Product introduction method and system based on AR glasses
By acquiring user-generated images and historical information through AR glasses, the system identifies target audiences and generates predictive questions and answers, thus solving the problems of high cost and instability caused by manual explanations and achieving efficient and accurate product introductions.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- QINGYUAN POLYTECHNIC
- Filing Date
- 2025-12-31
- Publication Date
- 2026-04-10
AI Technical Summary
In existing technologies, product introductions rely on manual explanations, which leads to high training and management costs, unstable service quality, difficulty in maintaining consistency, and poor presentation effectiveness.
By acquiring real-time field-of-view image information and historical question information of target users through AR glasses, the system can identify the target audience and generate predicted questions and answers, reducing the thinking time of presenters and improving the accuracy of answers.
It enables fast and accurate product introductions, shortens user waiting time, and improves user experience and presentation effectiveness.
Smart Images
Figure CN121833119A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the technical field of intelligent applications, and more specifically, to a product introduction method and system based on AR glasses. Background Technology
[0002] As an emerging spatial computing device, AR glasses are characterized by the seamless integration of digital information with the real world, achieving a visual effect of superimposing the virtual and real. They can project a virtual screen into the user's field of vision through the lenses, providing an immersive experience that surpasses traditional devices.
[0003] Currently, product introductions generally rely on human explanations. However, human explanations require high training and management costs, and the service quality is easily affected by the presenter's condition, making it difficult to maintain stability and consistency. This results in poor presentation effectiveness and requires further improvement. Summary of the Invention
[0004] Based on this, embodiments of this application provide a product introduction method and system based on AR glasses to solve the problem of poor introduction effect in the prior art.
[0005] In a first aspect, embodiments of this application provide a product introduction method based on AR glasses, the method comprising: Acquire real-time field-of-view image information and multiple historical question information of the target user; Based on the real-time field-of-view image information, the target object of interest information is determined; Based on the target interest information and multiple historical question information, generate predicted question information corresponding to each of the historical question information; Based on the multiple predicted question information, predictive answer information corresponding to each predicted question information is generated.
[0006] Compared with existing technologies, the beneficial effects are as follows: The product introduction method based on AR glasses provided in this application allows the terminal device to first acquire the real-time field-of-view image information and multiple historical question information of the target user. Then, based on the real-time field-of-view image information, it quickly determines the target attention information. Next, based on the target attention information and multiple historical question information, it accurately generates predicted question information corresponding to each historical question information. Finally, based on multiple predicted question information, it effectively generates predicted answer information corresponding to each predicted question information. This enables the prediction of questions that the target user may ask, shortens the thinking time of the presenter, improves the accuracy of the presenter's answers, reduces the waiting time of the target user, effectively improves the user experience, significantly improves the presentation effect, and to a certain extent solves the problem of poor presentation effect in the current market.
[0007] Secondly, embodiments of this application provide a product introduction system based on AR glasses, the system comprising: Real-time field-of-view image information acquisition module: used to acquire the target user's real-time field-of-view image information and multiple historical question information; Target interest object information determination module: used to determine target interest object information based on the real-time field-of-view image information; Predictive question information generation module: used to generate predictive question information corresponding to each of the historical question information based on the target interest information and multiple historical question information; Predictive answer information generation module: used to generate predictive answer information corresponding to each of the multiple predicted question information.
[0008] Thirdly, embodiments of this application provide a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method described in the first aspect above.
[0009] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method described in the first aspect above.
[0010] It is understood that the beneficial effects of the second to fourth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description
[0011] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below.
[0012] Figure 1 This is a schematic flowchart of a product introduction method provided in an embodiment of this application; Figure 2 This is a flowchart illustrating step S200 in a product introduction method provided in an embodiment of this application; Figure 3 This is a flowchart illustrating step S300 of a product introduction method provided in an embodiment of this application; Figure 4 This is a flowchart illustrating the process after step S400 in a product introduction method provided in an embodiment of this application; Figure 5 This is a block diagram of a product introduction system provided in one embodiment of this application; Figure 6 This is a schematic diagram of a terminal device provided in an embodiment of this application. Detailed Implementation
[0013] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.
[0014] In the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.
[0015] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.
[0016] To illustrate the technical solution described in this application, specific embodiments are provided below.
[0017] Please see Figure 1 , Figure 1 This is a flowchart illustrating a product introduction method based on AR glasses provided in this application embodiment. In this embodiment, the execution subject of the product introduction method is a terminal device. It is understood that the types of terminal devices include, but are not limited to, mobile phones, tablets, laptops, Ultra-Mobile Personal Computers (UMPCs), netbooks, Personal Digital Assistants (PDAs), etc. This application embodiment does not impose any restrictions on the specific type of terminal device.
[0018] Please see Figure 1 The product introduction method provided in this application includes, but is not limited to, the following steps: In S100, real-time field-of-view image information and multiple historical question information of the target user are acquired.
[0019] Specifically, the terminal device can acquire real-time field-of-view image information and multiple historical question information of the target user based on the preset AR glasses. The real-time field-of-view image information is used to describe the target user's real-time field of view, and the historical question information is used to describe the questions that the target user has asked about the product.
[0020] In S200, the target object of interest is determined based on real-time field-of-view image information.
[0021] Specifically, after the terminal device acquires real-time field-of-view image information and multiple historical question information, the terminal device can determine the target attention object information based on the real-time field-of-view image information. The target attention object information is used to describe the object that the target user is paying attention to. For example, when the product is a new energy vehicle, the object can be a certain component, such as a door, hood, or tire.
[0022] In some possible implementations, for effectively determining the target interest information, please refer to [link / reference]. Figure 2 Step S200 includes, but is not limited to, the following steps: In S210, the region of interest is determined based on real-time field-of-view image information and preset field-of-view center region information.
[0023] Specifically, after the terminal device acquires real-time field-of-view image information and multiple historical question information, the terminal device can determine the central area of the real-time field-of-view image information as the area of interest based on the real-time field-of-view image information and the preset field-of-view center area information. The center point of the field-of-view center area information coincides with the center point of the real-time field-of-view image information, and the specific size of the field-of-view center area information can be customized.
[0024] In S220, based on a preset target detection algorithm, the information of the target object to be identified is determined according to the information of the region of interest.
[0025] Specifically, after the terminal device determines the region of interest information, it can determine the category of the object in the region of interest information based on a preset target detection algorithm, so as to effectively determine the target of interest information. The target detection algorithm can be the Faster R-CNN algorithm or the Transformer algorithm.
[0026] In S230, it is determined whether the duration of the central region of the information of the object to be monitored is greater than the preset duration threshold information.
[0027] Specifically, after the terminal device determines the information of the object to be of interest, the terminal device can determine whether the duration of the central region of the information of the object to be of interest is greater than the preset duration threshold information. The duration of the central region is used to describe the duration of the information of the object to be of interest in the central region of the real-time field-of-view image information.
[0028] In S240, if the duration of the central region of the pending object of interest information is greater than the duration threshold information, then the pending object of interest information is determined to be the target object of interest information.
[0029] Specifically, if the duration of the central region of the pending object of interest information exceeds the duration threshold, the terminal device can effectively determine the pending object of interest information as the target object of interest information.
[0030] In S300, based on the target interest information and multiple historical question information, predictive question information is generated corresponding to each historical question information.
[0031] Specifically, after the terminal device determines the target user's information, it can effectively generate predicted questions for each historical question based on the target user information and multiple historical questions. The predicted questions describe the questions that the target user is predicted to ask.
[0032] For some possible implementations, please refer to [link to relevant documentation] for efficient generation of predictive query information. Figure 3 Step S300 includes, but is not limited to, the following steps: In S310, based on a preset sampling time period, multiple historical question information of the target user is obtained.
[0033] Specifically, after the terminal device determines the target user's information, it can determine the questions the target user has asked during the preset sampling period and obtain multiple historical questions from the target user. The specific value of the sampling period can be customized.
[0034] In S320, based on a preset keyword extraction algorithm, the question keyword information corresponding to each historical question is determined according to each historical question information.
[0035] Specifically, after multiple historical question messages from the terminal device, the terminal device can determine the keywords corresponding to each historical question message based on a preset keyword extraction algorithm, such as "color", "lifespan" and "material", effectively determining the question keyword information corresponding to each historical question message. The keyword extraction algorithm can be either the TF-IDF algorithm or the TextRank algorithm.
[0036] In S330, based on the information of each question keyword and according to the information of the target audience, predictive question information corresponding to each question keyword is generated.
[0037] Specifically, after the terminal device determines the question keyword information, it can generate predicted question information corresponding to each question keyword information based on the target audience information, thereby generating multiple possible questions about the question keyword information around the target audience information.
[0038] In S400, based on multiple predicted question information, predicted answer information corresponding to each predicted question information is generated.
[0039] Specifically, after the terminal device generates the predicted question information, it can generate the predicted answer information corresponding to each predicted question information based on multiple predicted question information.
[0040] In some possible implementations, in order to shorten the thinking time of the presenter and reduce the waiting time of the target user, after step S400, the method may include, but is not limited to, the following steps: In the S500, information about the target audience and multiple predicted questions are sent to the presenter's corresponding terminal.
[0041] Specifically, after the terminal device generates the predicted answer information, it can send the target user information and multiple predicted questions to the presenter's corresponding terminal, which helps the presenter to quickly and comprehensively understand the target user's situation.
[0042] In some possible implementations, to help target users gain a more comprehensive understanding of the product, please refer to [link / reference]. Figure 4 After step S400, the method further includes, but is not limited to, the following steps: In S600, multiple component information is determined based on the predicted solution information.
[0043] Specifically, the terminal device can determine multiple component information based on the predicted solution information, whereby the component information describes the components involved in the predicted solution information.
[0044] In S610, based on the information of each involved component, image information of the involved component corresponding to each involved component is generated.
[0045] Specifically, after the terminal device determines multiple pieces of information about the involved components, the terminal device can generate image information of the involved components corresponding to each piece of information. The image information of the involved components is used to describe images pre-captured for the actual involved components.
[0046] In S620, an image set information to aid understanding is generated based on multiple image information involving components.
[0047] Specifically, after the terminal device generates image information involving components, it can generate an auxiliary understanding image set based on multiple images involving components, thereby helping the target user to further understand the product. The auxiliary understanding image set information is used to describe the collection of multiple images involving components.
[0048] The implementation principle of the product introduction method based on AR glasses in this application embodiment is as follows: The terminal device can first acquire the real-time field-of-view image information and multiple historical question information of the target user. Then, based on the real-time field-of-view image information, it quickly determines the target attention information. Next, based on the target attention information and multiple historical question information, it accurately generates predicted question information corresponding to each historical question information. Finally, based on multiple predicted question information, it effectively generates predicted answer information corresponding to each predicted question information. This enables the prediction of questions that the target user may ask, shortens the thinking time of the presenter, improves the accuracy of the presenter's answers, reduces the waiting time of the target user, effectively improves the user experience, and enhances the presentation effect.
[0049] It should be noted that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.
[0050] Embodiments of this application also provide a product introduction system based on AR glasses. For ease of explanation, only the parts relevant to this application are shown, such as... Figure 5 As shown, the system 50 includes: Real-time field-of-view image information acquisition module 51: used to acquire the target user's real-time field-of-view image information and multiple historical question information; Target interest information determination module 52: used to determine target interest information based on real-time field-of-view image information; Predictive question information generation module 53: used to generate predictive question information corresponding to each historical question information based on the target interest information and multiple historical question information; Predictive answer information generation module 54: Used to generate predictive answer information corresponding to each predictive question based on multiple predictive question information.
[0051] Optionally, the target interest information determination module 52 mentioned above includes: The Region of Interest Determination Submodule is used to determine the region of interest information based on real-time field-of-view image information and preset field-of-view center region information. The submodule for determining information on objects of interest to be identified is used to determine information on objects of interest to be identified based on a preset target detection algorithm and information about the region of interest. The central region duration determination submodule is used to determine whether the duration of the central region of the object to be monitored is greater than the preset duration threshold. The target interest information determination submodule is used to determine the target interest information if the duration of the central region of the pending interest information is greater than the duration threshold.
[0052] Optionally, the aforementioned predictive question information generation module 53 includes: Historical Question Information Acquisition Submodule: Used to acquire multiple historical question information of a target user based on a preset sampling time period; Question Keyword Information Determination Submodule: Based on a preset keyword extraction algorithm, this module determines the question keyword information corresponding to each historical question based on that historical question information. Predictive Question Information Generation Submodule: This module generates predicted question information corresponding to each question keyword based on the target audience information.
[0053] Optionally, the system 50 also includes: Target audience information sending module: Used to send target audience information and multiple predicted questions to the presenter's corresponding terminal.
[0054] Optionally, the system 50 also includes: Component Information Determination Module: Used to determine multiple component information based on predicted solution information; The component image information generation module is used to generate corresponding component image information based on the information of each component. Image set information generation module for auxiliary understanding: used to generate image set information for auxiliary understanding based on multiple image information of related parts.
[0055] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.
[0056] This application also provides a terminal device, such as... Figure 6 As shown, the terminal device 60 of this embodiment includes: a processor 61, a memory 62, and a computer program 63 stored in the memory 62 and executable on the processor 61. When the processor 61 executes the computer program 63, it implements the steps in the product introduction method embodiment described above, for example... Figure 1 Steps S100 to S400 are shown; or, when processor 61 executes computer program 63, it implements the functions of each module in the above-described device, for example... Figure 5 The functions of modules 51 to 54 are shown.
[0057] The terminal device 60 can be a desktop computer, laptop, handheld computer, or cloud server, etc., and includes, but is not limited to, a processor 61 and a memory 62. Those skilled in the art will understand that... Figure 6 This is merely an example of terminal device 60 and does not constitute a limitation on terminal device 60. It may include more or fewer components than shown, or combine certain components, or different components. For example, terminal device 60 may also include input / output devices, network access devices, buses, etc.
[0058] The processor 61 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.; the general-purpose processor can be a microprocessor or any conventional processor, etc.
[0059] The memory 62 can be an internal storage unit of the terminal device 60, such as the hard disk or memory of the terminal device 60. The memory 62 can also be an external storage device of the terminal device 60, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the terminal device 60. Furthermore, the memory 62 can include both internal storage units and external storage devices of the terminal device 60. The memory 62 can also store computer program 63 and other programs and data required by the terminal device 60. The memory 62 can also be used to temporarily store data that has been output or will be output.
[0060] One embodiment of this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium can include any entity or device capable of carrying computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.
[0061] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the methods, principles and structures of this application should be covered within the scope of protection of this application.
Claims
1. A product introduction method based on AR glasses, characterized in that, The method includes: Acquire real-time field-of-view image information and multiple historical question information of the target user; Based on the real-time field-of-view image information, the target object of interest information is determined; Based on the target interest information and multiple historical question information, generate predicted question information corresponding to each of the historical question information; Based on the multiple predicted question information, predictive answer information corresponding to each predicted question information is generated.
2. The method according to claim 1, characterized in that, The step of determining the target object of interest information based on the real-time field-of-view image information includes: Based on the real-time field-of-view image information and the preset field-of-view center region information, the region of interest information is determined; Based on a preset target detection algorithm, the information of the target object to be monitored is determined according to the information of the region of interest. Determine whether the duration of the central region of the object to be monitored is greater than a preset duration threshold. If the duration of the central region of the pending object of interest information is greater than the duration threshold, then the pending object of interest information is determined to be the target object of interest information.
3. The method according to claim 2, characterized in that, The step of generating predicted question information corresponding to each of the historical question information based on the target interest information and multiple historical question information includes: Based on a preset sampling time period, obtain multiple historical question information of the target user; Based on a preset keyword extraction algorithm, the question keyword information corresponding to each of the historical question information is determined according to each of the historical question information. Based on the question keyword information, and according to the target interest information, predictive question information corresponding to each question keyword information is generated.
4. The method according to claim 3, characterized in that, After generating predicted answer information corresponding to each of the multiple predicted question information, the method further includes: The target audience information and multiple predicted questions are sent to the presenter's corresponding terminal.
5. The method according to claim 1, characterized in that, After generating predicted answer information corresponding to each of the multiple predicted question information, the method further includes: Based on the predicted solution information, multiple component information is identified; Based on the information of each of the involved components, generate image information of the involved components corresponding to each of the involved component information; Based on the image information of multiple components involved, an image set information to aid understanding is generated.
6. A product introduction system based on AR glasses, characterized in that, The system includes: Real-time field-of-view image information acquisition module: used to acquire the target user's real-time field-of-view image information and multiple historical question information; Target interest object information determination module: used to determine target interest object information based on the real-time field-of-view image information; Predictive question information generation module: used to generate predictive question information corresponding to each of the historical question information based on the target interest information and multiple historical question information; Predictive answer information generation module: used to generate predictive answer information corresponding to each of the multiple predicted question information.
7. The system according to claim 6, characterized in that, The target interest information determination module includes: The attention area information determination submodule is used to determine the attention area information based on the real-time field-of-view image information and the preset field-of-view center area information. The submodule for determining information of objects of interest to be determined is used to determine information of objects of interest to be determined based on the information of the region of interest, according to a preset target detection algorithm. The central region duration determination submodule is used to determine whether the duration of the central region of the object to be monitored is greater than a preset duration threshold. The target attention object information determination submodule is used to determine the target attention object information as such if the duration of the central region of the target attention object information is greater than the duration threshold information.
8. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 5.
9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 5.