Systems, Platforms, and Methods for Personalized Shopping Using a Virtual Shopping Assistant

Abstract

The present disclosure provides apparatuses, systems, and methods for providing personalized online product try-on. In various embodiments, a personalized shopping system includes: an automated shopping assistant that accesses product data; a matching system that accesses historical data, preference data, and / or anatomical data measured using the automated shopping assistant device, wherein the personalized shopping system can generate a personalized match based on the historical data, preference data, and / or anatomical data. The automated shopping assistant device can include a depth sensor and / or an image scanner capable of capturing various 2D and / or 3D models. These models can be used to generate anatomical data. The anatomical data can be used to virtually try on various items. Products can be personalized based on the historical data, preference data, and / or anatomical data.

Description

[0001] Cross - Reference to Related Applications

[0002] This application claims priority to U.S. Provisional Patent Application No. 62 / 621,548, filed on January 24, 2018, entitled "A System, Platform and Method for Personalized Shopping using a Virtual Shopping Assistant", the disclosure of which is hereby incorporated by reference in its entirety. Technical Field

[0003] The present invention generally relates to methods, applications, and devices for personalized product shopping. Background Art

[0004] Currently, most shoe shopping still occurs in physical stores. Most customers are familiar with the limitations of traditional shopping, as are store managers and salesclerks. Typically, customers rely on shopping assistants to direct them to products, inform them of the location of in - stock products, provide assistance with product try - ons, and so on.

[0005] In addition, the typical shopping experience needs to be repeated as customers visit the same or different stores more or less each time, resulting in extremely low efficiency and user disappointment.

[0006] It would be highly advantageous to have a system or method that can achieve a highly accurate, user - friendly, automated or semi - automated try - on solution that can operate both online and in - store. Summary of the Invention

[0007] According to an embodiment of the present invention, there is provided an apparatus, system, and method for providing personalized online product try - on.

[0008] A method for personalized shopping has the following steps: an automated shopping assistant system accesses product data, a matching system accesses user historical data, the matching system accesses user preference data, the matching system accesses user anatomical data obtained from an automated shopping assistant device, and the automated shopping assistant system matches the user historical data, user preference data, and user anatomical data with the product data to generate a personalized matching system.

[0009] In some embodiments, the automated shopping assistant system matches the user historical and preference data with the product data to generate personalized product recommendations.

[0010] In some embodiments, the automated shopping assistant system can be used to enable users to order personalized products.

[0011] In some embodiments, an automated shopping assistant system can be used to provide simulations representing one or more anatomical features of a user.

[0012] In many embodiments, a user and one or more third parties can provide product fit feedback, and a user and one or more third parties can provide social feedback. The automated shopping assistant system can adjust personalized products based on the product feedback. The system can also provide anatomical data about the user, wherein the automated shopping assistant system also takes into account the anatomical data to generate a user shopping avatar that includes one or more features of the user.

[0013] The automated shopping assistant system can include a virtual try-on feature. In many embodiments, products are generated based on the avatar before the user orders a personalized product. User preferences can be selected from the group consisting of size, color, material, and type preferences.

[0014] According to some embodiments, a platform for personalized shopping is provided, which includes: a cloud-based server that includes a profile module for generating digital avatars for a plurality of users; a product module for incorporating product data of a plurality of products; and a matching module adapted to run code to match digital avatar data and product data to generate product recommendations; an end-user computing device communicatively connected to the cloud-based server, including an image capture element, wherein the matching module runs a software application to generate a user mobile shopping avatar based on the capture of at least a portion of the user's anatomy, and further for generating anatomical data for the digital avatar profile of the user.

[0015] In some embodiments, the platform is adapted to generate and / or present simulations representing one or more anatomical features of a user.

[0016] In some embodiments, the platform can have a product ordering module, a product customization module, a social shopping module, and / or a product try-on module, etc.

[0017] A handheld system for personalized shopping can have: a screen configured to receive user input; a device camera for capturing a standard image of the user's anatomy; and a processor having registers adapted to analyze anatomical data, product data, user history data, and user preference data, wherein the processor retrieves information from the registers and writes information to the registers, the processor is configured to match user history and preference data with product data to generate a personalized matching system, and the processor is configured to match user history and preference data with product data to generate a personalized product, and wherein the user can purchase the personalized product by providing user input to the screen.

[0018] In several embodiments, the system has a depth sensor configured to accurately determine the distance of an object from the sensor, and wherein depth sensor information is used to match preference data with product data. In some embodiments, the depth sensor is capable of providing a 3D scan of at least a portion of the body related to the user's anatomical profile so that the length, width, and depth of that portion of the body can be captured.

[0019] In some embodiments, the handheld system includes a software application running on the handheld system to generate and present a graphical simulation of a user's mobile shopping profile based on the capture of at least a portion of the user's anatomy.

[0020] A shopping assistant system for shopping using a shopping profile is provided, including: a shopping assistant virtual standing surface for generating a 3D user shopping profile based on the capture of at least a portion of the user's body by a camera device; a mobile device app for applying the user shopping profile in a store; a communication cloud-based shopping assistant server connected to a shopping assistant database; and a plurality of product tags for enabling a user to capture a selected product.

[0021] The shopping assistant system further includes one or more image scanners for capturing at least a portion of the body related to the user's anatomical profile so that the length, width, and depth of that portion of the body can be captured.

[0022] The shopping assistant system, wherein the shopping assistant standing surface includes one or more augmented reality (AR)-generated markers for assisting in capturing body part dimensions.

[0023] The shopping assistant system, wherein the shopping assistant virtual standing surface includes one or more augmented reality (AR)-generated 3D elements for assisting in positioning the body part to be scanned.

[0024] The shopping assistant system further includes a plurality of product tags associated with a plurality of products so that a user can shop by scanning one or more product tags.

[0025] The shopping assistant system further includes a shopping profile for each of a plurality of users for enabling a mobile device user to shop for another user using the other user's shopping profile.

[0026] A method for enhancing in-store shopping is provided, including: identifying a user entering a shopping area and positioning the user on a virtual standing surface of a shopping assistant; opening a new or known user profile; using one or more sensors to start capturing at least a part of the body; generating a 3D shopping profile of the user; sending the user shopping profile to the user's mobile device, where the user's mobile device can be used in a shopping assistant application; allowing the user to select a product of interest by scanning a product label using the user's mobile device; and providing shopping assistance for the selected product to the user.

[0027] The method further includes ordering the selected product using the user's mobile device.

[0028] The method further includes customizing the selected product using the user's mobile device.

[0029] The method further includes ordering the customized product using the user's mobile device.

[0030] The method further includes providing user product inventory information.

[0031] The method further includes trying on the selected product on the user shopping profile avatar.

[0032] The method further includes sending the tried-on user profile avatar to a social media system for viewing by selected associates connected to the user.

[0033] The method further includes enhancing the user shopping profile based on user behavior.

[0034] The method further includes providing shopping recommendations based on the user shopping profile and / or user shopping behavior.

[0035] The method further includes shopping in an online store using the user shopping profile.

[0036] The method further includes adding an additional user shopping profile to the mobile device.

[0037] The method further includes transferring the user's profile from an in-store device to the user's mobile device.

[0038] In many embodiments, a method for generating a user shopping profile using a virtual standing surface is provided, including: running a virtual shopping assistant application to instruct the user to prepare the environment for profile generation scanning; subsequently placing a reference object in an appropriate position; then capturing the environment (including the capture of the reference object) with their device camera and clicking on the captured reference object to define it as the reference object; providing a virtual assistant to further assist or guide the user to perform the scanning appropriately by using an AR reproduction drawn by the user on the virtual scanning surface or map; subsequently instructing the user to stand in a digitally superimposed virtual scanning mat; then starting the scanning; processing the scanning to form a user profile; and enabling the user to shop in a real or digital store by using the shopping profile. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The principles and operations of the systems, devices, and methods according to the present invention can be better understood with reference to the accompanying drawings and the following description. It should be understood that these drawings are provided for illustrative purposes only and are not intended to be limiting, where:

[0040] Figure 1A is a schematic system diagram depicting a system for facilitating personalized shopping according to some embodiments;

[0041] Figure 1B is a schematic system diagram depicting a platform for facilitating personalized shopping according to some embodiments;

[0042] Figure 2 is a flowchart showing a process for facilitating personalized shopping according to some embodiments;

[0043] Figure 3 is a flowchart for facilitating a personalized in-store shopping experience according to some embodiments;

[0044] Figure 4 is a flowchart for facilitating a personalized online shopping experience according to some embodiments;

[0045] Figure 5 is a flowchart showing an example of a personalized hybrid shopping experience according to some embodiments;

[0046] Figure 6 is a flowchart showing an example of personalized shoe shopping, either online or offline, according to some embodiments;

[0047] Figure 7 is a flowchart showing an example of personalized glasses shopping and manufacturing, either online or offline, according to some embodiments;

[0048] Figure 8A shows an exploded view of an example of a shopping assistant device according to some embodiments;

[0049] Figures 8B to Figure 8H show a set of views of an example of a shopping assistant device according to some embodiments;

[0050] Figure 9 show a shopping assistant system according to some embodiments;

[0051] Figure 10 is a flowchart showing an example of the combined use of a shopping assistant in a store device and a remote user communication device with a personalized shopping support application according to some embodiments;

[0052] Figure 11A and Figure 11B describe an example of the process of using a shopping assistant according to some embodiments;

[0053] Figures 12A to 12B is an example of a screenshot according to some embodiments, the screenshot showing an interactive screen on a shopping assistant screen for guiding a user to place their feet on a marked tablet;

[0054] Figures 13A to 13B is an example of a screenshot according to some embodiments, the screenshot showing an interactive guide displayed on a shopping assistant screen or a mobile screen for helping a user define their profile and their contact information;

[0055] Figures 14A to 14B is an example of a screenshot on a shopping assistant screen or a mobile screen according to some embodiments for showing a simulated reproduction of a scanned pair of feet and calves;

[0056] Figures 15A to 15B is an example of a screenshot on a shopping assistant screen or a mobile screen for helping a user input behavior-related information, which can be used to provide better user-related output;

[0057] Figures 16A to 16D show a set of views of an example of a shopping assistant standing surface according to some embodiments;

[0058] Figure 17 show an additional version of a shopping assistant standing surface according to some embodiments;

[0059] Figure 18 show another version of a shopping assistant standing surface according to some embodiments;

[0060] Figure 19 show a first user scenario according to some embodiments, where a virtual graphical example showing the use of a shopping assistant device is provided;

[0061] Figure 20Shows a second user scenario according to some embodiments, where a virtual graphical example showing the use of a shopping assistant device is provided;

[0062] Figure 21 Is a picture showing an example of a user located on a shopping assistant device according to some embodiments;

[0063] Figures 22A to 22J Is an example of a screenshot and a teaching screen according to some embodiments, the screenshot and the teaching screen showing a series of steps for guiding a user to use a virtual scanning pad; and

[0064] Figure 23 Is a flowchart depicting the step flow in the generation and use of a virtual shopping profile according to some embodiments. Detailed Description

[0065] The following description is presented to enable a person having ordinary skill in the art to make and use the invention provided in the context of a particular application and its requirements. Those skilled in the art will appreciate various modifications to the described embodiments, and the general principles defined herein may be applied to other embodiments. Thus, the invention is not limited to the particular embodiments shown and described, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein. In other instances, well-known methods, procedures, and components have not been described in detail so as not to obscure the invention.

[0066] As used herein, the term "try on" may refer to trying on a product, viewing the tried-on product, and modifying the product according to the physical parameters of a specific person's body or otherwise. The term "avatar" may refer to an anthropomorphic, iconographic, modeled, and / or graphical representation of a specific person, specifically, a person on a screen.

[0067] By optionally providing accurate size recommendations to customers based on a simulation or avatar model of the customer's foot for each shoe model, the relatively low online shopping rate for shoes can be increased, thereby enhancing the customer's purchasing confidence.

[0068] Non-limiting embodiments of the present invention include systems, platforms, and methods for facilitating highly personalized shopping (including effective try-on of products) online and / or in-store. In some embodiments, systems, platforms, and methods for enabling personalized manufacturing of products are provided.

[0069] Now refer to Figure 1A , Figure 1A Is a schematic system diagram depicting a system 100 for facilitating personalized shopping according to some embodiments. The system 100 enables seamless shopping in a store and / or online using a highly accurate user shopping profile and / or avatar generated by an automated shopping assistant device. In some cases, data processing is performed on a cloud and / or a local automated shopping assistant device.

[0070] As can be seen, the personalized shopping system 100 includes a platform 105 for personalized shopping profile management. The platform 105 may include a digital avatar profile module 110, a digital product file module 115, a product selection module 120, a product try-on module 125, a social shopping module 130, a product ordering module 135, and a product customization module 137.

[0071] The platform 105 communicates with a communication cloud 140. The communication cloud 140 may include a physical profile data module 145 communicatively connected to activate a tablet, kiosk, or automated shopping assistant device 185. The communication cloud 140 is further communicatively connected to a user 180 to provide physical user data, such as from 2D and / or 3D scans or other digital measurement sources. The communication cloud 140 may also include a user preference data module 150, which is communicatively connected to the automated shopping assistant device 185 and / or 180 to provide user preference data. The communication cloud 140 may also include a product file data module 160, which is communicatively connected to a product database 165 and a product matching data module 170. The product matching data module 170 includes a product matching algorithm communicatively connected to a product database 175.

[0072] In some embodiments, the device 185 includes one or more imaging devices, such as 2D and / or 3D cameras, which may be mobile or static components. The device 185 may also include one or more sensors, such as proximity sensors, scanners, cameras, pressure plates, and / or other sensors.

[0073] It can be seen that the digital avatar profile 110 is highly personalized and is constructed from various data sources directly or indirectly from the user or representing physical and / or mental, emotional, psychological characteristics. The digital avatar profile 120 typically includes a file or a set of files and data points from which instructions can be executed to enable the generation of a high-resolution user profile or avatar from one or more data sources. In addition, the product selection module 120 typically matches the personalized avatar profile 110 with the selected digital product online or offline. The calculation of the matching algorithm can be performed by a processor through the storage, retrieval, and processing of data. In some embodiments, one or more device registers can be used, where a register refers to one of a small group of data storage locations that are part of a computer processor and are used to hold computer instructions, storage addresses, or any kind of data. In some embodiments, the matching algorithm can include running code to provide a perfect or near-perfect match between the product type, size, style, model, etc. provided by the product database and the physical parameters and / or user preference data defined by the user avatar profile, at least based on a scan of at least a part of the user's body related to the user profile. For example, User A has a foot profile defined by size, width, and depth. In addition, the user's profile can include preference data such as preferred style, shoe type, and color, such as blue or gray sports shoes. The product database can include, for example, blue, gray, and blue-gray sports shoes that are precise or close enough to the user's size, width, and depth. In this case, the matching algorithm matches the profile definition with one or more products in the product database that match the user profile.

[0074] By using the product try-on module 125 to provide system feedback and product try-on data, as well as social shopping data from the social shopping module 130, the product selection module 120 can be further improved. In some embodiments, the product try-on module includes means for feedback from a shopper's shopping assistant or supporter. In many embodiments, the product try-on module includes means for feedback from a virtual shopping assistant or supporter, such as a communicatively connected supporter, a digital or virtual mirror or screen that shows the product to the user. Additionally, the product customization module 137 can receive data from the product try-on module 125 and / or the social shopping module 130 to help further personalize the product being considered for acquisition based on the digital avatar and the product try-on module 125 and / or the social shopping module 130. The product customization module 137 can enable the user to change or customize the product being tried or tested, for example, by changing the product color, shape, design, size, material, etc. In this way, the product to be ordered can be constructed according to user-specific or customized requirements. Additionally, the product customization module 137 can send the customized product selected or generated by the user to the product selection module 120, after which the product selection module 120 can initiate an order for the customized product via the product ordering module 135. Moreover, the user updates included in the user changes made in the product selection module 120 can be used to update the digital avatar profile 110, thereby keeping the user avatar profile updated, for example, updates to user body changes, preference changes, etc.

[0075] The product selection module 120 includes a file or a set of files and data points from which instructions can be executed to perform commands so that a high-resolution user profile or avatar is matched with products having a high try-on rating for the shopping survey being performed on each system user. The product selection module can also integrate the feedback generated in the system module to continuously improve the accurate product recommendations it provides. Using various technical processes performed on the avatar, such as integrating volume, cross-sectional area, and perimeter, as well as length, width, height, and additional distances, the system can represent the avatar as an array of numbers. In some embodiments, this array of numbers can represent various elements of the avatar to allow comparison with similar elements of the products tried on by the avatar. Thus, when comparing the avatar data, which can be enhanced using recommendation algorithms and machine learning techniques, etc., with the product data from the product files, this can allow for accurate, continuously improving, and personalized product recommendations from the system.

[0076] According to some embodiments, a relatively low-level integration of a 3D scanner can be utilized to generate a digital avatar profile. In some examples, the sensors or scanners that can be used can include structured light, time of flight, photogrammetry, or any other type of 3D and / or 2D scanning technology. Suppliers of such technology include, but are not limited to, PrimeSenseTM-based scanners, Occipital Structure sensors, 3D Systems Sense sensors, iSense sensors, IntelTM RealSense sensors (standalone or machine-integrated), iPad- or tablet-based scanning platforms, PCs (integrated and external), Android + RealSense (next generation) devices, and Google Project Tango devices, among others.

[0077] Now referring to Figure 1B , Figure 1B , which is a schematic system diagram depicting a platform 180 for facilitating personalized shopping according to some embodiments. As can be seen, the personalized shopping platform 180 includes one or more user mobile devices 182, such as smartphones or tablets, including, but not limited to, cameras, applications, and data connections; store computing devices or point-of-sale computing devices, kiosks, or automated shopping assistant devices 184, typically located at or near the store, such as electronic devices with one or more cameras, sensors, or scanning devices, applications, and data connections; wherein the mobile devices 182 and / or the automated shopping assistant device 185 are connected to a communication cloud 186. The communication cloud 186 includes: a digital product module 190 for storing, merging, and managing data of multiple products; a digital avatar profile module 188 for storing, merging, processing, and managing profile data of multiple users; and a matching module 192 for matching product and avatar profile data to assist in product recommendations and other matching functions. The platform 180 also includes a product customization module 194 for ordering customized products based on the output of the matching module and / or user selection; and a product ordering module 196 for enabling the ordering of products based on the output of the matching module and / or user selection.

[0078] Now referring to Figure 2 , Figure 2is a flowchart showing a process for facilitating personalized shopping (both online and offline) according to some embodiments. It can be seen that product information from the product database 200 can be used for products to be discovered, purchased, or manufactured. At step 205, historical data of the user can be retrieved, for example, based on previous user purchases and research. At step 210, user preference data such as size, color, material, type preference, etc. can be obtained. At step 215, scanned or graphical data can be obtained for the user, for example, from standard photos, 2D and / or 3D image scans, or from capture and processing using a POS kiosk or an automated shopping assistant device, etc. This graphical data is used by the personalized shopping system to generate a physical profile of the user based on the user's physical attributes. At step 220, by processing various input data from steps 205, 210, and 215, a multi-dimensional user shopping profile (hereinafter referred to as the user shopping avatar) can be developed, thereby generating a user shopping avatar or profile that includes the user's physical attributes as well as user behavior and user preference data. The profile or avatar is a dynamic structure that can optionally use feedback and additional input from steps 205, 210, and / or 215 to continuously improve in a way that animates, reflects, or represents the user. In one implementation, the user avatar can be used to match the user with potential products in a single store and / or in multiple stores (e.g., any chain store in a network or any online retail store, or an affiliate of an online and / or offline store or platform).

[0079] At step 225, a match between the user shopping profile and the product being studied or needed is performed. In this step, according to the specific user shopping profile, product data from the product database 200 is matched with the product the user is studying, so that products that are not suitable for a specific user can be highly filtered and suitable products can be highly matched according to the specific user's personal shopping profile and preferences. The matching step can be supplemented by providing recommendations for the user to the product matching process based on the above user profile.

[0080] At step 230, product fitting data from feedback of in-person or remote people can be used to help modify the matching of user data and product data. For example, feedback from salespersons in a store can be used to update the user profile, or feedback from remote people connected via, for example, a smart phone or computer can be used to update the user profile. In some cases, for example, users can use feedback from salespersons or friends (such as which colors look good on a person or which size looks most fitting, etc.) to update their shopping profiles. In some cases, users can use advanced graphics processing and 3D rendering to virtually try on the product under study, so that users can see themselves wearing the product based on a digital simulation of placing the product on the user's shopping avatar. In some cases, the system can provide static or dynamic high-resolution visual outputs, such as, optionally, an animated avatar or character suitable for the avatar, the presented pictures, and / or the visual representation of the recommendation. For example, such a reproduction can allow the user to see the product being tried on to be depicted on the avatar, thus helping the user to visualize details such as fit, tightness, color, style, material, etc. based on, for example, a color heat map. For example, when the product contacts the body, the color heat map can be used to indicate areas such as tightness, tension, friction, etc. As described above, users can use the shopping avatar to provide further feedback to modify the user's shopping profile. At step 235, feedback can be obtained from the social network the user is connected to or direct third-party feedback to help modify the user's shopping profile.

[0081] At step 237, product customization can integrate data from the product fitting feedback of step 230 and / or the social feedback of step 235 to help further personalize the product being considered for acquisition according to the digital avatar and the product fitting module 125 and / or the social shopping module 130.

[0082] At step 240, the user can order a personalized product, either within a physical store or an online store. Additionally, a personalized product can be ordered from a manufacturer, who can produce the product based on the user's request such that the product is a one-time customized product for the user. The customized product can include, for example, various types of customization, including material type, print sample, color, size, volume, angle, model variation, style, private customization, etc.

[0083] Now refer to Figure 3 , Figure 3is a flowchart for facilitating a personalized offline (in-store) shopping experience according to some embodiments. As can be seen, at the backend or computing system that supports the physical store, product information from the product database 300 can be used for products discovered, purchased, or manufactured by online users. In some embodiments, the product database is associated with a product data processing module that is adapted to perform high-intensity calculations at the local point-of-sale device and / or on the cloud according to types and requirements. At step 305, the historical data of the user can be retrieved, for example, based on the previous purchases of the user in the store or chain store. At step 310, user preference data such as size, color, material, type preference, etc. can be obtained. At step 315, at the front end or the user side, scan or graphic data can be obtained for the user, for example, from a standard photo, 2D and / or 3D image scanning, or from the capture and processing using a POS kiosk or device, etc. In some embodiments, a dedicated or general application on a smart phone, tablet, or other computing device can be used to achieve effective shooting or scanning by the user. In several embodiments, a shopping assistant, helper, salesperson, and / or colleague can use a dedicated or general camera or scanning device, kiosk, or standing platform (mobile or stationary). At step 320, this geometric data, together with various input data from steps 305 and 310, is used by the personalized shopping system to generate a multi-dimensional user shopping avatar or profile that includes the user's physical attributes as well as user behavior and user preference data.

[0084] At step 325, a match between the user shopping profile and the product being studied or desired is performed. In this step, according to the specific user shopping profile, the product data from the product database 300 is matched with the product requested by the user. The matching step can be supplemented by providing recommendations for the user to the product matching process based on the above user profile, so as to be able to perform advanced filtering on products that are not suitable for a specific user and advanced matching on suitable products according to the specific user's personal shopping profile and preferences. This advanced filtering enables presenting approximately suitable products, optionally currently available products, to, for example, the store salesperson or the user himself / herself, rather than letting the user select unsuitable items, thus wasting the time and resources of the shopping assistant and the shopper himself / herself. This also allows the user to benefit from the matching and recommendation data generated for other avatars or users, who can optionally share similar characteristics anonymously, thus achieving more intelligent and accurate matching and / or recommendation.

[0085] At step 330, product fitting data from feedback of in-person or remote people can be used to help modify the matching of user data and product data. For example, feedback from sales staff in a store can be used to update the user profile, or feedback from remote people connected via, for example, a smart phone or computer can be used to update the user profile. In some cases, for example, users can use feedback from sales staff or friends (such as which colors look good on a person or which size looks most suitable, etc.) to update their shopping profiles. At step 335, active and / or passive methods can be used to obtain feedback from the user. For example, when the system receives actual feedback from one or more in-person people and / or one or more remote people regarding fitting (such as good / bad / unacceptable level) or other aspects, active input of feedback occurs. Such feedback can allow the user to input the selected options into the system via, for example, a text box or text input element. The user can input the selected size, type, or other preferences into the text box or text input element. Passive feedback can occur when the system receives actual feedback regarding fit or other aspects from sales information, returns, etc., or by trying certain types, colors, sizes, etc., enabling the system to learn from the user's past choices and behaviors to further improve the avatar as well as product information and fitting for other users. In some cases, users can use advanced graphics processing and 3D rendering to try on the product being studied, enabling the user to virtually see themselves wearing the product based on a digital simulation of placing the product on the user's shopping avatar. As described above, users can use the shopping avatar to provide further feedback to modify the user's shopping profile.

[0086] At step 340, the user can order personalized products from a physical store. For example, for products that are available in principle but not currently in the store, or to enable the manufacture of specially requested products based on the user's shopping avatar, such that the product is a one-time custom product for the user.

[0087] At step 345, the user can select personalized products and / or modify or design the product, optionally purchasing a custom product that will be created and / or manufactured for her / him based on products she / he has seen, liked, and selected in the store. These modifications can include visual changes (such as name engraving, color, material, printing, etc.) and physical properties (such as controlling the height of the shoe heel, the thickness of the eyeglass frame, etc.). At steps 340 and 345, these features can allow in-store customers to enjoy features typically limited to e-commerce and online shopping.

[0088] Now refer to Figure 4 , Figure 4A flowchart for facilitating a personalized online shopping experience according to some embodiments is shown. It can be seen that an online store can obtain product information from a product database 400 for selecting products to offer to online users. At step 405, historical data of an online user can be retrieved, for example, based on previous user purchases and research. At step 410, user preference data such as size, color, material, type preference, etc. can be obtained. At step 415, scanned or graphical data can be obtained for the user, for example, from standard photos, 2D and / or 3D image scans, or from capture and processing using a POS kiosk or device, etc. In some embodiments, a dedicated or general-purpose application on a smart phone, tablet, or other computing device can be used to enable effective shooting or scanning by the user. In many embodiments, a web camera, 3D camera, video recorder, etc. can be used to obtain scanned or graphical data. At step 420, this graphical data, together with various input data from steps 405, 410, and 415, is used by the personalized shopping system to generate a multi-dimensional user shopping avatar or profile, which includes user physical attributes as well as user behavior and user preference data.

[0089] At step 425, a match between the user shopping profile and the product being researched or desired is performed. In this step, product data from the product database 400 is matched with the product the user is researching according to a specific user shopping profile, enabling advanced recommendations for product matching based on the specific user's personal shopping profile and preferences, for example, to help filter out products that are not suitable for a specific user and perform advanced matching for suitable products.

[0090] At step 430, product try-on data from feedback from remote persons such as family members, friends, or shopping assistants connected via a smart phone or computer can be used to help modify the matching of user data and product data to include, for example, data on which colors look good on a person or which sizes look most fitting, which the user can utilize to update their shopping profiles. In additional examples, codes can be used to provide product color recommendations, size or fit recommendations, etc. The feedback can be actively or statically collected from the user, for example, based on purchase information, shipping and return shipping data, etc. At step 435, feedback can be obtained from a social network or a social network the user is connected to, to help modify the user shopping profile. Additionally, person- and / or machine-based digital representatives, style experts, and / or additional guidance information can be input to improve the guidance and support provided to shoppers during the online purchase process. In some cases, advanced graphics processing and 3D rendering can be used to enable the user to virtually try on the product under study, such that the user can see themselves wearing the product based on a digital simulation of placing the product on the user's shopping avatar. This can be done using real-time simulation, considering a live stream of an animated video or a high-resolution image of the simulation. In some embodiments, "digital try-on" can include physical simulation to include precise positioning of elements on a static or moving avatar. As described above, the user can use the shopping avatar to provide further feedback to modify the user's shopping profile.

[0091] At step 440, the user can order a product from an online store. Optionally, at step 445, the user can generate a personalized product from the online store such that a specially requested product can be manufactured based on the user's shopping avatar, such that the product is a one-of-a-kind custom product for the user. In the case of custom production output, if needed, the shopping system can be directly connected to the company's production hardware and ERP system to facilitate such personalized product manufacturing. In one example, the personalized product can be represented in a 3D printer file such as an STL model or a digital cutting device file such as a DXF or DWG file. In many embodiments, this can be a custom routing card or production instructions and BOM files. Additional inputs can include visual renderings that will help the product manufacturer or printer visually design the custom product.

[0092] In some embodiments, data from the product database 400 can be used with the body or avatar profile exported in step 420 to develop a custom product at step 445, optionally without product matching at step 425.

[0093] Now refer to Figure 5 , Figure 5A flowchart showing examples of personalized hybrid shopping experiences according to some embodiments is presented. As can be seen from the figure, at the backend or computing system that supports physical stores and / or online stores, product information from the product database 500 can be used for products discovered, purchased, or manufactured by online users or in-store users. At step 505, user historical data can be retrieved, for example, based on previous user purchases in a store or chain store (whether online experience and / or in-store experience). At step 510, user preference data such as size, color, material, type preference, etc. can be obtained. At step 515, at the frontend or user side, user scan or graphical data performed by the user or a shopping assistant can be obtained according to, for example, a standard photo, 2D and / or 3D scans, or according to capture and processing using a POS kiosk, etc. In some embodiments, a dedicated or general-purpose application on a smartphone, tablet, or other computing device can be used to achieve effective shooting or scanning by the user. In many embodiments, the shopping assistant can use a dedicated or general-purpose camera or scanning device, which can include portable or non-portable devices, kiosk types, or stand-alone devices. At step 520, this graphical data, together with various input data from steps 505, 510, and 515, is used by the personalized shopping system to generate a multi-dimensional user shopping avatar or profile, which includes user physical attributes as well as user behavior and user preference data. One advantage of the system is seamless conversion, where the user can switch between online and offline shopping while enjoying the benefits of personalization through the use of an ever-updated personal profile in online and / or in-store scenarios.

[0094] In some embodiments, at step 525, for online shopping optionally located in a physical store, a match between the user shopping profile and the product being studied or needed is performed. In this step, according to the specific user shopping profile, product data from the product database 500 is matched with the product requested by the user, enabling advanced filtering of products that are not suitable for a specific user and advanced matching of suitable products based on the specific user's personal shopping profile and preferences. This advanced filtering enables presenting approximately suitable products, optionally currently available products, to, for example, store salespersons or the user themselves, rather than having the user select unsuitable items, thus wasting the time and resources of the shopping assistant and / or the shopper themselves.

[0095] At step 530, product fitting data from in-person or remote personnel feedback can be used to help modify the matching of user data and product data. For example, feedback from sales personnel in a store can be used to update the user profile, or feedback from remote personnel connected via, for example, a smart phone or computer can be used to update the user profile. In some cases, for example, users can use feedback from sales personnel or friends (such as which colors look good on a person or which size looks most fitting, etc.) to update their shopping profiles. At step 535, feedback can be obtained from a social network or a social network the user is connected to, to help modify the user shopping profile. In some cases, users can use advanced graphics processing and 3D rendering to virtually try on the product being studied, such that the user can see themselves wearing the product based on a digital simulation of placing the product on the user's shopping avatar. As described above, users can use the shopping avatar to provide further feedback to modify the user's shopping profile.

[0096] At step 540, an online user can order a product in a physical store. At step 550, an online user can order a personalized product in a physical store (for example, a product that is in principle available but not currently in the store), or enable the manufacture of a specially requested product based on the user's shopping avatar, such that the product is a one-time customized product for the user.

[0097] In some embodiments, at step 545, for a user in a physical store, the matching of the user shopping profile with the product being studied or needed is performed. In this step, according to the specific user shopping profile, the product data from the product database 500 is matched with the product requested by the user, so as to be able to perform advanced filtering on products that are not suitable for a specific user and advanced matching on suitable products according to the personal shopping profile and preferences of the specific user. This advanced filtering enables presenting approximately suitable products, optionally currently available products, to, for example, store sales personnel or the user themselves, rather than having the user select unsuitable items, thus wasting the time and resources of the shopping assistant and / or the shopper themselves.

[0098] Now refer to Figure 6 , Figure 6A flowchart showing an example of online or offline personalized shoe shopping according to some embodiments is presented. As can be seen from the figure, insole information can be obtained from the insole product database at 600. Additionally, last information can be obtained from the last product database at 605. In some cases, the inner sole data, last data, and / or shoe model data may include data regarding the shape, volume, shoe material, closure type, shoe type, width, length, height, thickness, material elasticity, comfort fit, etc. of each product. In some examples, mesh analysis and digitization can be provided. For instance, to run a mesh analysis of each 3D last, which combines 2D DXF data, and will be added to the last database 605. Additionally, shoe model data of the shoe to be discovered, purchased, or manufactured can be obtained from the shoe model database 610. In some cases, for example, a 3D STL file can be imported for the last, while a 2D DXF file can be imported for the bottom of the last.

[0099] At step 615, scanned or geometric data can be obtained for the user, for example, from a standard photograph, 2D and / or 3D image scanning, or from capture and processing using an automated shopping assistant device, etc. This graphical data can be processed at 620 by a personalized shopping system either in the cloud or within the unit itself to generate a physical profile of the user based on the user's physical attributes. The profile can include all or some of the following attributes: a 3D mesh (including the exact geometry of the profile), a 3D mesh of the exact geometry (including one or more parts of the user's body), a 2D image, attributes calculated according to one or more input methods (including specific volumes, cross-sectional measurements, specific distances and lengths, and non-numerical attributes such as preferences, etc.). For example, the user's single foot or both feet are photographed or scanned while standing on or near a reference object on the floor or another surface. In addition, the user's single foot or both feet can be scanned by a camera that scans at different angles around the foot, or by the person moving back and forth around the camera, thereby generating a 3D model, video, or series of pictures as a reference. The scanned data can generally be processed, optionally including interpolation and / or cleaning (to allow object recognition and mesh generation), or other suitable processing means. In some cases, meshing can also enable the removal of redundant geometry and / or fixing of mesh errors, for example, including separating, identifying, and preparing each of the two feet, removing the floor, pants, or other redundant materials from the scan, etc. In some cases, the processing of the scanned data can allow foot alignment (which also helps in the separation or personalization of the two feet) to provide accurate measurements of the two feet, including dimensional analysis (used to determine the length, width, and height of general and specific areas) and cross-sectional analysis (used to determine the area, perimeter, and other dimensions at a specific cross-section). The scanned data processing can allow the smoothing of the edges of the scanned foot, the construction of missing volumes, the construction of the sole of the foot, etc. In some cases, the total foot volume and / or region-specific volumes can be extracted from the model as additional information. At step 625, the processed user scan data can be parameterized to, for example, extract exact lengths, widths, heights, arches, metatarsal heads, cross-sections, perimeters, volume dimensions, etc. These parameters can be calculated from the clean 3D mesh using specific algorithms. For example, the calculation of the arch height of a model scanned in a standing position is complex and can be based on the comparison of the XYZ parameters of various anatomical parts on different cross-sections of the center of the foot. The width of the foot can be calculated based on the volume of the foot covering calculated at the 3D mesh and 2D cross-section levels. The length of the foot can be calculated based on the combination of the total length and the "metatarsal head length", which represents the distance between the heel and the first metatarsal. In addition, user-specific conditions (such as pain, infection, injury, etc.) can be identified and integrated into the user's shoe shopping profile. At this step, the pronation or supination state of the foot can also be analyzed. Additionally, the arch of the foot can be identified and measured to try on a supportive insole or other prosthetics.

[0100] At step 630, historical data of the user can be retrieved, for example, based on previous user purchases in a store or chain store (whether an online experience and / or an in-store experience). At step 635, user preference data such as size, color, material, type preference, etc. can be obtained. At step 640, by processing various input data from steps 615, 620, 625, 630, and 635, a multi-dimensional user shoe shopping profile (hereinafter referred to as a user shopping avatar) can be created, thereby generating a user shoe shopping avatar or profile including the user's physical attributes as well as the user's behavior and user preference data. In some embodiments, the user's shoe shopping profile includes the user's two feet (usually different), and parameters are determined separately for these two feet, so as to benefit from the separate profiles of the left and right feet.

[0101] At step 645, a match between the user shoe shopping profile and the shoe product being inspected, studied, or needed is performed. In this step, according to the specific user shopping profile, product data including dimensions from product databases 600, 605, and 610 is matched with the product being studied by the user, so as to be able to perform advanced filtering on products that are not suitable for the specific user and advanced matching on suitable products according to the personal shopping profile and preferences of the specific user. The matching step can be supplemented by providing recommendations for the user based on the above profiles of the matching process. This step can directly use the models of the digital profiles of the feet and shoes, and / or parametric digital models.

[0102] At step 650, product fitting data from feedback of a person present or a remote person can be used to help modify the match between the user data and the product data. For example, feedback from a salesperson in a store can be used to update the user profile, or feedback from a remote person connected via, for example, a smart phone or a computer can be used to update the user profile. In some cases, for example, the user can use the feedback of a salesperson or a friend (such as which colors look good on a person or which size looks most suitable, etc.) to update their shopping profile. In some cases, the user can use advanced graphics processing and 3D rendering to try on the product being studied, so that the user can see themselves virtually wearing the product according to the digital simulation of placing the product on the user shopping avatar. As described above, the user can use the shopping avatar to provide further feedback to modify the user's shopping profile. At step 655, feedback can be obtained from the social network connected by the user to help modify the user shopping profile.

[0103] At step 660, a user may order a pair of personalized shoes either within a physical store or an online store. Additionally, personalized products can be ordered from a manufacturer that can produce products based on the user's requests such that the products are one-time custom-made products for the user. The customized footwear can be customized and / or personalized, for example, in one or more of the following ways: shape (e.g., size, length, geometry, and / or volume), design (e.g., color, pattern, imprint, and / or material), or any other specification or combination thereof.

[0104] Now refer to Figure 7 , Figure 7 is a flowchart showing an example of online or offline personalized eyewear shopping and manufacturing according to some embodiments. The eyewear may include, but is not limited to, sunglasses and any type of optical glasses. As can be seen from the figure, at 700, eyewear model information from an eyewear product database can be obtained from eyewear models or product databases of various file types or data structures. According to some embodiments, the eyewear frame acquisition can be achieved by preparing a parametric model (e.g., by generating model parameters for multiple input types, processing resolution adjustment, implementing automatic rigging and skinning, integrating the range of motion animation, and correcting shape keys, etc.).

[0105] At step 705, the user's historical data can be used, which may include, for example, facial anatomical landmarks and measured distances such as pupil distance, the positions of each eye, cheek, temple, and various points on the ear and nose, etc. General parameters for each face are also loaded, and the general parameters may optionally include volume, proportion, and standard shape, and the general parameters for each face can be retrieved, for example, based on previous user surveys and / or purchases in a store or chain store, from online and / or store experiences. At step 710, user preference data such as size, color, material, type preference, usage requirements, etc. can be obtained. This data can be obtained directly or indirectly, for example, using purchase information, questionnaires, forms, and / or any other data acquisition method.

[0106] At step 715, scanned or graphical data can be obtained for the user, for example, from a standard photograph, 2D and / or 3D image scans, or from capture and processing using an automated shopping assistant. This includes, for example, any type of 3D scanning technology described in the foregoing section, or alternative 2D methods with or without reference objects for sizing. Generally, user head and face scan data can be obtained at this stage. In some embodiments, head and face model preparation and analysis can include model preparation, such as smoothing and cleaning, reconstructing a mesh with enhanced topology and / or optimized detail / weight ratio compression for real-time optimized display, and / or orientation and alignment. Additionally, facial feature recognition can be used, for example, to generate a facial model presented from multiple angles (e.g., 3 to 15 angles to help determine normals, depth, color). Further, computer vision and / or machine learning algorithms can be applied to identify, for example, eyes, nose, nasal bridge, temples, ears, etc. Processing of the scan data can also include projection of 2D landmarks onto the 3D model, and verification of anatomical landmarks. In the absence of landmarks, an assessment based on statistical or empirical results can be applied to the replacement of these landmarks.

[0107] At step 720, the processed user scan data can be parameterized to, for example, extract precise facial length, width, height, proportions, nose width and volume, ear size, ear height, ear position, skin color, and / or other relevant facial features and dimensions, etc. At 725, the personalized shopping system can process this data along with the user's historical data from 705 and the user preference data at 715 to generate a user's glasses shopping profile based on the user's facial profile and other physical attributes as well as user behavior and user preference data. In some embodiments, the user's glasses shopping profile includes the user's two eyes (which are usually different) to benefit from separate profiles for the left and right eyes. In some embodiments, pictures, electronic forms, or in-app embedded testing methods will be used to collect the optical prescription, or in some cases, the optical prescription will be collected from an external prescription file. According to some embodiments, the system can recommend specific models based on facial shape, previous purchases and history, and optionally based on comparison with similar avatars (optionally anonymously).

[0108] At step 730, a match is performed between the user's glasses shopping profile and the glasses products being studied or needed. In this step, according to the specific user shopping profile, the product data from the product database 700 is matched with the products the user is studying, enabling advanced filtering of products that are not suitable for a specific user and advanced matching of suitable products according to the specific user's personal shopping profile and preferences.

[0109] At step 745, frame customization is used to adjust each frame to fit the user's face. Frame customization can include, for example: taking key measurements of the subject or the user's face; applying an iterative comparison algorithm to adjust the frame for the face; digitally positioning the frame on the object's face according to each prepared user eyewear shopping profile or avatar, etc., properly orienting the frame to the face, scaling the size, width, and position of the bridge of the nose, adjusting the temple fold, temple length, and wide-angle tilt or angle of the glasses according to the object's face, etc.

[0110] At step 735, product try-on data from feedback from in-person or remote personnel can be used to help modify the matching of user data and product data. For example, feedback from a salesperson or optometrist in a store can be used to update the user profile, or feedback from a remote person connected via, for example, a smartphone or computer can be used to update the user profile. In some cases, for example, the user can use feedback from a salesperson or friend (such as which colors look good on a person or which size, style, type looks most suitable, etc.) to update their shopping profile.

[0111] In some embodiments, at step 745, advanced graphics processing can be used for the user to virtually try on the product being studied, so that the user can see himself / herself wearing glasses based on a digital simulation of placing the glasses on the face of the user's shopping avatar. In some embodiments, virtual try-on can include features such as physical simulation that positions the glasses in the correct or optimal position and can slide the glasses along the nose. Additionally, the try-on can include the overlay of pictures or 3D models on the facial model and / or a series of pictures or any combination of the above. Animation effects can be included to emphasize different attributes of the glasses, including custom animations in the case of customizing the frame, or other animations such as fly-in / fly-out animations for switching between pairs of glasses. As described above, the user can use the shopping avatar to provide further feedback to modify the user's shopping profile. In some embodiments, the user can view the customized frame on a digital version of his / her face to provide in-depth visual feedback. For example, the user's face can be displayed in a 3D viewer, and the appearance can be enhanced to provide one or more of 3D view operations (such as zooming, rotating) and animation effects to cater to the user experience, such as a breathing face, smiling, blinking, or other animated or static visual effects. In addition, customization options can thus be provided to the user, including: selecting any frame from a collection, customizing the frame and lens colors, customizing the automatically recommended try-on ability, personalizing documents (such as text, prescriptions, etc.), and implementing side-by-side comparisons between different frames. At step 740, feedback can be obtained from a social network or a social network to which the user is connected to help modify the user's shopping profile. Of course, other steps in the step combination can be used to process the input data.

[0112] Step 750 involves various embodiments where the system enables the production of customized glasses to fit the user based on an automated or semi-automated parametric design of the frame. At step 750, if needed, the system can prepare the relevant glasses production printing and cutting files. In some embodiments, 3D printing files in standard formats such as STL or OBJ and 2D lens cutting files such as DXF can be prepared. In some embodiments, the system creates two or more pairs of models for each frame design. For example, this allows for the use of lightweight models at the front end of the application for visualization purposes while maintaining high-resolution models for print file preparation, which can include, for example, high-resolution features and details such as hinges, grooves, angles, temple arms, etc. The printing models for glasses customization described here can be automated and / or manual. Additionally, the file preparation for 3D printing can include automatically resolving printing issues, generating normal, replicated, perforated, and non-manifold geometries, etc. In some embodiments, the system can create customized labels on the glasses or goggles, for example, including text, QR codes, or barcodes, which will enable traceability throughout the production and distribution process.

[0113] At step 755, the user can order a pair of personalized glasses within a physical store or an online store. Additionally, a personalized product can be requested from the store or ordered from a manufacturer that can produce the product based on the user's request such that the product is a one-time customized product for the user.

[0114] According to multiple embodiments, a system and process for automated personalized product ordering using a digital mirror or personalized viewing protocol are described. Virtual reality and / or augmented reality can be integrated to manipulate, view, and / or try on a specified device (such as existing or designed glasses) on a screen, table, smartphone, communication device, etc., to achieve a visual representation of a customized or non-customized frame on the customer's face.

[0115] According to many embodiments, a file format suitable for enabling personalized product ordering is provided. The file format combines all relevant information including physical attributes and personal preferences to represent the user and assist the user in performing personalized or non-personalized shopping for clothing, glasses, footwear, or other body-related products. This avatar standard format can be used to be inserted into substantially any online or physical shopping platform to allow for the customization of the store to fit the physical and aesthetic needs and preferences of the customer.

[0116] Now refer to Figure 8ATo FIGS. 8G, different views of a POS device, a startup tablet, or a kiosk according to some embodiments are shown. In some embodiments, the shopping assistant device generates a user avatar based on one or more of the following: 3D scanning, image acquisition using one or more cameras, measuring the user profile using a platen, etc. In some embodiments, a standing mat can be used as a positioning mat or reference for the user to stand on for body scanning. In some cases, the standing platform can include illumination at the bottom of the standing mat to support accurate measurement of any color from a camera or scanner on the device by minimizing or marginalizing shadows and creating a black / white perimeter effect. In some embodiments, there can be proximity sensors for each foot to measure whether the foot is in place or close by and to tell the user to move if needed. Additionally, the device can include a distance or proximity sensor / robot that identifies approaching users to attract the users to the device, in which case the device can be automatically activated when the user enters the selected geographical area. In several embodiments, sensors can be used to measure the height of the user's instep to, for example, establish the instep volume. In many embodiments, professional sensors can be used, such as sensors for measuring diabetic ulcers, etc. Such sensors can be used, for example, cameras, 3D sensors, full-circle cameras, and / or multiple cameras.

[0117] Figure 8A is an exploded view of an example of components of a POS device or a kiosk device in some embodiments. As can be seen, the kiosk device 800 can include: a standing base 805; a light source for optionally illuminating the standing base; one or more proximity sensors 816 for identifying the position of the foot to be scanned by the kiosk device 800; a standing mat 815 having a space for standing with both feet; and a cushion layer 820 on which the feet are mounted. In some embodiments, the cushion layer 820 can integrate a pressure sensing mechanism, such as a flatbed scanner; a pin board; a platen; a touchscreen-type surface having capacitor and / or pressure sensor elements, etc., to determine the arch size. In some embodiments, the arch size measuring element can be used to determine the user's need for and / or the size of an insole.

[0118] In some embodiments, the arch size measuring element can be used to determine the need for and / or the size of the user's instep profile.

[0119] In some embodiments, the arch size measuring element can be used to determine the need for and / or the size of the user's metatarsal ball profile (of the foot).

[0120] In many embodiments, one or more lasers or other illumination mechanisms can be used to determine the arch, metatarsal head, or gait dimensions. In one example, a laser from above the foot can be used to display the height or arch of the foot and the dimensions of the bridge, e.g., by identifying the dimensions of "hidden" areas not visible to the laser and using the "hidden" space to determine parameters (such as height) at different points on the foot. In another example, diffraction gratings, prisms, or other filters use multiple lines to be able to identify the highest points of the foot.

[0121] In several embodiments, one or more lights, optionally having different colors, can be used alone and / or in combination, along with image processing, to neutralize the color of the sock and / or foot and help identify non-foot space. In many embodiments, background elimination techniques can be used, for example, to identify one or more of the arches.

[0122] In addition, the kiosk device 800 can include a body 822 that includes a computer mount 825 and a camera fixing element 826 for fixing one or more camera elements 835, a panel element 830, another panel or cover element 845, a computing screen, preferably a touchscreen PC or tablet 840, and optionally, the body 822 has a location for setting a proximity sensor 850, such as a proximity sensor 850 for identifying the proximity of a user to the computing device.

[0123] FIG. 8B is a front view of an example of a POS device or kiosk device.

[0124] FIG. 8C is an isometric view of an example of a POS device or kiosk device.

[0125] FIG. 8D is an isometric front view of an example of a POS device or kiosk device.

[0126] FIG. 8E is an isometric rear view of an example of a POS device or kiosk device.

[0127] FIG. 8F is a side view of an example of a POS device or kiosk device.

[0128] FIG. 8G is a top view of an example of a POS device or kiosk device.

[0129] Figure 8H is a view of an example of one or more sensors in a POS device or kiosk device. It can be seen that the kiosk device can be configured with multiple sensors, such as one or more proximity sensors, and the LED panel can be configured to provide light from below the standing area.

[0130] Now refer to Figure 9 , Figure 9FIG. 0 shows a schematic diagram of a shopping assistant system 900, which includes an automated shopping assistant device 906 that integrates computing components adapted to run a shopping assistant application or software program 915. The automated shopping assistant device 906 is adapted to connect to a communication network such as a communication cloud 920 to access a user shopping profile 925 (if it is on the cloud), and / or send the user shopping profile to the cloud. Additionally, according to some embodiments, a remote user mobile device (such as a smart phone, tablet, or other camera supporting mobile communication devices 905, 910) is adapted to run a shopping assistant application or software program 916. Devices 905 and 910 typically include one or more cameras 910, for example, to enable the capture of information about a person's single or both feet under IR / NIR or visible light conditions, optionally using standard picture / scanning, video, a series of pictures, or advanced sensing components (such as structured light, time of flight, etc.) simultaneously. Devices 905 / 910 typically include a gyroscope to provide camera orientation data to the device cameras, for example, to only allow photos to be taken when the camera is substantially flat. In some embodiments, internal sensing components and / or additional sensors can be connected to communication devices 905, 910 to provide supplementary data to the system. For example, such sensors can help improve the accuracy of measurements, assist the user during the capture of data with real-time feedback, and / or provide input to the computing engine. The remote devices 905 and 910 can communicate with the communication cloud 920, and specifically, can be connected to the digital shopping avatar or profile 925 of the device user. In some embodiments, the user can use the mobile devices 905, 910 together with the automated shopping assistant device 906 or use the mobile devices 905, 910 instead of the automated shopping assistant device 906 to generate a shopping profile for one or more users.

[0131] Now referring to Figure 10 , Figure 10 FIG. 1 shows a schematic diagram of a shopping assistant system 1000 and the workflow between components. It can be seen that the startup tablet or shopping assistant device 1005 can scan the user to generate a user's shopping profile. The generated profile is sent to the user's mobile device 1010 and can subsequently be used to optionally scan a product (such as a shoe 1015) via a product label (such as a QR code 1020) representing the selected product. Additionally, in some embodiments, the user can use a mobile application 1025 to build a shopping profile. In some embodiments, at 1030, the user shopping profile can be used to enhance in-store shopping. In some embodiments, at 1040, the user shopping profile can be used to enhance online shopping.

[0132] Now referring to Figure 11A , Figure 11AA flowchart showing an example of personalized footwear shopping in a shopping store by using an in-store or POS automated shopping assistant device in combination with a mobile computing device application. As can be seen, at step 1100, the user can be identified by a proximity sensor of the shopping assistant device, and at step 1105, the user can be requested to stand on a marked mat, and optionally, interactive guidance can be provided to ensure that the user stands in the correct position for accurate scanning. At step 1110, the device scans the body or body part / element, and at step 1115, a shopping profile is generated based on the scan. At step 1120, the device can present a shopping avatar to the user in a graphical format. At step 1125, the device can send the shopping avatar to the user's mobile device. At step 1130, the user can open the shopping application, which can be used to assist with shopping and / or research. At step 1135, the user can use the avatar on their mobile device to shop or conduct research, for example, by using coded tags (such as QR codes or barcodes) to scan the selected products. Generally, the scanned products can be processed in a manner related to the user avatar to, for example, determine if the product fits the avatar, the user's profile or preferences, etc. In some cases, the application can provide a graphical simulation of the selected product on the avatar. At step 1140, the application can connect to a communication cloud or other database to match the selected products with product data to, for example, assist in determining purchase options, inventory status, product quality, product features, reviews, sizes, etc. In some cases, at step 1145, the application can present recommendations, purchase data, etc. to the user. In further steps, the application can enhance the in-store shopping experience, for example, by providing shopping suggestions, options, shortcuts, access to other databases, etc.

[0133] Now refer to Figure 11B , Figure 11BA flowchart showing an example of personalized footwear shopping in a shopping store by using an in-store or POS automated shopping assistant device in combination with a mobile computing device application. As can be seen, at step 1100, a new or known user can be entered on the shopping assistant device, for example, by a biometric identifier, an input screen, etc. At step 1105, the user can be requested to stand on a marked mat, and optionally, interactive guidance can be provided to ensure that the user stands in the correct position for accurate scanning. At step 1110, the device scans the body or body part / element, and at step 1115, the scanned data is processed and a shopping profile is generated based on the scan. At step 1120, the device can present the shopping profile to the user in a graphical or other format as a simulation, a shopping avatar, or other virtual assistant. At step 1125, the device can send the shopping avatar to the user's mobile device in a format or configuration usable by the software, code, or application of the device. At step 1130, the user can open the shopping application or other program that can operate the shopping avatar with the shopping assistant application. At step 1135, the user can use the avatar on their mobile device to shop or conduct research, for example, by using encoded tags (such as QR codes or barcodes) to scan the selected products. Generally, the scanned products can be processed in a way that takes into account the generated shopping avatar to, for example, determine whether the product fits the avatar, the user's profile or preferences, etc. In some cases, the application can provide a graphical simulation of the selected product on the avatar. At step 1140, the application can connect to a communication cloud or other database to match the selected products with advanced product data to, for example, assist in determining ordering options, inventory status, product quality, product features, reviews, sizes, etc. In other cases, at step 1140, the application can connect to a communication cloud or other database to match the selected products with advanced user data to, for example, assist in determining user preferences, user history, and user profile updates, etc. In some cases, at step 1145, the application can present recommendations, purchase data, purchase options, reviews, news, etc. to the user to help enhance the online store shopping experience. In some cases, at step 1150, the application can present recommendations, purchase data, purchase options, reviews, news, etc. to the user to help enhance the in-store shopping experience, for example, by providing shopping suggestions, options, shortcuts, access to additional databases, etc.

[0134] In some embodiments, a user shopping experience can be performed for other users connected to the user of the shopping assistant. In such cases, the user application can include shopping profiles of multiple users, thereby allowing the user of the mobile device to perform shopping for multiple users based on the shopping profiles of the users.

[0135] According to some embodiments, mobile and / or user avatars can be shared with other users. For example, a user can access or control multiple user profiles, such as in a wallet or holder of an avatar or profile, with user authorization. In such a case, the controlling user can shop on behalf of other users. For example, a parent can save the profiles of all of their family members, thereby allowing the parent to easily shop online and / or offline for all associated family members.

[0136] According to some embodiments, additional personalization, such as icons or pictures, can be provided for each user mobile shopping avatar or user shopping avatar. Such personalization is particularly useful for a controlling user to manage multiple users or mobile shopping avatars. This information associated with any identifier can be saved on a cloud avatar database and associated with the user in any platform he or she uses. For example, in the case where a family member scans and saves the profile of one or more of their family members, these profiles can be shared with other family members that can currently be loaded into the in-store system or e-commerce website being used, and the personalization information can then be used. In the case of a website, the output can be personalized based on this personalization data and can even include pictures or avatars or 3D models of other users next to the information provided, to again ensure that the user is convinced that the recommendation is personal and based on his or her profile, or other profiles that the user legally uses.

[0137] According to some embodiments, an online store can include a user shopping virtual assistant that uses a profile plugin or other digital object, which can appear on substantially any web page (regardless of whether it is optimized for a mobile phone, desktop, laptop, tablet, wearable device, etc.), to provide recommendations, guidance, or other assistance to the user when relevant. For example, the virtual shopping assistant can show information about different fits of the user profile being used, or otherwise assist the user. For example, when shopping or browsing in the Nike online store, a user with a foot size of European size 41 may be informed that the equivalent size of their foot profile in Nike shoes is European size 42 or US size 10.5. Additionally, if the user profile includes preference data, such as preferred colors and fits, etc., the shopping virtual assistant can also provide suggestions or guidance based on the user preferences. For example, in a Nike shoe store, the shopping assistant can suggest options such as US size 10.5, sports shoes, blue or green, etc. for the user to look for.

[0138] In some embodiments, the virtual assistant can direct the user directly to one or more pages that match the user's shopping profile data and preferences. In several embodiments, the profile can direct the website to sections that are of interest or relevant to a particular user while avoiding irrelevant pages. In many embodiments, the system can use the personalized information alone or with additional users to rearrange the website and create a personalized version of the website, which can represent the content that she / he may be most interested in and the content that is most suitable for him / her.

[0139] According to some embodiments, the virtual shopping assistant can enable the presentation of a 3D view of the product being viewed and optionally a 3D view of a personalized product. For example, a customized shoe being viewed according to the user's shopping profile can be presented in 3D from all sides and angles to help the user view the product from multiple dimensions.

[0140] According to some embodiments, a virtual try-on module can be provided to allow the product being viewed to be worn on a shopping avatar.

[0141] According to some embodiments, the user shopping avatar can be a one-time avatar for a store. In many embodiments, the user shopping avatar can be applied to a chain store. In several embodiments, the user shopping avatar can be applied to various brands or stores that are, for example, all owned by a parent entity. In many embodiments, via a connection to a general user profile in the cloud, the user shopping avatar can be applicable to any or all stores.

[0142] Now refer to Figures 12A to 12B , Figures 12A to 12B which is an example of a screenshot of an interactive screen of a shopping assistant screen according to some embodiments, for guiding the user to place their feet on the marked mat;

[0143] Now refer to Figures 13A to 13B , Figures 13A to 13B which is an example of a screenshot of an interactive guide of a shopping assistant screen or a mobile screen according to some embodiments, for helping the user define their profile and their contact information;

[0144] Now refer to Figures 14A to 14B , Figures 14A to 14B which is an example of a screenshot of a shopping assistant screen or a mobile screen according to some embodiments, showing a simulated reproduction of a pair of scanned feet and calves;

[0145] Now refer to Figures 15A to 15B , Figures 15A to 15B which is an example of a screenshot of a shopping assistant screen or a mobile screen for helping the user input behavior-related information, which can be used to provide better user-related outputs.

[0146] Now refer to Figures 16A to 16D , Figures 16A to 16D which shows a perspective view of an example of a shopping assistant standing surface according to some embodiments. As can be seen from the figure, the standing surface 1600 is typically a flexible surface, such as a mat or a carpet, optionally made of PVC, rubber, polyurethane, paper, cardboard, or any other suitable material. The standing surface 1600 typically includes a 3D portion or element 1605 that replaces the wall and is capable of correctly positioning the feet for scanning. This 3D element serves as a footrest against which the instep is placed. The standing surface 1600 typically includes markings 1610, dots, or indicatory graphics to improve the accuracy of the scanned image. In some embodiments, the markings 1610 can serve as signs, where there can be multiple signs, and the signs can have different sizes, dimensions, functions, etc., all of which can be the same or some signs can be different from other signs.

[0147] Figure 17 shows an additional form of the shopping assistant standing surface according to some embodiments. As can be seen, there is a 3D foot placement element 1705 for each foot.

[0148] Figure 18 shows another form of the shopping assistant standing surface according to some embodiments. As can be seen, there are 3D foot placement elements 1805 of different shapes.

[0149] Figure 19 shows a first user scenario according to some embodiments, where a virtual graphical example showing the use of the shopping assistant device is provided. As can be seen, the assistant 1900 can use a standard camera 1910 (e.g., a phone or a tablet) and / or a depth camera to take or scan the system user 1905.

[0150] Figure 20 shows a second user scenario according to some embodiments, where a virtual graphical example showing the use of the shopping assistant standing surface is provided. As can be seen, the system user 2000 can use a standard camera 2005 (e.g., a phone or a tablet) and / or a depth camera to perform a self - shoot or a scan.

[0151] Figure 21 is a picture showing an example of a user located on the shopping assistant standing surface according to some embodiments. As can be seen from the figure, the standing surface 2100 typically includes a 3D portion or element 2105 (replacing the wall) and enables the correct positioning of the feet for scanning. This 3D element serves as a footrest against which the instep is placed. The standing surface 2100 typically includes markings or indicatory graphics 2110.

[0152] According to some embodiments, a virtual scanning mat can be used to enable a user device to generate an accurate scan of their body (e.g., the user's foot) without a physical mat or marked surface, as described above. In some embodiments, a reference object such as a rectangular sheet or paper or card is required to enable a shopping assistant application, device, and / or system to accurately map and scan the user's body. In many embodiments, a reference object is not required.

[0153] In some embodiments, the user device, application software, and / or server can integrate augmented reality (AR) functionality to assist the user in performing an accurate scan without using a physical scanning mat. For example, known AR toolkits such as Apple's ARKit or Google's ARCore can be used to provide AR functionality in a shopping assistant application. Thus, AR can be used to provide virtual assistance to the user and / or provide a virtual mat or surface (with lines and markers etc. as needed) to guide the user to stand appropriately so as to be able to perform an accurate scan. In some embodiments, a virtual assistant such as a character or avatar can be used or selectively used to guide the user. In some embodiments, the virtual assistant can guide and correct the user in real time, e.g., telling the user to position themselves differently, change the light, etc., to enhance the scan.

[0154] In many embodiments, the virtual scan mapping generated by the user device / application can appear transparent to the user, thereby enabling the user to stand essentially anywhere while the system imposes the virtual scan mapping on the user's foot and captures the relevant scan data as well as virtual mat markers (whether visible or transparent markers) to generate a shopping profile and / or avatar.

[0155] In some embodiments, an angle measurement device can be provided to enable angle control such that the user can perform scans at various supported angles and still generate an accurate scan. For example, an angle measurement graphic that displays the status of the display device accelerometer and / or gyroscope status can be used to show whether the user's current scan angle is acceptable and, if not, assist the user in scanning at a more appropriate angle.

[0156] In several embodiments, a focus enhancement device can be provided to enable the user to generate an accurate scan and, in parallel, be able to observe the object of the focused scan. For example, one or more captures of the foot and / or the environment can be taken in AR mode and one or more captures of the foot and / or the environment can be taken in picture (focus) mode such that when viewing the AR environment, a focused image of the foot can be imposed in the AR view to ensure that the focused image of the foot is constantly displayed.

[0157] In many embodiments, a virtual try-on device can be provided to enable a user to use AR to generate an accurate profile or avatar of a scanned body part (such as a foot) and place a virtual shoe on the foot. In this way, by presenting the selected footwear on the user's foot using AR, different types, sizes, varieties, brands, colors, patterns, etc. can be seen on the user's foot. In some embodiments, other body parts can be scanned to generate a profile of the selected part, as described herein with respect to the foot.

[0158] In many embodiments, different processing algorithms can be used to achieve optimal profile generation and / or display for different feet. Thus, the scan can be processed by multiple algorithms, and the best algorithm can be selected for the user profile. In some embodiments, a machine learning device can be used to automatically vote for the best profile to be used.

[0159] Figures 22A to 22J is an example of a screenshot and a teaching screen according to some embodiments, the screenshot and the teaching screen showing a series of steps for guiding a user to use a virtual scanning mat. As can be seen from the figure, the system, device, equipment, and application take steps to provide the user with a virtual standing surface generated using augmented reality. The virtual standing surface typically includes virtual markers (such as points, lines, and indicator graphics) to enhance the accuracy of the scanned image and facilitate user use.

[0160] Figure 22A is a screenshot showing an example of a GUI of a shopping assistant screen according to some embodiments for guiding a user on how to prepare to use a virtual shopping assistant. It can be seen that the user can be requested, for example, to take off their shoes, put on appropriate socks, and prepare a suitable reference object (such as a rectangular card or paper).

[0161] Figure 22B is a screenshot showing an example of a GUI of a shopping assistant screen according to some embodiments for guiding a user on how to prepare a selected reference object for scanning before using a virtual shopping assistant.

[0162] Figure 22C is a capture showing an example of a user holding a smartphone (displaying the GUI of a shopping assistant screen) according to some embodiments for guiding a user to calibrate the user device with the environment to be used for the virtual assistant. As can be seen in the example provided, the user can be requested to slowly move their phone or device around until an indication (such as a change in screen or frame color) is provided, which indicates that the device has mapped or otherwise successfully scanned the environment. For example, this initial scan can draw the reference object and other details of the environment, and then the data can be processed to determine the size of the reference object and the necessary environmental elements in order to accurately measure the user's body in the next steps.

[0163] Figures 22D to 22E This is a capture showing an example of a user holding a smartphone (with a GUI displaying a shopping assistant screen) for guiding the user to scan the environment to be used for the virtual assistant. As can be seen in the provided example, the user may be requested to move their phone or device closer to a page or reference object and click on a digital image of the reference object to tell the application to generate a virtual scan pad.

[0164] Figure 22F and Figure 22G This is a capture showing an example of a user holding a smartphone with a GUI that integrates augmented reality functionality to further guide the user. It can be seen that the virtual representation of the user can provide the user with further instructions or guidance, using appropriate graphics to assist the user.

[0165] Figure 22H This is a capture showing an example of a user holding a smartphone (with a GUI displaying a shopping assistant screen) for guiding the user to select a location to complete the scanning process and generate a virtual scan pad at the selected location.

[0166] Figure 22I This is a capture showing an example of a user holding a smartphone (with a GUI displaying a shopping assistant screen) for guiding the user to select a location to complete the scanning process and generate a virtual scan pad at the selected location.

[0167] Figure 22J This is a screenshot showing an example of the GUI of the shopping assistant screen, which shows a virtual scan pad at the selected location for the user to stand on or "inside" for scanning the user's body or in this case, the foot. The user device can now scan the user's foot and process the scanned data based on the use of the virtual scan pad to present an accurate profile of the user's foot.

[0168] Figure 23A flowchart depicting the step - by - step process during the generation of a virtual shopping profile according to some embodiments is shown. As can be seen, at step 2305, the remote user is instructed to prepare (with a computing device running a virtual shopping assistant application) the environment for profile - generation scanning. For example, for a foot scan, the user may be asked to remove their shoes, wear appropriate clothing, and prepare an appropriate reference object. At step 2310, the user is instructed to place the reference object in an appropriate position, such as against a wall in the room. At step 2315, the user is instructed to capture the environment (including the capture of the reference object) with their device camera and click on the captured reference object to define it as the reference object. At step 2320, the virtual assistant (optionally including the user's virtual image) can use the AR reproduction of the user depicted on a virtual scan plane or map to further assist or guide the user to perform the scan appropriately. At step 2325, the user is instructed to stand within a digitally - overlaid virtual scan mat. At step 2330, the user is instructed to start the scan by clicking a "scan" button or function. At step 2335, the scan can be processed to form a user profile for remote shopping. At step 2340, the user shops in a physical or digital store using the shopping profile.

[0169] In some embodiments, the shopping assistant standing surface may include active components (such as light, detectors, sound, etc.). In this case, the shopping assistant standing surface may include a power source (optionally a battery - powered source), and one or more suitable sensors.

[0170] In some embodiments, the shopping assistant standing surface may include a platen (optionally supporting Bluetooth) to assist in receiving additional data regarding the shape of the user's arch.

[0171] In some embodiments, the shopping assistant standing surface may be foldable, for example, for reasons of storage, transportation, or display.

[0172] In a further configuration, the shopping assistant standing surface may be integrated into a "try - on chair".

[0173] In some embodiments, the shopping assistant standing surface may include two standing surfaces with two different colors (e.g., for image recognition).

[0174] In some embodiments, the shopping assistant standing surface may be placed on, tried on, or integrated into a try - on chair or stool. In this case, when in a sitting position, the standing surface can be placed to accommodate the user's feet.

[0175] In some embodiments, the shopping assistant standing surface may include an Augmented Reality (AR) function, allowing a user standing on the standing surface to browse the shoes on his or her feet and see them on the generated model. For example, this may enable a customer to view his / her bare feet or feet with socks on and see different shoes that he / she can browse based on his / her feet from the augmented reality tracking through AR glasses or a phone / tablet.

[0176] In some embodiments, the shopping assistant device may help a chain store generate online and / or offline loyalty by allowing for automated shopping assistance, proactive selling, cross-selling, etc. in multiple stores.

[0177] In several embodiments, the shopping experience of a user with respect to footwear can be enhanced sufficiently by applying the following steps: measuring the user's physical profile on device 185 and providing the user's standard size as well as modifications for different shoes / brands; obtaining the customer's ID or shopping profile from the customer's mobile computing or communication device; and obtaining the customer's ID or shopping profile from device 185 to the communication cloud.

[0178] In the case of a first-time user where the user does not have a previous user profile, the shopping assistance process can be implemented as follows: The user generally removes their shoes at the entrance of the store or shopping area and stands on the activation tablet or shopping assistant device. In the current example, a footwear application is described. The device then measures / scans the user's body area (e.g., feet), and thereafter the device or cloud network may process the user data and generate a user shopping avatar. Once generated, the avatar is sent to the user's mobile device running the shopping assistant application, for example, using mail, beacons, SMS, QR codes, IR beams, etc. The user can then scan the desired shoes, whereupon the device is configured to match the desired shoes and then try on the desired shoes on the avatar to provide the best fit. The device can also provide the user with relevant product information such as availability, color, size, related shoes, ratings, etc.

[0179] In the case of a second user who has multiple devices, the shopping assistance process can be implemented as follows: The user typically picks up shoes at the entrance of a store or shopping area and stands on a startup tablet or shopping assistant device. In the current example, a footwear application is described. The device then measures / scans the user's body area (e.g., feet), and thereafter the device or cloud network can process the user data and generate a user shopping avatar. Once generated, the avatar is sent, for example, using mail, beacons, SMS, QR codes, IR beams, etc., to the user's mobile device running the shopping assistant application. The user can then scan the desired shoes, whereupon the device is configured to match the desired shoes and then try on the desired shoes on the avatar to provide the best fit. The device can provide the user with expert or advisory information, thus serving at least partially as a sales representative. The device can also provide relevant product information (e.g., availability, color, size, related shoes and grades), as well as options to measure movement / style / weight, etc.

[0180] In a third user case, an enhanced shopping experience can be provided, whereby the automated shopping assistance process can be combined with local shoe scanning. In some cases, user data or avatars can be used to filter appropriate evaluations / comments from the online world + social feedback + rankings, sales information / history, recommendations, upselling, cross-selling, etc.

[0181] For purposes of illustration and description, the above description of the invention has been given. It is not intended to be exhaustive or to limit the invention to the precise form disclosed. Those skilled in the art will appreciate that many modifications, variations, substitutions, alterations, and equivalents are possible in light of the above teachings. Accordingly, it is to be understood that the appended claims are intended to embrace all such modifications and alterations that fall within the true spirit of the invention.

Claims

1. A shopping assistant system, comprising: a processor; and a register communicating with the processor and storing instructions which, when read by the processor, cause the shopping assistant system to: display a guidance interface on a user device to guide the user to calibrate the user device with a background environment, wherein calibrating the user device includes instructing the user to slowly move the user device around until it is determined that a successful scan has been completed, and displaying a first indication on the guidance interface indicating that the user device has successfully scanned the background environment; after calibrating the user device with the background environment, provide the user device with a graphical user interface to generate a virtual scan pad; after receiving a click on a digital image of a reference object in the graphical user interface, use the user device to generate the virtual scan pad, wherein the virtual scan pad includes markings for guiding the user to stand appropriately to allow accurate scanning of a part of the user's body without referring to a physical pad or a marked surface; when a part of the user's body is within the markings of the virtual scan pad, obtain an image of the part of the user's body from the user device; calculate user body measurement data of the part of the user's body based on the image; generate a 3D model of the part of the user's body based on the user body measurement data, wherein the 3D model includes the user body measurement data; generate at least one product recommendation based at least on the user body measurement data; and display the at least one product recommendation.

2. The shopping assistant system according to claim 1, wherein, The user body measurement data includes at least one measurement, and the at least one measurement includes the length, width, and depth of a part of the user's body.

3. The shopping assistant system according to claim 1, wherein, The virtual scan pad includes one or more augmented reality generated markings for aligning a part of the user's body to the user device.

4. The shopping assistant system according to claim 1, wherein The instructions, when read by the processor, further cause the shopping assistant system to: process the user body measurement data to remove the floor from the user body measurement data.

5. The shopping assistant system according to claim 1, wherein The at least one product recommendation includes at least one product label associated with a product.

6. The shopping assistant system according to claim 1, wherein, The instructions, when read by the processor, further cause the shopping assistant system to: based on receiving authorization from the user, send the at least one product recommendation to a mobile device associated with a second user, wherein the mobile device allows the second user to shop for the user.

7. The shopping assistant system according to claim 1, wherein, The at least one product recommendation is generated based on a combination of user shopping history data, user preference data, and at least one measurement of a part of the user's body and corresponding product data.

8. The shopping assistant system according to claim 1, wherein The instructions, when read by the processor, further cause the shopping assistant system to: send the at least one product recommendation to a social media platform for viewing by one or more third parties.

9. The shopping assistant system according to claim 1, wherein The part of the user's body includes the user's feet.

10. The shopping assistant system according to claim 1, wherein: the shopping assistant system includes at least one camera; and When a user body part is within the markings of the virtual scan mat, the at least one camera captures at least one image of a portion of the user's body.

11. The shopping assistant system according to claim 10, wherein, The 3D model is generated based on at least one image of a portion of the user's body.

12. The shopping assistant system according to claim 2, wherein, When read by the processor, the instructions further cause the shopping assistant system to: Obtain scanned product data, where the scanned product data is obtained based on a label associated with the product; Determine a recommended size of the product based on the at least one measurement; and Display the recommended size of the product.

13. The shopping assistant system according to claim 12, further comprising: Generating a second 3D model of the product based on the recommended size of the product; And Displaying the second 3D model.

14. A method for personalized shopping, comprising: Displaying a guidance interface on a user device to guide the user to calibrate the user device with a background environment, where calibrating the user device includes instructing the user to slowly move the user device around until it is determined that a successful scan has been completed, and displaying a first indication on the guidance interface indicating that the user device has successfully scanned the background environment; After calibrating the user device with the background environment, providing a graphical user interface to the user device to generate a virtual scan mat; After receiving a click on a digital image of a reference object in the graphical user interface, generating the virtual scan mat by a shopping assistant device, where the virtual scan mat includes markings for guiding the user to stand appropriately to allow accurate scanning of a portion of the user's body without referring to a physical mat or marked surface; When a user body part is within the markings of the virtual scan mat, obtaining an image of a portion of the user's body by the shopping assistant device; Calculating user body measurement data of a portion of the user's body by the shopping assistant device and based on the image; Generating a 3D model of a portion of the user's body by the shopping assistant device and based on the user body measurement data, where the 3D model includes the user body measurement data; Generating at least one product recommendation by the shopping assistant device and at least based on the user body measurement data; and Displaying the at least one product recommendation by the shopping assistant device.

15. The method according to claim 14, wherein, The portion of the user's body includes the user's feet.

16. The method according to claim 14, wherein The user body measurement data includes at least one measurement, and the at least one measurement includes the length, width, and depth of a portion of the user's body.

17. The method according to claim 14, wherein The at least one product recommendation is virtually tried on the 3D model of a portion of the user's body.

18. The method according to claim 14, wherein The at least one product recommendation is generated based on a combination of user shopping history data, user preference data, and at least one measurement of a portion of the user's body and corresponding product data.

19. The method according to claim 14, wherein The at least one product recommendation is a personalized product based on a combination of the 3D model of a portion of the user's body and user preferences.

20. The method according to claim 14, further comprising: Generate a second 3D model of the product based on the recommended size of the product, and display the second 3D model.

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