System, platform and method for personalized shopping using virtual shopping assistant

Abstract

Apparatuses, systems, and methods for providing personalized online product try-on are disclosed herein. In various embodiments, a personalized shopping system includes: an automatic shopping assistant that accesses product data; a matching system accesses historical data, preference data, and / or anatomical data measured using an automated shopping assistant device, where the personalized shopping system may generate personalized matches based on the historical data, preference data, and / or anatomical data. The automated shopping assistant device may include a depth sensor and / or an image scanner capable of capturing various 2D and / or 3D models. These models may be used to generate anatomical data. The anatomical data may be used to virtually attempt various items. Products may be personalized based on the historical data, preference data, and / or anatomical data.

Description

[0001] This application is a divisional application of the patent application with application number 201980018307.5, filed on January 24, 2019, and titled “A System, Platform and Method for Personalized Shopping using a Virtual Shopping Assistant”.

[0002] Cross Reference to Related Applications

[0003] This application claims priority to U.S. Provisional Patent Application No. 62 / 621,548, filed on January 24, 2018, titled “A System, Platform and Method for Personalized Shopping using a Virtual Shopping Assistant”, the disclosure of which is incorporated herein by reference in its entirety. TECHNICAL FIELD

[0004] The present invention relates generally to methods, applications, and devices for personalized product shopping. BACKGROUND

[0005] Currently, most footwear shopping still occurs in real brick and mortar stores. Both customers and store managers and associates are familiar with the limitations of traditional shopping. Often, customers rely on shopping assistants to guide them to products, inform them of the location of in-stock products, provide assistance with product try-ons, and so on.

[0006] Furthermore, the typical shopping experience needs to be repeated with each visit by the customer to the same or different store, resulting in extreme inefficiencies and user frustration.

[0007] It would be highly advantageous to have a system or method that enables a highly accurate, user-friendly, automated or semi-automated try-on solution that can be run both online and in-store. SUMMARY

[0008] According to embodiments of the present invention, there is provided an apparatus, system and method for providing personalized online product try-on.

[0009] A method for personalized shopping has the steps of an automated shopping assistant system accessing product data, a matching system accessing user history data, a matching system accessing user preference data, a matching system accessing user anthropometric data acquired from an automated shopping assistant apparatus, the automated shopping assistant system matching the user history data, the user preference data, and the user anthropometric data with the product data to generate a personalized matching system.

[0010] In some embodiments, the automated shopping assistant system matches user history and preference data with product data to generate personalized product recommendations.

[0011] In some embodiments, the automated shopping assistant system can be used to enable a user to order personalized products.

[0012] In some embodiments, the automated shopping assistant system can be used to provide a simulation representing one or more anatomical features of a user.

[0013] In many embodiments, a user and one or more third parties can provide product try-on feedback, and the user and one or more third parties can provide social feedback. The automated shopping assistant system can tune personalized products based on product feedback. The system can also provide anatomical data about a user, where the automated shopping assistant system also considers the anatomical data to generate a user shopping avatar that contains one or more features of the user.

[0014] The automated shopping assistant system can include a virtual try-on feature. In many embodiments, a product is generated based on an avatar before a user orders a personalized product. User preferences can be selected from a group consisting of size, color, material, and type preferences.

[0015] According to some embodiments, there is provided a platform for personalized shopping, comprising: a cloud-based server comprising a profile module for generating a digital avatar for a plurality of users; a product module for consolidating product data for a plurality of products; and a matching module adapted to run code to match digital avatar data and product data to generate product recommendations; a terminal user computing device communicatively connected to the cloud-based server, comprising an image capture element, wherein the matching module runs a software application to generate a user mobile shopping avatar based on a capture of at least a portion of the user's anatomy, in turn for generating anatomical data for the user's digital avatar profile.

[0016] In some embodiments, the platform is adapted to generate and / or present a simulation representing one or more anatomical features of a user.

[0017] 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, among others.

[0018] A handheld system for personalized shopping can have a screen configured to receive user input, a device camera for capturing standard images of a 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 a user can purchase the personalized product by providing user input to the screen.

[0019] In several embodiments, the system has a depth sensor configured to accurately determine the distance of an object from the sensor, and wherein the 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 to enable capturing the length, width, and depth of the portion of the body.

[0020] 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.

[0021] 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 a capture of at least a portion of a user's body by a camera device, a mobile device app for applying the user's 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.

[0022] 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 to enable capturing the length, width, and depth of the portion of the body.

[0023] The shopping assistant system, wherein the shopping assistant standing surface includes one or more augmented reality (AR) generated markers for assisting in capturing body portion dimensions.

[0024] 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 a body portion to be scanned.

[0025] The shopping assistant system also includes a plurality of product tags associated with a plurality of products for a user to shop by scanning one or more product tags.

[0026] The shopping assistant system also 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.

[0027] An in-store shopping enhancement method is provided, including: identifying a user entering a shopping area, positioning the user on a shopping assistant virtual standing surface; opening a new or known user profile; initiating capture of at least a portion of a body using one or more sensors; generating a user 3D shopping profile of the user; sending the user shopping profile to a user mobile device, wherein the user mobile device is usable in a shopping assistant application; selecting a product of interest by the user by scanning a product tag using the user mobile device; and providing shopping assistance to the user for the selected product.

[0028] The method also includes ordering the selected product using the user mobile device.

[0029] The method also includes customizing the selected product using the user mobile device.

[0030] The method also includes ordering the customized product using the user mobile device.

[0031] The method also includes providing user product inventory information.

[0032] The method also includes trying on the selected product on the user shopping profile avatar.

[0033] The method also includes sending the tried-on user profile avatar to a social media system for viewing by selected associates connected to the user.

[0034] The method also includes enhancing the user shopping profile based on user behavior.

[0035] The method also includes providing shopping recommendations based on the user shopping profile and / or user shopping behavior.

[0036] The method also includes shopping in an online store using the user shopping profile.

[0037] The method also includes adding additional user shopping profiles to the mobile device.

[0038] The method also includes transferring the profile of the user from the in-store device to the user mobile device.

[0039] 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 a user to prepare an environment for a profile generation scan; subsequently placing reference objects in place; then capturing the environment with their device camera (including capture of the reference objects), and tapping on the captured reference objects to define them as reference objects; providing a virtual assistant to further assist or guide the user in properly performing the scan by using AR recreations that the user draws on a virtual scan plane or map; subsequently instructing the user to stand in a digitally superimposed virtual scan mat; then starting the scan; processing the scan 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 DRAWINGS

[0040] The principles and operation of systems, apparatuses, and methods according to the present application can be better understood with reference to the drawings and the following description, it being understood that such drawings are given for illustrative purposes only and are not meant to be limiting, wherein:

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

[0042] Figure 1B is a schematic system diagram depicting a platform for facilitating personalized shopping according to some embodiments;

[0043] Figure 2 is a flowchart showing a process for facilitating personalized shopping according to some embodiments;

[0044] Figure 3 is a flowchart for facilitating a personalized in-store shopping experience according to some embodiments;

[0045] Figure 4 is a flowchart for facilitating a personalized online shopping experience according to some embodiments;

[0046] Figure 5 is a flowchart showing an example of a personalized hybrid shopping experience according to some embodiments;

[0047] Figure 6 is a flowchart showing an example of personalized shoe shopping online or offline according to some embodiments;

[0048] Figure 7 is a flowchart showing an example of personalized eyewear shopping and manufacturing online or offline according to some embodiments;

[0049] Figure 8A shows an exploded view of an example of a shopping assistant device according to some embodiments;

[0050] Figures 8B-8H A set of views showing an example of a shopping assistant device according to some embodiments;

[0051] Figure 9 A shopping assistant system according to some embodiments is shown;

[0052] Figure 10 A flowchart showing an example of the integrated 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;

[0053] Figure 11A And Figure 11B An example of a shopping assistant use process according to some embodiments is described;

[0054] Figures 12A-12B An example of a screenshot according to some embodiments showing an interactive screen on the shopping assistant screen for guiding the user to place their feet on the marked platform;

[0055] Figures 13A-13B An example of a screenshot according to some embodiments showing an interactive guide displayed on the shopping assistant screen or mobile screen for helping the user to define their profile and their contact information;

[0056] Figures 14A-14B An example of a screenshot on the shopping assistant screen or mobile screen according to some embodiments for showing a scanned pair of feet and lower legs;

[0057] Figures 15A-15B An example of a screenshot on the shopping assistant screen or mobile screen for helping the user to input behavior related information that can be used to provide better user related output;

[0058] Figures 16A-16D A set of views showing an example of a shopping assistant standing surface according to some embodiments;

[0059] Figure 17 An additional version of a shopping assistant standing surface according to some embodiments is shown;

[0060] Figure 18 Another version of a shopping assistant standing surface according to some embodiments is shown;

[0061] Figure 19 A first user situation according to some embodiments is shown in which a virtual graphic example showing the use of a shopping assistant device is provided;

[0062] Figure 20a second user scenario is shown in which a virtual graphical example showing the use of a shopping assistant device is provided, in accordance with some embodiments;

[0063] Figure 21 is a picture showing an example of a user located on a shopping assistant device, in accordance with some embodiments;

[0064] Figures 22A-22J is an example of a screenshot and a tutorial screen showing a series of steps to guide a user in using a virtual scan pad, in accordance with some embodiments; and

[0065] Figure 23 is a flowchart describing the flow of steps in the process of virtual shopping profile generation and use, in accordance with some embodiments. DETAILED DESCRIPTION

[0066] The following description is presented to enable any person skilled in the art to make and use the application provided in the context of a particular application and its requirements. Various modifications to the described embodiments will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other embodiments. Thus, the present application is not intended to be limited to the particular embodiments disclosed, 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 present application.

[0067] The term "try on" as used herein can refer to trying on a product, viewing a product being tried on, modifying a product to a particular person's body or other physical parameters. The term "avatar" can refer to a personification, icon, model and / or graphic representing a particular person, in particular, a person on a screen.

[0068] By optionally providing an accurate size recommendation to a customer based on a simulation or avatar model of the customer's foot for each shoe model, the lower online shopping rate for footwear can be increased, thereby increasing the customer's confidence in making a purchase.

[0069] Non-limiting embodiments of the present application include systems, platforms and methods for facilitating highly personalized shopping online and / or in-store, including effective try-on of products. In some embodiments, systems, platforms and methods for enabling personalized manufacturing of products are provided.

[0070] Reference is now made to Figure 1A , Figure 1A is a schematic system diagram depicting a system 100 for facilitating personalized shopping, in accordance with 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 the cloud and / or on a local automated shopping assistant device.

[0071] As can be seen, the personalized shopping system 100 includes a platform 105 for personalized shopping profile management, which can 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.

[0072] The platform 105 is in communication with a communication cloud 140, which can include a physical profile data module 145 communicatively connected to a launch pad, kiosk, or automated shopping assistant device 185, the communication cloud 140 further communicatively connected to a user 180, providing physical user data, for example, from 2D and / or 3D scans or other digital measurement sources. The communication cloud 140 can also include a user preference data module 150, which is communicatively connected to the automated shopping assistant device 185 and / or 180, providing user preference data. The communication cloud 140 can also include a product file data module 160, which is communicatively connected to a product database 165 and a product matching data module 170, which contains a product matching algorithm communicatively connected to a product database 175.

[0073] In several embodiments, the device 185 includes one or more imaging devices, such as 2D and / or 3D cameras, which can be mobile components or static components. The device 185 can also include one or more sensors, such as proximity sensors, scanners, cameras, platen, and / or other sensors.

[0074] It can be seen that the digital avatar profile 110 is highly personalized, constructed from various data sources that are directly or indirectly from the user or represent physical characteristics and / or spiritual, emotional, psychological characteristics. The digital avatar profile 120 typically includes a file or 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. Further, the product selection module 120 typically matches the personalized avatar profile 110 with selected digital product lines online or offline. The computation of the matching algorithm can be performed by the 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 set of data holding locations that are part of a computer processor used to hold computer instructions, memory 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 types, sizes, styles, models, etc. provided by the product database with the physical parameters defined by the user avatar profile and / or user preference data based at least on a scan of at least a portion of the user's body related to the user profile. For example, user A has a foot profile defined by size, width, and depth. Further, the user's profile can include preference data such as preferred style, shoe type, and color, for example, blue or gray athletic shoes. The product database can include, for example, blue, gray, and blue-gray athletic shoes that are exact 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 from the product database that match the user profile.

[0075] The product try-on module 125 can further improve the product selection module 120 by providing system feedback and product try-on data, as well as social shopping data from the social shopping module 130. 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 user the product. 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 according to 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 experimented with or tested, such as by changing the product color, shape, design, size, material, etc. In this way, the product to be ordered can be constructed according to the user's 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. Additionally, user updates contained 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, such as with updates to the user's body changes, preference changes, etc.

[0076] The product selection module 120 includes a file or set of files and data points from which instructions can be executed to execute commands to match the high resolution user profile or avatar with products having a high level of try-on to the shopping investigation being performed by each system user. The product selection module can also integrate feedback generated in the system modules to continually 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 in an array of numbers. In some embodiments, the array of numbers can represent various elements of the avatar to allow comparison to similar elements of products being tried on by the avatar. Thus, when the avatar data, which can be enhanced using recommendation algorithms and machine learning techniques, etc., is compared to product data from product files, this can allow accurate, continually improving, personalized product recommendations from the system.

[0077] According to some embodiments, a relatively low level of integration of 3D scanners can be utilized to generate digital avatar profiles. In some examples, sensors or scanners that can be used can include structured light, light time, photogrammetry, or any other type of 3D and / or 2D scanning technology. Vendors of such technology include, but are not limited to, PrimeSense™ based scanners, pillow structure sensors, 3D Systems sensors (3D-Systems Sense) and iSense sensors, Intel™ RealSense sensors (standalone or machine integrated), iPad or tablet based scanning platforms, PC (integrated and external), Android + RealSense (next generation) devices, and Google Project Tango devices, among others.

[0078] Reference is now made to Figure 1B , Figure 1B 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 a smartphone or tablet, including but not limited to a camera, an application, and a data connection; a store computing device or point of sale computing device, kiosk, or automated shopping assistant device 184, typically at or near a store, such as an electronic device having one or more cameras, sensors, or scanning devices, an application, and a data connection; wherein the mobile device 182 and / or automated shopping assistant device 185 are connected to a communication cloud 186. The communication cloud 186 includes a digital product module 190 for saving, consolidating, and managing data for a plurality of products; a digital avatar profile module 188 for saving, consolidating, processing, and managing profile data for a plurality of users; and a matching module 192 for matching product and avatar profile data to facilitate product recommendations and other matching functions. The platform 180 further includes a product customization module 194 for ordering customized products based on matching module output and / or user selection; and a product ordering module 196 for enabling ordering of products based on matching module output and / or user selection.

[0079] Reference is now made to Figure 2 , Figure 2is a flowchart showing a process to facilitate personalized shopping, whether online or offline, according to some embodiments. As can be seen, product information from product database 200 can be used for products to be discovered, purchased, or manufactured. At step 205, historical data for the user can be retrieved, for example, based on previous user purchase history and research. At step 210, user preference data such as size, color, material, type preference, etc. can be obtained. At step 215, scan 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 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 the various input data from steps 205, 210, and 215, a multi-dimensional user shopping profile (hereinafter referred to as a user shopping avatar) can be developed, 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 construct that can optionally use feedback and additional input from steps 205, 210, and / or 215 to continually improve in the way it 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 across multiple stores (e.g., any chain store in a network or any online retail store, or affiliates of an online and / or offline store or platform).

[0080] At step 225, a match of the user shopping profile to products being researched or needed is performed. In this step, product data from product database 200 is matched to products being researched by the user, according to the particular user shopping profile, enabling advanced filtering of products that are not suitable for the particular user and advanced matching of suitable products according to the particular user's individual shopping profile and preferences. The matching step can be supplemented by providing recommendations for the user to the product matching process based on the user profile described above.

[0081] At step 230, product try-on data from feedback from in-person staff or remote staff can be used to help modify the matching of user data to product data, for example, feedback from a sales staff in a store can be used to update a user profile, or feedback from a remote staff, for example, connected via a smart phone or computer, can be used to update a user profile. In some cases, for example, a user can use feedback from a sales staff or a friend (e.g., which colors look good on a person or which size looks best, etc.) to update their shopping profile. In some cases, a user can use advanced graphics processing and 3D rendering to virtually try on a product being studied, such that the user can see themselves in the product being tried on according to a digital simulation of the product being placed on the user's shopping avatar. In some cases, the system can provide a static or dynamic high resolution visual output, for example, an animated avatar or character optionally fitted to the avatar, a picture and / or visual representation of the rendering being recommended. For example, such a rendering can allow a user to see a product being tried on to be depicted on the avatar, thereby helping the user to visualize details such as try-on, fit, color, style, material, etc. according to a color heat map, etc. For example, a color heat map can be used to indicate areas of tightness, tension, friction, etc. when a product is in contact with the body. As described above, a user can use the shopping avatar to provide further feedback to modify the user's shopping profile. At step 235, feedback can be obtained from a social network to which the user is connected or direct third party feedback to help modify the user's shopping profile.

[0082] At step 237, product customization can integrate data from product try-on feedback from step 230 and / or social feedback from step 235 to help further personalize a product being considered for acquisition according to the digital avatar and product try-on module 125 and / or social shopping module 130.

[0083] At step 240, a user can order a personalized product, whether within a physical store or an online store. In addition, a personalized product can be ordered from a manufacturer, which can produce the product based on a user's request such that the product is a one-off custom product for the user. Custom products can include, for example, various types of customization including material type, print sample, color, size, volume, angle, model variation, style, private customization, etc.

[0084] Reference is now made 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 a backend or computing system supporting a physical store, product information from a product database 300 can be used to tailor products discovered, purchased, or manufactured by an online user. In some embodiments, the product database is associated with a product data processing module adapted to perform high intensity computations on local point of sale devices and / or in the cloud according to type and demand. At step 305, historical data for a user can be retrieved, for example, based on previous purchases by the user in a store or chain. 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 user side, scan 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 smartphone, tablet, or other computing device can be used to enable effective photographing or scanning by the user. In several embodiments, a dedicated or general purpose camera or scanning device, kiosk, or stand (mobile or stationary) can be used by a shopping assistant, helper, salesperson, and / or colleague. At step 320, this geometric data is used by the personalized shopping system along with various input data from steps 305 and 310 to generate a multi-dimensional user shopping avatar or profile that includes user physical attributes as well as user behavior and user preference data.

[0085] At step 325, a matching of the user shopping profile to products being researched or needed is performed. In this step, product data from the product database 300 is matched to products requested by the user according to the particular user shopping profile. The matching step can be supplemented by providing recommendations for the user to the product matching process based on the user profile described above, enabling advanced filtering of products that are not suitable for the particular user and advanced matching of suitable products according to the particular user's individual shopping profile and preferences. This advanced filtering enables presentation of products that are generally suitable, optionally currently available, to, for example, a store salesperson or the user themselves, rather than having the user select unsuitable items, wasting shopping assistant and shopper's own time and resources. This also allows the user to benefit from matching and recommendation data generated for other avatars or users that can optionally share similar characteristics in an anonymous manner, enabling more intelligent and accurate matching and / or recommendations.

[0086] At step 330, product try-on data from feedback from in-person staff or remote staff can be used to help modify the matching of user data to product data, for example, feedback from a sales staff in a store can be used to update a user profile, or feedback from remote staff, for example, connected via a smart phone or computer, can be used to update a user profile. In some cases, for example, a user can use feedback from a sales staff or a friend (e.g., which colors look good on a person or which size looks best, etc.) to update their shopping profile. At step 335, feedback can be obtained from the user using active and / or passive methods. For example, active input of feedback can occur when the system receives actual feedback from one or more in-person staff and / or one or more remote staff regarding a try-on (e.g., how good / bad / unacceptable it was) or other aspects. Such feedback can allow the user to, for example, enter the selected option into the system via, for example, a text box or text input element, into which the user can enter the selected size, type, or other preference. Passive feedback can occur when the system receives actual feedback from sales information, returns, etc., regarding fit or other aspects, or by trying certain types, colors, sizes, etc., such that the system is able to learn from the user's past selections and behavior to further improve the personalization of the avatar as well as product information and try-ons for other users. In some cases, the user can use advanced graphics processing and 3D rendering to try on the product being studied, such that the user can see themselves virtually wearing the product according to a digital simulation of the product placed on the user's shopping avatar. As described above, the user can use the shopping avatar to provide further feedback to modify the user's shopping profile.

[0087] At step 340, the user can order a personalized product from the physical store, for example, for a product that is available in principle but not currently in the store, or to enable a specially requested product to be made based on the user's shopping avatar, such that the product is a one-off custom product for the user.

[0088] At step 345, the user can select a personalized product and / or modify or design the product, optionally based on products she / he has seen, liked, and selected in the store, to purchase a custom product to be created and / or manufactured for her / him. These modifications can include visual changes (such as name engraving, colors, materials, printing, etc.) as well as physical attributes (such as controlling the height of a shoe heel, the thickness of a glasses frame, etc.). At steps 340 and 345, these features can allow in-store customers to enjoy features that are typically limited to e-commerce and online shopping.

[0089] Reference is now made to Figure 4 , Figure 4is a flowchart for facilitating a personalized online shopping experience according to some embodiments. As can be seen, an online store can obtain product information from a product database 400 for selection of products to be offered to an online user. At step 405, historical data for the 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 preferences, etc. can be obtained. At step 415, scan 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 special or general purpose application on a smartphone, tablet, or other computing device can be used to enable effective photographing or scanning of the user. In many embodiments, a webcam, 3D camera, video camera, etc. can be used to obtain the scan or graphical data. At step 420, this graphical data is used by the personalized shopping system along with the various input data from steps 405, 410, and 415 to generate a multi-dimensional user shopping avatar or profile that includes user physical attributes as well as user behavior and user preference data.

[0090] At step 425, a matching of the user shopping profile to products being researched or needed is performed. In this step, product data from the product database 400 is matched to products that the user is researching, according to the particular user shopping profile, enabling advanced recommendations of product matches according to the particular user's personal shopping profile and preferences, for example, to help filter out products that are not suitable for the particular user, and to make advanced matches to suitable products.

[0091] 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 to product data, for example, to include data about which colors look good on a person or which size looks the best fit, etc., that the user can utilize to update their shopping profile. In further examples, codes can be used to provide product color recommendations, size or fit recommendations, etc. This feedback can be actively collected from the user, for example, based on purchase information, shipping and return shipping data, etc., or collected statically. At step 435, feedback can be obtained from social networks or social networks to which the user is connected to help modify the user's shopping profile. Additionally, human 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 in the online purchasing process. In some cases, advanced graphics processing and 3D rendering can be used to enable the user to virtually try on a product being investigated, such that the user can see themselves in the product based on a digital simulation of the product placed on the user's shopping avatar. This can be done using real-time simulation, taking into account live streaming of animated videos or high resolution images of the simulation, etc. In some embodiments, the "digital try-on" can include physical simulation to include precise positioning of elements on an avatar that is static or moving. As noted above, the user can use the shopping avatar to provide further feedback to modify the user's shopping profile.

[0092] At step 440, the user can order the product from the online store. Optionally, at step 445, the user can generate a personalized product from the online store to enable the manufacture of a specially requested product based on the user's shopping avatar, such that the product is a one-off custom product for the user. In the case of custom production output, the shopping system can connect directly to the company production hardware and ERP systems, if needed, 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, such as a DXF or DWG file. In many embodiments, this can be a custom routing card or production instructions and BOM file. Additional input can include visual presentations that will help the product manufacturer or printer to visually design the custom product.

[0093] In some embodiments, data from the product database 400 can be used with the body or avatar profile derived in step 420 to develop a custom product at step 445, optionally without product matching at step 425.

[0094] Reference is now made to Figure 5 , Figure 5is a flowchart showing an example of a personalized hybrid shopping experience according to some embodiments. As can be seen from the figure, at the backend or computing system supporting a physical store and / or an online store, product information from a product database 500 can be used to tailor products discovered, purchased or manufactured by an online user or in-store user. At step 505, historical data of the user can be retrieved, for example, based on previous user purchases in the store or chain of stores, whether an 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 front end or user side, scanned or graphical data of the user performed by the user or a shopping assistant can be obtained from, for example, standard photos, 2D and / or 3D scans, or from capture and processing using a POS kiosk or the like. In some embodiments, a dedicated or general purpose application on a smartphone, tablet or other computing device can be used to enable effective taking or scanning of the user. In many embodiments, a shopping assistant can use a dedicated or general purpose camera or scanning device, which can include a portable or non-portable device, a kiosk type or standalone device. At step 520, this graphical data is used by the personalized shopping system along with the various input data from steps 505, 510 and 515 to generate a multi-dimensional user shopping avatar or profile that includes user physical attributes as well as user behavior and user preference data. One advantage of this system is seamless transitioning, where the user can transition between online and offline shopping while enjoying the benefits of personalization through the use of an ever-updating personal profile in online and / or in-store scenarios.

[0095] In some embodiments, at step 525, for online shopping optionally located in a physical store, a matching of the user shopping profile to products being researched or needed is performed. In this step, product data from the product database 500 is matched to products requested by the user according to the particular user shopping profile, enabling advanced filtering of products that are not suitable for the particular user and advanced matching of suitable products according to the particular user’s personal shopping profile and preferences. This advanced filtering enables presentation of products that are generally suitable, optionally currently available, to, for example, a store salesperson or the user himself, rather than having the user select unsuitable items, wasting shopping assistant and / or the shopper’s own time and resources.

[0096] At step 530, product try-on data from in-person staff or remote staff feedback can be used to help modify the matching of user data to product data, for example, feedback from a sales staff in a store can be used to update a user profile, or feedback from a remote staff member, for example, connected via a smart phone or computer, can be used to update a user profile. In some cases, for example, a user can use feedback from a sales staff or friend (e.g., which colors look good on a person or which size looks best, etc.) to update their shopping profile. At step 535, feedback can be obtained from social networks or social networks to which the user is connected to help modify the user shopping profile. In some cases, a user can use advanced graphics processing and 3D rendering to virtually try on a product being researched so that the user can see themselves in the product according to a digital simulation of the product on the user shopping avatar. As described above, a user can use the shopping avatar to provide further feedback to modify the user's shopping profile.

[0097] 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 (e.g., a product that is available in principle but not currently in the store), or enable the manufacture of a specially requested product based on the user's shopping avatar so that the product is a one-off custom product for the user.

[0098] In some embodiments, at step 545, for a user in a physical store, a matching of the user shopping profile to a product being researched or needed is performed. In this step, product data from the product database 500 is matched to a product requested by a user according to the particular user shopping profile, enabling advanced filtering of products that are not suitable for the particular user and advanced matching of suitable products according to the particular user's personal shopping profile and preferences. This advanced filtering enables the presentation of products that are generally suitable, optionally currently available, to, for example, a store sales staff or the user themselves, rather than having the user select unsuitable items, wasting shopping assistant and / or shopper's own time and resources.

[0099] Reference is now made to Figure 6 , Figure 6is a flowchart illustrating an example of personalized shoe shopping online or offline according to some embodiments. As can be seen from the figure, insole information can be obtained from an insole product database at 600. Additionally, last information can be obtained from a last product database at 605. In some cases, the insole data, last data, and / or shoe model data can 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 example, to run a mesh analysis of each 3D last, which combines 2D DXF data, will be added to the last database 605. Additionally, shoe model data for a shoe to be discovered, purchased, or manufactured can be obtained from a shoe model database 610. In some cases, for example, 3D STL files can be imported for the last, while 2D DXF files can be imported for the insole.

[0100] At step 615, scan or geometry data can be acquired for the user, for example, from standard photographs, 2D and / or 3D image scans, or from capture and processing using an automated shopping assistant device, etc. This graphical data can be processed at 620 by the personalized shopping system, either on the cloud or in the unit itself, in order to generate a physical profile of the user based on the user's physical attributes. This profile can include all or some of the following attributes: a 3D mesh (including the exact geometry of the profile), an exact geometry 3D mesh (including one or more parts of the user's body), 2D images, 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 together are photographed or scanned while standing on the floor or another surface with reference objects next to or near the feet. In addition, the user's single foot or both feet can be scanned by a camera that scans around the foot at different angles, 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 scan 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, mesh division can also enable removal of excess geometry and / or fixing mesh errors, for example, including separating, recognizing and preparing each of the two feet, removing the floor, pants or other excess material from the scan, etc. In some cases, processing of the scan data can allow for foot alignment (which also aids in separation or individualization of the two feet) to provide accurate measurements of the two feet, including volumetric analysis (to determine length, width and height of general and specific areas) and cross-sectional analysis (to determine area, perimeter and other dimensions at specific cross-sections). The scan data processing can allow for smoothing of the edges of the scanned foot, construction of missing volumes, construction of the foot sole, etc. In some cases, the full foot volume and / or area-specific volumes can be extracted from the model as additional information. At step 625, the processed user scan data can be parameterized, for example, to extract exact length, width, height, arch, ball of the foot, cross-section, perimeter, 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 a comparison of XYZ parameters of various anatomical parts on different cross-sections of the foot center. The width of the foot can be calculated based on the volume of the head sock calculated on the 3D mesh and 2D cross-section levels. The length of the foot can be calculated from the combination of the total length and the "ball of the foot length", which represents the distance between the heel and the first metatarsal bone. In addition, user-specific conditions such as pain, infection, injury, etc. can also be identified and integrated into the user's shoe shopping profile. In this step, the pronation or supination status of the foot can also be analyzed. In addition, the arch of the foot can be identified and measured for the fitting of support insoles or other prostheses.

[0101] At step 630, historical data of the user can be retrieved, for example, based on previous user purchases in a store or chain of stores, whether online experience and / or in-store experience. At step 635, user preference data such as size, color, material, type preference, etc. can be acquired. At step 640, by processing the various input data from steps 615, 620, 625, 630, and 635, a multi-dimensional user shoe shopping profile (hereinafter referred to as user shopping avatar) can be created, generating a user shoe shopping avatar or profile that includes user physical attributes as well as user behavior and user preference data. In some embodiments, the user's shoe shopping profile includes both feet of the user (typically different), with parameters determined separately for each foot, thereby benefiting from separate profiles for the left and right feet.

[0102] At step 645, a matching of the user shoe shopping profile to the shoe product being examined, researched, or needed is performed. In this step, product data from product databases 600, 605, and 610, including dimensions, is matched to the product being researched by the user, according to the specific user shopping profile, thereby enabling an advanced filtering of products that are not suitable for that specific user, and an advanced matching of suitable products, according to the specific user's personal shopping profile and preferences. The matching step can be supplemented by providing recommendations to the user based on the above-mentioned profile based matching process. This step can directly use the model of the digital profile of the foot and shoe, and / or the parameterized digital model.

[0103] At step 650, product try-on data using feedback from in-person or remote personnel can be used to help modify the matching of the user data to 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, for example, via a smartphone or computer, can be used to update the user profile. In some cases, for example, a user can use feedback from a salesperson or friend (for example, which colors look good on a person or which size looks the 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 researched, such that the user can see themselves virtually wearing the product according to a digital simulation of placing the product onto the user shopping avatar. As mentioned 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 acquired from social networks to which the user is connected to help modify the user shopping profile.

[0104] At step 660, the user can order a pair of personalized shoes in a physical store or in an online store. Further, the personalized product can be ordered from a manufacturer that can produce the product based on the user's request such that the product is a one-off customized product 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.

[0105] Reference is now made to Figure 7 , Figure 7 is a flowchart illustrating an example of online or offline personalized eyewear shopping and manufacturing according to some embodiments. The eyewear can include, but is not limited to, sunglasses and any type of optical eyewear. As can be seen from the figure, at 700 eyewear model information from an eyewear product database can be obtained from an eyewear model or product database of various file types or data structures. According to some embodiments, eyewear frame acquisition can be achieved by preparing parametric models (e.g., by generating model parameters for multiple input types, processing resolution adjustments, implementing automatic fitting and skinning, integrating range of motion animations, and correcting shape keys, etc.).

[0106] At step 705, the user's historical data can be used, the historical data including, for example, facial landmarks and measured distances, such as interpupillary distance, location of each eye, cheeks, temples, and various points on the ears and nose, etc. Also loaded are general parameters for each face, optionally including volume, proportions, and standard shapes, which can be retrieved from online and / or store experiences, for example, based on previous user surveys and / or purchase situations in a store or chain. 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.

[0107] At step 715, the user's scan or graphical data can be acquired, for example, from standard photographs, 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 sections above, or alternative 2D methods using or not using reference objects for sizing. Generally, user head and face scan data can be acquired at this stage. In some embodiments, head and face model preparation and analysis can include model preparation, such as smoothing and cleaning, reconstruction of meshes with enhanced topology and / or optimized detail / weight ratio compression for real-time optimized display, and / or orientation and alignment. In addition, facial feature recognition can be used, for example, to generate a face model presented from multiple angles (e.g., 3 to 15 angles, to help determine normals, depth, color). Additionally, computer vision and / or machine learning algorithms can be applied to identify, for example, eyes, nose, nose bridge, temples, ears, etc. Processing of the scan data can also include projection of 2D landmarks to the 3D model, and verification of anatomical landmarks. In the absence of landmarks, statistical or empirical results-based evaluation can be applied to replacement of these landmarks.

[0108] At step 720, the processed user scan data can be parameterized to, for example, extract precise face length, width, height, proportions, nose width and volume, ear size, ear height, ear position, skin color, and / or other relevant face features and dimensions, etc. At 725, the personalized shopping system can process this data along with user history data from 705 and user preference data at 715 to generate a user's eyewear shopping profile based on the user's face profile and other physical attributes, as well as user behavior and user preference data. In some embodiments, the user eyewear shopping profile includes both eyes of the user (typically different), benefiting from separate profiles for the left and right eyes. In some embodiments, an optical prescription will be collected using a picture, an electronic form, or an embedded test method within the application, or in some cases from an external prescription file. According to some embodiments, the system can recommend a specific model based on face shape, previous purchases and history, and optionally based on comparison (optionally anonymized) to similar avatars.

[0109] At step 730, a match of the user's eyewear shopping profile to eyewear products being researched or needed is performed. In this step, product data from the product database 700 is matched to products being researched by the user, according to the specific user shopping profile, enabling advanced filtering of products that are not suitable for the specific user, and advanced matching of suitable products, according to the specific user's personal shopping profile and preferences.

[0110] At step 745, each frame is adjusted to fit the user's face using frame customization, which can include, for example: taking key measurements of the subject's or user's face; applying an iterative comparison algorithm to face adjust the frame; digitally positioning the frame on the subject's face according to each prepared user eyewear shopping profile or avatar, etc., orienting the frame appropriately to the face, scaling the size, width, and position of the nose bridge, adjusting the eyewear arm folding, eyewear arm length, and wide angle tilt or angle, etc. according to the subject's face.

[0111] At step 735, product try-on data using feedback from in-person or remote personnel can be used to help modify the matching of user data to product data, for example, feedback from a salesperson or optician in a store can be used to update the user profile, or feedback from a remote person connected, for example, via a smart phone or computer can be used to update the user profile. In some cases, for example, a user can use feedback from a salesperson or friend (e.g., which colors look good on a person or which size, style, type looks best, etc.) to update their shopping profile.

[0112] In some embodiments, at step 745, advanced graphics processing can be used for the user to virtually try on the product being investigated, so that the user can see themselves wearing the eyewear according to a digital simulation of the eyewear placed on the user's shopping avatar's face. In some embodiments, the virtual try-on can include features such as a physical simulation that positions the eyewear in the correct or optimal position and can slide the eyewear along the nose. Additionally, the try-on can include an overlay of pictures or 3D models on the face model and / or a series of pictures or any combination of the above. Animation effects can be included to emphasize different attributes of the eyewear, including custom animations in the case of custom frames, or other animations such as fly-in / fly-out animations for switching between pairs of eyewear. As mentioned 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 frames on a digital version of his / her face to provide a deep visual feedback. For example, the user's face can be displayed in a 3D viewer and the appearance can be enhanced in order to provide one or more of 3D view manipulation (e.g., zoom, rotation) and animation effects to cater to the user experience, such as a face that is breathing, smiling, blinking, or other animated or static visual effects. Furthermore, the user can thus be presented with customization options including: selecting any frame from a collection, customizing frame and lens color, customizing automatically recommended try-ons, personalization of documents (e.g., text, prescription, etc.), and enabling side-by-side comparison between different frames. At step 740, feedback can be obtained from social networks or social networks to which the user is connected to help modify the user's shopping profile. Of course, other steps of the step combination can be used to process the input data.

[0113] Step 750 involves various embodiments in which the system enables production of custom eyewear to fit the user based on the automated or semi-automated parametric design of the frames. At step 750, relevant eyewear production printing and cutting files can be prepared by the system, if needed. 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 for visualization purposes at the front end of the application, while maintaining high resolution models for printing file preparation, which can include, for example, high resolution features and details such as hinges, grooves, angles, temples, etc. The printed models of the eyewear customization described herein can be automated and / or manual. Furthermore, the file preparation for 3D printing can include automatic resolution of printing issues, generation of normal, duplicate, holed, and non-manifold geometries, etc. In some embodiments, the system can create a custom label on the eyewear or eyewear, for example, including text, a QR code or a barcode, which will enable traceability throughout the production and distribution process.

[0114] At step 755, the user can order a pair of personalized eyewear within a physical store or an online store. Furthermore, the 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-off custom product for the user.

[0115] According to various embodiments, systems and processes for automated personalized product ordering using digital mirrors or personalized viewing protocols are described. Virtual reality and / or augmented reality can be integrated to manipulate, view, and / or try on specified devices, such as existing or designed eyewear, on a screen, a table, a smartphone, a communication device, etc., thereby enabling a visual representation of the customized or non-customized frames on the face of the customer.

[0116] According to many embodiments, a file format is provided that is adapted to enable personalized product ordering. The file format incorporates all relevant information including physical attributes and personal preferences to represent the user and assist the user in performing personalized customization or non-customized shopping for clothing, eyewear, footwear, or other body-related products. The avatar standard format can be used to plug into substantially any online or physical shopping platform to allow for customization-enabled try-on of the physical and aesthetic needs and preferences of the customer by the store.

[0117] Reference is now made to Figures 8A-8Gdifferent views of a POS device, kiosk, or information kiosk in accordance with some embodiments. In some embodiments, the shopping assistant device generates a user avatar based on one or more of: 3D scanning, image acquisition using one or more cameras, measuring a user profile with a platen, etc. In some embodiments, a standing pad can be used to act as a positioning pad or reference for a user to stand on to perform a body scan. In some cases, the standing platform can include lighting at the bottom of the standing pad to support accurate measurements of any color from the cameras or scanners on the device by minimizing or marginalizing shadows and causing a black / white perimeter effect. In some embodiments, there can be proximity sensors for each foot to measure if the foot is in place or close and tell the user to move if needed. In addition, the device can include distance or proximity sensors / robots that identify an approaching user to draw the user to the device, in which case the device can automatically start when the user enters a selected geographic area. In several embodiments, sensors can be used to measure the height of a user's instep, for example, to establish an instep volume. In many embodiments, specialized sensors can be used, such as sensors for measuring diabetic ulcers, etc. Such sensors can be used, such as cameras, 3D sensors, full perimeter cameras, and / or multiple cameras.

[0118] Figure 8A is an exploded view of an example of components of a POS device or kiosk apparatus in some embodiments. As can be seen, the kiosk apparatus 800 can include a standing base 805, a light source to optionally illuminate the standing base, proximity sensor(s) 816 to identify the location of a foot to be scanned by the kiosk apparatus 800, a standing pad 815 having a space for both feet to stand on, and a pad layer 820 on which the feet are mounted. In some embodiments, the pad layer 820 can integrate pressure sensing mechanisms, such as a flatbed scanner, a pin plate, a platen, a touchscreen-type surface with capacitors and / or pressure sensor elements, etc., to determine arch size. In some embodiments, the arch size measurement elements can be used to determine the need for and / or size of an insole for the user.

[0119] In some embodiments, the arch size measurement elements can be used to determine the need for and / or size of an instep profile for the user.

[0120] In some embodiments, the arch size measurement elements can be used to determine the need for and / or size of a metatarsal ball profile for the user.

[0121] In many embodiments, one or more lasers or other illumination mechanisms can be used to determine arch, ball, or step size. In one example, a laser from above the foot can be used to display the height of the foot or arch and bridge size, for example, by identifying the size of the "hidden" area where the laser cannot be seen, and using the "hidden" space to determine parameters (such as height) at different points on the foot. In another example, a diffraction grating, prism, or other filter uses multiple lines to enable identification of the highest points of the foot.

[0122] In several embodiments, one or more lights, optionally of 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 to help identify non-foot space. In many embodiments, one or more of the arches can be identified, for example, using background subtraction techniques.

[0123] In addition, kiosk device 800 can include a main body 822, which includes a computer mount 825 and a camera mounting element 826 for mounting one or more camera elements 835, a panel element 830, another panel or cover element 845, a computing screen, preferably a touch screen PC or tablet 840, and optionally, the main body 822 has a location for mounting a proximity sensor 850, for example, for identifying the proximity of a user to the computing device.

[0124] Figure 8B Front view of an example of a POS device or kiosk device.

[0125] Figure 8C Isometric view of an example of a POS device or kiosk device.

[0126] Figure 8D Isometric front view of an example of a POS device or kiosk device.

[0127] Figure 8E Isometric back view of an example of a POS device or kiosk device.

[0128] Figure 8F Side view of an example of a POS device or kiosk device.

[0129] Figure 8G Top view of an example of a POS device or kiosk device.

[0130] Figure 8H View of an example of one or more sensors in a POS device or kiosk device. As can be seen, the kiosk device can be configured with multiple sensors, for example, one or more proximity sensors, and an LED panel can be configured to provide a light source from below the standing area.

[0131] Reference is now made toFigure 9 , Figure 9 A schematic of a shopping assistant system 900 is shown, including 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 on the cloud), and / or to send a user shopping profile to the cloud. In addition, according to some embodiments, remote user mobile devices, such as smartphones, tablets or other cameras supporting mobile communication devices 905, 910 are 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 capturing information about a person's single or double foot under IR / NIR or visible light conditions, optionally using standard pictures / scans, video, a series of pictures or advanced sensing components (e.g., structured light, time of flight, etc.) simultaneously. Devices 905 / 910 typically include a gyroscope to provide camera orientation data to the device camera, for example, to allow taking a picture only when the camera is substantially flat. In some embodiments, internal sensing components and / or additional sensors can be connected to the communication devices 905, 910 to provide supplemental data to the system. Such sensors can help improve the accuracy of the measurements, assist the user during the capture of data with real-time feedback, and / or provide input to the computing engine, for example. Remote devices 905 and 910 can communicate with the communication cloud 920, and in particular, can connect to a digital shopping avatar or profile 925 of a user of the device. In some embodiments, a user can use a mobile device 905, 910 to generate a shopping profile for one or more users with or instead of the automated shopping assistant device 906.

[0132] Reference is now made to Figure 10 , Figure 10 A schematic of a shopping assistant system 1000 and workflow between components is shown. As can be seen, a launching tablet or shopping assistant device 1005 can scan a user to generate a shopping profile for the user. The generated profile is sent to a mobile device 1010 of the user, and can subsequently be used to scan a product, such as a shoe 1015, optionally via a product tag, such as a QR code 1020, representing the selected product. In addition, in some embodiments, a user can use a mobile application 1025 to build a shopping profile. In some embodiments, at 1030, a user shopping profile can be used to enhance in-store shopping. In some embodiments, at 1040, a user shopping profile can be used to enhance online shopping.

[0133] Reference is now made to Figure 11A , Figure 11Ais a flowchart showing an example of personalized footwear shopping in a shopping store by using an in-store or POS automated shopping assistant device in conjunction with a mobile computing device application. As can be seen, at step 1100, a 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 provided with interactive guidance to ensure the user is standing in the correct position, enabling 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 in 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 scanning a selected product using a coded tag (e.g. QR code or barcode). In general, scanned products can be processed in relation to the user avatar, for example to determine whether the product is suitable for the avatar, suitable for 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 product with product data, for example to assist in determining purchase options, inventory status, product quality, product features, reviews, sizing, 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.

[0134] Reference is now made to Figure 11B , Figure 11Bis a flowchart showing an example of personalized footwear shopping in a shopping store by using an in-store or POS automated shopping assistant device in conjunction 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 provided with interactive guidance to ensure the user is standing in the correct position, enabling accurate scanning. At step 1110, the device scans the body or body part / element, and at step 1115, the scan 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 an avatar, 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 device's software, code, or application. At step 1130, the user can open a 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 research, for example, by scanning a selected product using a coded tag (e.g., QR code or barcode). Generally, the scanned product can be processed in a manner that takes into account the generated shopping avatar, for example, to determine whether the product is suitable for the avatar, suitable for 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 product with advanced product data, for example, to help determine ordering options, inventory status, product quality, product features, reviews, sizing, etc. In other cases, at step 1140, the application can connect to a communication cloud or other database to match the selected product with advanced user data, for example, to help determine user preferences, user history, and user profile updates, etc. In some cases, at step 1145, the application can present the user with recommendations, purchase data, purchase options, reviews, news, etc., to help enhance the online store shopping experience. In some cases, at step 1150, the application can present the user with recommendations, purchase data, purchase options, reviews, news, etc., to help enhance the in-store shopping experience, for example, by providing shopping suggestions, options, shortcuts, access to additional databases, etc.

[0135] In some embodiments, a user shopping experience can be performed for other users connected with the user of the shopping assistant. In such cases, the user application can contain shopping profiles for multiple users, allowing the user of the mobile device to perform shopping for multiple users according to the shopping profiles of the users.

[0136] According to some embodiments, the mobile and / or user avatar can be shared with other users. For example, a user can have access to or control multiple user profiles under the user's authorization, e.g., in a wallet or holder of avatars or profiles. In this case, the controlling user can shop on behalf of the other users. For example, a parent can save profiles of all of his or her family members, allowing the parent to easily shop online and / or offline for all of the associated family members.

[0137] According to some embodiments, additional personalization, such as an icon or picture, can be provided for each user mobile shopping avatar or user shopping avatar. This personalization can be particularly useful for a controlling user managing multiple users or mobile shopping avatars. This information associated with any identifier can be saved on the cloud avatar database and associated with the user in any platform she / he uses. For example, in the case of a family member scanning and saving profiles of one or more of his or her family members, these profiles can be shared with the other family members that can be loaded into the in-store system or e-commerce website used at the moment, and this personalization information is used subsequently. In the case of a website, the output can be personalized according to this personalization data, and can even include a picture or avatar or 3D model of the other user 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 used by the user legally.

[0138] According to some embodiments, the online store can include a user shopping virtual assistant that uses the profile plug-in or other digital object, which can appear on substantially any web page (whether or not optimized for a mobile phone, desktop, laptop, tablet, wearable device, etc.) to provide recommendations, guidelines, or other assistance to the user when associated. For example, the virtual shopping assistant can show information about different fit 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 can be informed that the equivalent size for his or her 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 fit, etc., the shopping virtual assistant can also make suggestions or guidance based on the user's preferences. For example, in the Nike shoe store, the shopping assistant can suggest that the user look for US size 10.5, athletic shoes, blue or green, etc.

[0139] In some embodiments, the virtual assistant can take 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 portions that are of interest or relevant to the 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 that can represent the content that she / he can be most interested in and the content that is most suitable for him or her.

[0140] 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 custom shoe being watched according to the user's shopping profile can be presented in 3D from all sides and angles, helping the user to view the product from multiple dimensions.

[0141] According to some embodiments, a virtual try-on module can be provided to allow the product being viewed to be worn on the shopping avatar.

[0142] According to some embodiments, the user shopping avatar can be a one-time avatar of the 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, for example, all owned by a parent entity. In many embodiments, the user shopping avatar can be applicable to any or all stores via a common user profile connected to the cloud.

[0143] Reference is now made to Figures 12A-12B , Figures 12A-12B is an example of a screenshot of an interactive screen of a shopping assistant screen for guiding the user to place their feet on the marked mats, according to some embodiments;

[0144] Reference is now made to Figures 13A-13B , Figures 13A-13B is an example of a screenshot of an interactive guide of a shopping assistant screen or mobile screen for helping the user to define their profile and their contact information, according to some embodiments;

[0145] Reference is now made to Figures 14A-14B , Figures 14A-14B is an example of a screenshot of a shopping assistant screen or mobile screen showing a pair of scanned feet and a simulation of the lower leg, according to some embodiments;

[0146] Reference is now made to Figures 15A-15B , Figures 15A-15B is an example of a screenshot of a shopping assistant screen or mobile screen for helping the user to enter behavior-related information that can be used to provide better user-related output.

[0147] Reference is now made to Figures 16A-16D , Figures 16A-16D A perspective view of an example of a shopping assistant standing surface is shown, according to some embodiments. As can be seen in the figure, the standing surface 1600 is typically a flexible surface, such as a mat or carpet, optionally composed of PVC, rubber, polyurethane, paper, cardboard or any other suitable material. The standing surface 1600 typically includes a 3D portion or element 1605 which replaces the wall and enables correct positioning of the feet for scanning. This 3D element serves as a foot stop against which the instep is placed. The standing surface 1600 typically includes markers 1610, dots or indication graphics to improve the accuracy of the scanned image. In some embodiments, the markers 1610 can serve as signs, where there can be a variety of signs and the signs can have different sizes, dimensions, functions, etc., all of which can be the same or some of the signs can be different from the others.

[0148] Figure 17 An additional form of a shopping assistant standing surface is shown, according to some embodiments. As can be seen, there is a 3D foot placement element 1705 for each foot.

[0149] Figure 18 Another form of a shopping assistant standing surface is shown, according to some embodiments. As can be seen, there are 3D foot placement elements 1805 of different shapes.

[0150] Figure 19 A first user scenario is shown, according to some embodiments, in which a virtual graphic example is provided showing the use of a shopping assistant device. As can be seen, the assistant 1900 can use a standard camera 1910 (e.g., a phone or tablet) and / or a depth camera to take or scan the system user 1905.

[0151] Figure 20 A second user scenario is shown, according to some embodiments, in which a virtual graphic example is provided showing the use of a shopping assistant standing surface. As can be seen, the system user 2000 can use a standard camera 2005 (e.g., a phone or tablet) and / or a depth camera to perform a selfie or scan.

[0152] Figure 21 A picture showing an example of a user positioned on a shopping assistant standing surface, according to some embodiments. As can be seen in the figure, the standing surface 2100 typically includes a 3D portion or element 2105 (which replaces the wall) and enables correct positioning of the feet for scanning. This 3D element serves as a foot stop against which the instep is placed. The standing surface 2100 typically includes markers or indication graphics 2110.

[0153] According to some embodiments, virtual scan pads can be used to enable user devices to generate accurate scans of their body (e.g., the user's feet) without a physical pad or marker surface, as described above. In some embodiments, a reference object such as a rectangular piece of paper or card is needed to enable the shopping assistant application, device, and / or system to accurately map and scan the user's body. In many embodiments, no reference object is needed.

[0154] In some embodiments, the user device, application software, and / or server can integrate augmented reality (AR) functionality to help the user to make accurate scans without the need to use a physical scan pad. For example, known AR toolkits, such as Apple's ARKit or Google's ARCore, can be used to provide AR functionality in the shopping assistant application. Thus, AR can be used to provide virtual assistance to the user and / or to provide a virtual pad or surface (with lines and markers, etc., as needed) to the user to guide the user to stand properly to be able to perform accurate scans. 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., tell the user to position themselves differently, change the light, etc., to enhance the scan.

[0155] 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 virtually anywhere while the system imposes the virtual scan mapping on the user's feet and captures the relevant scan data as well as the virtual pad markers (whether visible or transparent) to generate the shopping profile and / or avatar.

[0156] In some embodiments, angle measurement devices can be provided to enable angle control so that the user can scan at various supported angles and still generate accurate scans. For example, angle measurement graphics that display the state of the device's accelerometer and / or gyroscope table state can be used to display whether the user's current scan angle is acceptable, and if not, to help the user to scan at a more appropriate angle.

[0157] In several embodiments, focus enhancement devices can be provided to enable the user to produce accurate scans and, in parallel, to be able to observe the focused scanned object. For example, one or more captures of the feet and / or environment can be taken in AR mode, and one or more captures of the feet and / or environment can be taken in picture (focus) mode, such that when viewing the AR environment, the focused image of the feet can be imposed in the AR view to ensure that the focused image of the feet is constantly displayed.

[0158] 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 (e.g. a foot) and place a virtual shoe on the foot. In this way, by using AR to present a selected shoe on the user's foot, different types, sizes, kinds, 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 here with respect to the foot

[0159] In many embodiments, different processing algorithms can be used to achieve optimal profile generation and / or display of different feet. Thus, scans can be processed by a variety of 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 on the best profile to use.

[0160] Figures 22A-22J is an example of a screenshot and tutorial screen showing a series of steps to guide a user in using a virtual scanning mat according to some embodiments. As can be seen from the figure, the system, device, apparatus and application take steps to provide a user with a virtual standing surface generated using augmented reality. The virtual standing surface typically includes virtual markers (such as dots, lines and indicator graphics) to enhance the accuracy of the scanned image and to facilitate user use.

[0161] Figure 22A is a screenshot showing an example of a GUI of a shopping assistant screen to guide a user on how to prepare to use a virtual shopping assistant according to some embodiments. As can be seen, the user can be asked to, for example, remove shoes, wear appropriate socks, and prepare an appropriate reference object such as a rectangular card or paper.

[0162] Figure 22B is a screenshot showing an example of a GUI of a shopping assistant screen to guide a user on how to prepare a selected reference object for scanning before using a virtual shopping assistant according to some embodiments.

[0163] Figure 22C is a capture showing an example of a user holding a smart phone (displaying a GUI of a shopping assistant screen) according to some embodiments to guide a user in calibrating a user device with an environment to be used for a virtual assistant. As can be seen in the example provided, the user can be asked to slowly move their phone or device around until an indication is provided (such as a screen or frame color change) showing that the device has mapped or otherwise successfully scanned the environment. For example, this initial scan can map the reference object and other details of the environment and this data can then be processed to determine the dimensions of the reference object and necessary environmental elements in order to be able to accurately measure a user's body in the next steps.

[0164] Figures 22D-22E is a capture showing an example of a user holding a smart phone (displaying a GUI of a shopping assistant screen) according to some embodiments, for guiding the user to scan an environment to be used for a virtual assistant. As can be seen in the example provided, the user can be requested to move their phone or device closer to the page or reference object, and click on the digital image of the reference object in order to tell the application to generate a virtual scan pad.

[0165] Figure 22F and Figure 22G is a capture showing an example of a user holding a smart phone (displaying a GUI of a shopping assistant screen) according to some embodiments, for guiding the user to scan an environment to be used for a virtual assistant. As can be seen in the example provided, the user can be requested to move their phone or device closer to the page or reference object, and click on the digital image of the reference object in order to tell the application to generate a virtual scan pad.

[0166] Figure 22H is a capture showing an example of a user holding a smart phone (displaying a GUI of a shopping assistant screen) according to some embodiments, for guiding the user to scan an environment to be used for a virtual assistant. As can be seen in the example provided, the user can be requested to move their phone or device closer to the page or reference object, and click on the digital image of the reference object in order to tell the application to generate a virtual scan pad.

[0167] Figure 22I is a capture showing an example of a user holding a smart phone (displaying a GUI of a shopping assistant screen) according to some embodiments, for guiding the user to scan an environment to be used for a virtual assistant. As can be seen in the example provided, the user can be requested to move their phone or device closer to the page or reference object, and click on the digital image of the reference object in order to tell the application to generate a virtual scan pad.

[0168] Figure 22J is a screenshot showing an example of a GUI of a shopping assistant screen, showing a virtual scan pad in a selected location for the user to stand on or "inside" the virtual scan pad for scanning the user's body or in this case feet. The user device can now scan the user's feet and process the scanned data based on the use of the virtual scan pad to present an accurate profile of the user's feet.

[0169] Figure 23is a flowchart depicting the steps in the process of virtual shopping profile generation, according to some embodiments. 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 the profile generation scan, for example, for a foot scan, the user can be asked to remove shoes, wear appropriate clothing and prepare an appropriate reference object. At step 2310, the user is instructed to place the reference object in the appropriate location, for example, against a wall in the room. At step 2315, the user is instructed to capture the environment (including the reference object capture) 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 a virtual image of the user) can use AR renderings of the user, depicted on a virtual scan plane or map, to further assist or guide the user in performing the scan properly. At step 2325, the user is instructed to stand in the digitally superimposed virtual scan mat. At step 2330, the user is instructed to start the scan by clicking on 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 real or digital store using the shopping profile.

[0170] In some embodiments, the shopping assistant standing surface can include active components (such as lights, detectors, sound, etc.). In such cases, the shopping assistant standing surface can include a power source (optionally a battery-powered power source), as well as one or more suitable sensors.

[0171] In some embodiments, the shopping assistant standing surface can include a platen (optionally supporting Bluetooth) to help receive additional data about the user's arch shape.

[0172] In some embodiments, the shopping assistant standing surface can be foldable, for example, for reasons of storage, shipping, or display.

[0173] In further configurations, the shopping assistant standing surface can be integrated into a "fitting chair".

[0174] In some embodiments, the shopping assistant standing surface can include two standing surfaces with two different colors (for example, for image recognition).

[0175] In some embodiments, the shopping assistant standing surface can be placed on, fitted on, or integrated into a fitting chair or stool. In such cases, the standing surface can be placed to accommodate the user's feet when in a seated position.

[0176] In some embodiments, the shopping assistant standing surface can include augmented reality (AR) functionality, allowing a user standing on the standing surface to browse shoes on his or her feet and see them on a generated model. For example, this can allow a customer to see his / her bare feet or feet in socks and see through AR glasses or phone / tablet that he / she can browse different shoes based on her / his feet from the augmented reality tracking.

[0177] In some embodiments, the shopping assistant device can help chain stores generate online and / or offline loyalty by allowing automated shopping assistance, proactive sales and cross-selling, etc. in multiple stores.

[0178] In several embodiments, the user's shopping experience for footwear can be substantially enhanced by applying the following steps: measuring the user's physical profile on the device 185 and providing the user's standard size and modifications for different shoes / brands; retrieving the customer's ID or shopping profile from the customer's mobile computing or communication device; and retrieving the customer's ID or shopping profile from the device 185 to the communication cloud.

[0179] In a first user case, where the user does not have a previous user profile, the shopping assistance process can be implemented as follows: the user typically takes off the shoes and stands on the launch pad or shopping assistant device at the entrance of the store or shopping area. 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 to the user's mobile device running the shopping assistant application, for example using email, beacon, SMS, QR code, IR beam, etc. The user can then scan the desired shoes, whereby the device is configured to match the desired shoes and then try them on the avatar to provide the best try-on. The device can also provide the user with relevant product information, such as availability, colors, sizes, related shoes, ratings, etc.

[0180] In the case of a second user with multiple devices, the shopping assistance process can be implemented as follows: The user typically removes their shoes at the entrance of a store or shopping area and stands on a launch tablet or shopping assistant device. In the current example, a footwear application is described. The device then measures / scans a region of the user's body (e.g., the 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 to the user's mobile device running the shopping assistant application, for example using email, beacons, SMS, QR codes, IR beams, etc. The user can then scan for desired shoes, whereby the device is configured to match the desired shoes, and then try on the desired shoes on the avatar for optimal fit. The device can provide the user with expert or advisory information, thus acting at least in part 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 for measuring movement / style / weight, etc.

[0181] In the third user scenario, 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 / reviews from the online world + social feedback + rankings, sales information / history, recommendations, upselling, cross-selling, etc.

[0182] For purposes of illustration and description, the invention has been given above. It is not intended to be exhaustive or to limit the invention to the precise forms disclosed. Those skilled in the art will understand that many modifications, variations, substitutions, alterations, and equivalents are possible in accordance with the foregoing teachings. Therefore, it should be understood that the appended claims are intended to encompass all such modifications and alterations falling within the true spirit of the invention.

Claims

1. A shopping assistant system, comprising: processor; and A memory that communicates with the processor and stores instructions, which, when read by the processor, enable the shopping assistant system to: A virtual scanning pad is generated using a mobile device, the virtual scanning pad including an augmented reality representation of markers configured to guide image scanning; The mobile device provides a display screen including the virtual scanning pad, which includes digitally overlaid markers to guide the user to stand properly for accurate scanning of a part of the user's body without referencing a physical pad or marker surface; When the part of the user's body is within the mark on the virtual scanning pad, an image of the part of the user's body is acquired from the mobile device; Based on the processing of the image, a 3D model of the part of the user's body is generated, wherein the 3D model includes user body measurement data calculated based on the image; At least one product recommendation is generated using a machine learning model, based at least on the user's body measurement data. Displaying at least one product recommendation that allows users to try on clothes in the 3D model; and In response to receiving user feedback related to the at least one product recommendation, the machine learning model is retrained using the user feedback.

2. The shopping assistant system according to claim 1, wherein, Generating the at least one product recommendation also includes identifying product purchases or recommendations from other users who share one or more profile attributes with the user.

3. The shopping assistant system according to claim 1, wherein, The virtual scanning pad includes one or more augmented reality-generated markers to be aligned with and configured to align with the portion of the user's body according to the scanning process.

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

5. The shopping assistant system according to claim 1, wherein, When the instruction is read by the processor, the shopping assistant system also causes the shopping assistant system to send the at least one product recommendation at the point of sale to a computing device associated with the user, based on authorization received from the user, wherein the computing device allows the user to modify the at least one product recommendation for the user, and wherein the at least one product recommendation is displayed on the 3D model of a part of the user's body and is provided for display on the computing device associated with the user.

6. The shopping assistant system according to claim 1, wherein, The machine learning model is configured to generate the at least one product recommendation based at least on user shopping history data, user preference data, and at least one measurement of a part of the user's body.

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

8. The shopping assistant system according to claim 1, wherein, When the instruction is read by the processor, it also causes the shopping assistant system to: Acquire scanned product data, wherein the scanned product data is obtained based on tags associated with the product; Based on the user's body measurement data, the recommended size of the product is determined; and The product is displayed as a try-on on the 3D model, along with the recommended size for the product.

9. The shopping assistant system according to claim 8, further comprising: Based on the recommended dimensions of the product, a second 3D model of the product is generated; as well as The second 3D model displays the 3D model of the part of the user's body that is being tried on.

10. A method comprising: A virtual scanning pad is generated by a mobile device, the virtual scanning pad including an augmented reality representation of markers configured to guide image scanning; The mobile device provides a display screen including the virtual scanning pad, which includes digitally overlaid markers to guide the user to stand properly for accurate scanning of a part of the user's body without referencing a physical pad or marker surface; When the part of the user's body is within the mark on the virtual scanning pad, the mobile device acquires an image of the part of the user's body; The mobile device generates a 3D model of the user's body portion based on the processed image, wherein the 3D model includes user body measurement data calculated based on the image; At least one product recommendation is generated using a machine learning model, based at least on the user's body measurement data. The mobile device displays the at least one product recommendation; and In response to receiving user feedback related to the at least one product recommendation, the machine learning model is retrained using the user feedback.

11. The method according to claim 10, wherein, Generating the at least one product recommendation also includes identifying product purchases or recommendations from other users who share one or more profile attributes with the user.

12. The method according to claim 10, wherein, The user's body measurement data includes the length, width, and depth of the portion of the user's body.

13. The method according to claim 10, wherein, The at least one product recommendation is tried on onto the 3D model of the part of the user's body.

14. The method of claim 10, wherein, The machine learning model is configured to generate the at least one product recommendation based at least on user shopping history data, user preference data, and at least one measurement of a part of the user's body.

15. The method according to claim 10, wherein, The at least one product recommendation is a personalized product based on a combination of the 3D model of a part of the user's body and the user's preferences.

16. The method of claim 10, further comprising: Obtain at least one additional image of a part of the user's body; as well as The 3D model is improved based on the at least one additional image.

17. The method of claim 10, further comprising: Based on authorization received from the user, the at least one product recommendation is sent at the point of sale to a computing device associated with the user, wherein the computing device allows the user to modify the at least one product recommendation for that user; and The at least one product recommendation is displayed on the 3D model of a part of the user's body on the computing device.

18. The method of claim 10, further comprising: Obtain scanned product data, wherein the scanned product data is obtained based on tags associated with the product; Based on the user's body measurement data, the recommended size of the product is determined; and The product is displayed as a try-on on the 3D model, along with the recommended size for the product.

19. The method of claim 10, further comprising: A guide interface is displayed on the mobile device to guide the user to calibrate the mobile device with the background environment, wherein calibrating the mobile device includes instructing the movement of the mobile device until it is determined that a successful scan has been completed, and displaying a first indication on the guide interface indicating that the mobile device has successfully scanned the background environment; When calibrating the mobile device using the background environment, a second indication that the mobile device has been calibrated is provided to the mobile device; and In response to user input recognizing the user's selected location, selectable interface elements are presented to generate a virtual scanning pad. The virtual scanning pad is generated when a user interaction with the selectable interface element is received.

20. A shopping assistant system, comprising: processor; and Registers that communicate with the processor and store instructions, which, when read by the processor, enable the shopping assistant system to: A guide interface is displayed on the user device to guide the user in calibrating the user device using the background environment; When calibrating the user equipment using the background environment, a graphical user interface is provided to the user equipment to generate a virtual scanning pad; Upon receiving a click on a digital image of a reference object in the graphical user interface, the virtual scanning pad is generated using the user device; When a part of the user's body is within the virtual scanning pad, an image of that part of the user's body is acquired from the user device; Generate a 3D model of the user's body portion based on the image; and At least one product recommendation is generated and displayed based on the 3D model.

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