kernel center, and calculate the second sum of the five second products. The product of the preset salience adjustment range and the second sum is determined as the salience adjustment value.

[0213] Optionally, the target value calculation unit is specifically used for:

[0214] The first smoothing boundary cutoff value is determined based on the consistency adjustment value and the consistency adjustment magnitude;

[0215] The target consistency is determined by the sum of the product of the consistency adjustment value and the first smooth boundary cutoff value and the consistency benchmark value.

[0216] The second smoothing boundary cutoff value is determined based on the salience adjustment value and the salience adjustment range;

[0217] The target salience is determined by the sum of the product of the salience adjustment value and the second smooth boundary truncation value, and the salience reference value.

[0218] Optionally, the rendering module 33 includes an interpolation unit and a rendering unit;

[0219] The interpolation unit is used to interpolate based on the refresh frame rate and the time interval for calculating target consistency and target saliency, to obtain multiple intermediate consistency and intermediate saliency values ​​that meet the frame rate requirements and are arranged in chronological order.

[0220] The rendering unit is used to render the reference interface sequentially based on each intermediate consistency and intermediate salience.

[0221] In some embodiments, the rendering apparatus for points-based marketing content in an AR multi-screen scenario includes a processor and a memory storing program instructions. The processor is configured to execute the rendering method for points-based marketing content in an AR multi-screen scenario provided in the foregoing embodiments when executing the program instructions.

[0222] In some embodiments, the rendering system for points-based marketing content in AR multi-screen scenarios includes the rendering device for points-based marketing content in AR multi-screen scenarios provided in the foregoing embodiments.

[0223] Figure 4 This is a schematic diagram of a rendering device for points-based marketing content in an AR multi-screen scenario provided in an embodiment of this application.

[0224] Combination Figure 4 As shown, the rendering device for points-based marketing content in an AR multi-screen scenario includes:

[0225] The processor 41 and memory 42 may also include a communication interface 43 and a bus 44. The processor 41, communication interface 43, and memory 42 can communicate with each other via the bus 44. The communication interface 43 can be used for information transmission. The processor 41 can call logical instructions in the memory 42 to execute the rendering method for points-based marketing content in the AR multi-screen scenario provided in the foregoing embodiments.

[0226] Furthermore, the logical instructions in the aforementioned memory 42 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium.

[0227] The memory 42, as a computer-readable storage medium, can be used to store software programs and computer-executable programs, such as program instructions / modules corresponding to the methods in the embodiments of this application. The processor 41 executes functional applications and data processing by running the software programs, instructions, and modules stored in the memory 42, thereby implementing the methods in the above-described method embodiments.

[0228] The memory 42 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the terminal device. Furthermore, the memory 42 may include high-speed random access memory and may also include non-volatile memory.

[0229] This application provides a computer-readable storage medium storing computer-executable instructions, which are configured to execute the rendering method for points-based marketing content in an AR multi-screen scenario provided in the foregoing embodiments.

[0230] This application provides a computer program product, which includes a computer program stored on a computer-readable storage medium. The computer program includes program instructions, which, when executed by a computer, cause the computer to execute the rendering method for points marketing content in an AR multi-screen scenario provided in the foregoing embodiments.

[0231] The aforementioned computer-readable storage medium may be a transient computer-readable storage medium or a non-transitory computer-readable storage medium.

[0232] The technical solutions of this application embodiment can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes one or more instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods in this application embodiment. The aforementioned storage medium can be a non-transitory storage medium, including: USB flash drive, portable hard drive, read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk, and other media capable of storing program code; it can also be a transient storage medium.

[0233] The foregoing description and accompanying drawings fully illustrate embodiments of this application to enable those skilled in the art to practice them. Other embodiments may include structural, logical, electrical, procedural, and other changes. The embodiments represent only possible variations. Individual components and functions are optional unless explicitly required, and the order of operations may vary. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. Moreover, the terminology used in this application is for describing embodiments only and is not intended to limit the claims. As used in the description of embodiments and claims, the singular forms “a,” “an,” and “the” are intended to equally include the plural forms unless the context clearly indicates otherwise. Additionally, when used in this application, the terms “comprise” and its variations “comprises” and / or “comprising” refer to the presence of stated features, integrals, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof. Unless otherwise specified, an element defined by the phrase "comprising a..." does not exclude the presence of other identical elements in the process, method, or apparatus that includes that element. In this document, each embodiment may focus on describing the differences from other embodiments, and similar or identical parts between embodiments can be referred to mutually. For methods, products, etc., disclosed in the embodiments, if they correspond to the method section disclosed in the embodiments, then the relevant parts can be referred to the description of the method section.

[0234] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the embodiments of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0235] The methods and products (including but not limited to devices and equipment) disclosed in the embodiments herein can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units may be merely a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the shown or discussed units may be through some interfaces, and the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms. Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, i.e., they may be located in one place or distributed across multiple network units. Some or all of the units may be selected to implement this embodiment according to actual needs. Furthermore, the functional units in the embodiments of this application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0236] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

Claims

1. A method for rendering points-based marketing content in an AR multi-screen scenario, characterized in that, The rendering method for displaying two or more credit card points marketing interfaces in an AR field of view includes: When the UI of the reference interface needs to be refreshed, obtain the current interaction immersion between the user and the main interface and the current linkage immersion between the user and the reference interface. The main interface is the interface that the user mainly interacts with among two or more credit card points marketing interfaces. The main interface displays one of the following: the existing points value, points-earning tasks, and product benefits. The reference interface is the interface that supplements the information displayed on the main interface in the product benefit redemption scenario. The reference interface displays one or two of the following: the existing points value, points-earning tasks, and product benefits, excluding the content displayed on the main interface. The current interaction immersion is used to indicate the degree of interaction between the user and the main interface, and the current linkage immersion is used to indicate the frequency of the user switching between the main interface and the reference interface. Determine the target consistency and target salience based on the current interaction immersion and the current linkage immersion, so that: When the current level of interactive immersion is high and the current level of interactive immersion is low, the consistency of the target is low and the prominence of the target is high; when the current level of interactive immersion is high and the current level of interactive immersion is high, the consistency of the target is high and the prominence of the target is low; when the current level of interactive immersion is low and the current level of interactive immersion is high, the consistency of the target is high and the prominence of the target is low; when the current level of interactive immersion is low and the current level of interactive immersion is low, the consistency of the target is high and the prominence of the target is high. Among them, target consistency is the similarity between the UI style of the reference interface and the main interface, and target prominence is the degree to which the UI elements of the reference interface are prominent. The reference interface is rendered based on the target consistency and target salience, so that the real-time consistency between the reference interface and the main interface, and the real-time salience of the reference interface are constrained by the target consistency and target salience.

2. The rendering method according to claim 1, characterized in that, Determine the target consistency and target salience based on the current interactive immersion and the current linkage immersion, including: Four core centers are constructed for the following scenarios: the current interaction immersion is too high and the current linkage immersion is too low; the current interaction immersion is too high and the current linkage immersion is too high; the current interaction immersion is too low and the current linkage immersion is too high; and the current interaction immersion is too low and the current linkage immersion is too low. A fifth core center is constructed for the scenario where the current interaction immersion is just right and the current linkage immersion is just right. Get the first difference between the current interactive immersion and the preset interactive immersion, and get the second difference between the current linkage immersion and the preset linkage immersion; The first immersion difference and the second immersion difference are input into the Gaussian activation function corresponding to each kernel center to obtain five smooth activation values; Five smooth activation values ​​are input into the softmax function to obtain the smooth membership probabilities of the five kernel centers; The consistency adjustment value is determined based on the consistency adjustment range, the smooth membership probability, and the consistency weight corresponding to each kernel center; the salience adjustment value is determined based on the salience adjustment range, the smooth membership probability, and the salience weight corresponding to each kernel center; the salience adjustment range is greater than the consistency adjustment range. The target consistency is determined based on the consistency adjustment value and the preset consistency, and the target salience is determined based on the salience adjustment value and the preset salience.

3. The rendering method according to claim 2, characterized in that, The first immersion difference and the second immersion difference are input into the Gaussian activation function corresponding to each kernel center to obtain five smooth activation values, including: ； in, For the first A smooth activation value, This is the difference in immersion level. This is the second immersion difference. For the first One core center, for The width of the core center; Five smooth activation values ​​are input into the softmax function to obtain the smooth membership probabilities of the five kernel centers, including: ； in, For the first Smooth membership degree of each core center For the first A smooth activation value, These are the weighting coefficients. For the first A smooth activation value, These are the weighting coefficients.

4. The rendering method according to claim 2, characterized in that, The consistency weights and salience weights corresponding to the five core centers are determined based on the following five cases: Scenario 1: The consistency of the objectives is low, while the salience of the objectives is high; Scenario 2: The consistency of the objectives is too high, while the salience of the objectives is too low; Scenario 3: The consistency of the objectives is too high, while the prominence of the objectives is too low; Scenario 4: The consistency of the objectives is relatively high, and the prominence of the objectives is relatively high; Scenario 5: The consistency of objectives remains unchanged and the salience of objectives remains unchanged; Among them, semantic "larger" corresponds to positive weight, and semantic "smaller" corresponds to negative weight; "target consistency biased by x" corresponds to consistency weight, and "target salience biased by x" corresponds to target salience weight; "x" represents "larger" or "smaller".

5. The rendering method according to claim 2, characterized in that, The consistency adjustment value is determined based on the preset consistency adjustment range, the consistency weights corresponding to each smooth membership probability and each kernel center, and the salience adjustment value is determined based on the preset salience adjustment range, the salience weights corresponding to each smooth membership probability and each kernel center, including: Calculate the first product of each smooth membership probability and the consistency weight corresponding to the same kernel center, and calculate the first sum of the five first products. The product of the preset consistency adjustment range and the first sum is determined as the consistency adjustment value. Calculate the second product of each smooth membership probability and the salience weight corresponding to the same kernel center, and calculate the second sum of the five second products. The product of the preset salience adjustment range and the second sum is determined as the salience adjustment value.

6. The rendering method according to claim 2, characterized in that, The target consistency is determined based on the consistency adjustment value and the preset consistency, and the target salience is determined based on the salience adjustment value and the preset salience, including: The first smoothing boundary cutoff value is determined based on the consistency adjustment value and the consistency adjustment magnitude; The target consistency is determined by the sum of the product of the consistency adjustment value and the first smooth boundary cutoff value and the consistency benchmark value. The second smoothing boundary cutoff value is determined based on the salience adjustment value and the salience adjustment range; The target salience is determined by the sum of the product of the salience adjustment value and the second smooth boundary truncation value, and the salience baseline value.

7. The rendering method according to any one of claims 1 to 6, characterized in that, Render a reference interface based on target consistency and target salience, including: Interpolation is performed based on the refresh frame rate and the time interval for calculating target consistency and target saliency to obtain multiple intermediate consistency and intermediate saliency values ​​that meet the frame rate requirements and are arranged in chronological order. The reference interface is rendered sequentially based on each intermediate consistency and intermediate prominence.

8. A rendering device for points-based marketing content in an AR multi-screen scenario, characterized in that, The AR field of view displays two or more credit card points marketing interfaces, and the rendering device includes: The acquisition module is used to acquire the current interaction immersion between the user and the main interface and the current linkage immersion between the user and the reference interface when the UI of the reference interface needs to be refreshed. The main interface is the interface that the user mainly interacts with among two or more credit card points marketing interfaces. The main interface displays one of the following: the existing points value, points-earning tasks, and product benefits. The reference interface is the interface that supplements the information displayed on the main interface in the product benefit redemption scenario. The reference interface displays one or two of the following: the existing points value, points-earning tasks, and product benefits, excluding the content displayed on the main interface. The current interaction immersion is used to indicate the degree of interaction between the user and the main interface, and the current linkage immersion is used to indicate the frequency of the user switching between the main interface and the reference interface. The determination module is used to determine the target consistency and target salience based on the current interaction immersion and the current linkage immersion, so that: When the current level of interactive immersion is high and the current level of interactive immersion is low, the consistency of the target is low and the prominence of the target is high; when the current level of interactive immersion is high and the current level of interactive immersion is high, the consistency of the target is high and the prominence of the target is low; when the current level of interactive immersion is low and the current level of interactive immersion is high, the consistency of the target is high and the prominence of the target is low; when the current level of interactive immersion is low and the current level of interactive immersion is low, the consistency of the target is high and the prominence of the target is high. Among them, target consistency is the similarity between the UI style of the reference interface and the main interface, and target prominence is the degree to which the UI elements of the reference interface are prominent. The rendering module is used to render the reference interface based on the target consistency and target salience, so that the real-time consistency between the reference interface and the main interface, and the real-time salience of the reference interface are constrained by the target consistency and target salience.

9. A rendering device for points-based marketing content in an AR multi-screen scenario, comprising a processor and a memory storing program instructions, characterized in that, The processor is configured to, when executing the program instructions, perform the rendering method for points-based marketing content in an AR multi-screen scenario as described in any one of claims 1 to 7.

10. A rendering system for points-based marketing content in an AR multi-screen scenario, characterized in that, Includes the rendering device for points-based marketing content in an AR multi-screen scenario as described in claim 8 or 9.

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