Google Patentsopen access

Identifying augmented reality visuals influencing user behavior in virtual- … — Adobe Inc. (US10950060B2)

ABSTRACT

Abstract

Certain embodiments involve enhancing personalization of a virtual-commerce environment by identifying an augmented-reality visual of the virtual-commerce environment. For example, a system obtains a data set that indicates a plurality of augmented-reality visuals generated in a virtual-commerce environment and provided for view by a user. The system obtains data indicating a triggering user input that corresponds to a predetermined user input provideable by the user as the user views an augmented-reality visual of the plurality of augmented-reality visuals. The system obtains data indicating a user input provided by the user. The system compares the user input to the triggering user input to determine a correspondence (e.g., a similarity) between the user input and the triggering user input. The system identifies a particular augmented-reality visual of the plurality of augmented-reality visuals that is viewed by the user based on the correspondence and stores the identified augmented-reality visual.

Description

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation application of U.S. patent application Ser. No. 16/189,638, filed Nov. 13, 2018, allowed, which is a continuation application of and claims priority to U.S. patent application Ser. No. 15/433,834, filed on Feb. 15, 2017, now issued as U.S. Pat. No. 10,163,269 the contents of which are incorporated herein by reference in their entireties.

TECHNICAL FIELD

This disclosure generally relates to virtual commerce and more specifically relates to identifying or determining one or more augmented reality visuals that influence user behavior in virtual commerce environments to personalize the virtual commerce environment to a user (e.g., via recommendations of various actions).

BACKGROUND

Augmented reality (“AR”) devices provide an augmented reality environment in which physical objects or “real world” objects are concurrently displayed with virtual objects in a virtual space. To provide the AR environment, some AR devices recognize one or more physical objects in a physical space using various image recognition methods and techniques. For example, AR devices capture images of the physical objects or the physical space and transmit the images of the physical objects or physical space to a server that performs the image recognition operations. The AR device generates and displays an AR environment that includes the recognized physical objects and the physical space. The AR device then generates one or more virtual objects and supplements or augments the physical object and physical space with the virtual objects by displaying the virtual objects, along with the physical objects. Other AR devices provide the AR environment by recognizing specific codes disposed on a physical object and displaying one or more virtual objects, along with the physical object “augmented” with the virtual object. A user of the AR device views the AR environment and provides user input to interact with, or manipulate, the virtual object or the physical object in the AR environment. As the AR device generates and provides the AR environment and as the user interacts with the AR environment, the AR device generates and provides various AR visuals (e.g., images or frames) to the user.

In virtual commerce (“v-commerce”) systems, an AR device provides an AR or v-commerce environment in which virtual objects correspond to “real world” physical objects that are available for sale and the virtual objects are used to “augment” a physical space or a physical object. The v-commerce system allows users to interact with the virtual objects, the physical objects, and the physical space as the user engages in commerce (e.g., as the user decides whether to purchase a real world physical object that corresponds to a virtual object).

Existing v-commerce systems and applications have limitations as they do not capture or track data indicating the various AR visuals generated and provided to a user in an AR or v-commerce environment and data indicating user behavior with regard to each AR visual. Thus, some existing v-commerce systems and applications do not identify AR visuals that influence or impact user behavior, which are useful and beneficial to enhance the v-commerce experience.

SUMMARY

Various embodiments of the present disclosure provide systems and methods for determining a correlation between augmented reality visuals (e.g., images or frames) and user behavior in a virtual-commerce environment. For example, various embodiments of the present disclosure provide systems and methods for determining augmented reality visuals that cause, or influence, user behavior in virtual-commerce environments, which can be used to improve personalization of an augmented reality environments for users.

In one example, a method for enhancing personalization of a virtual-commerce environment by identifying an augmented reality visual of the virtual-commerce environment includes obtaining, by a processor, data indicating a plurality of augmented-reality visuals generated in a virtual-commerce environment and provided for view by a user. The method further includes obtaining, by the processor, data indicating a triggering user input. The triggering user input indicates a predetermined user input provideable by the user as the user views an augmented-reality visual of the plurality of augmented-reality visuals and detectable by the processor. The method further includes obtaining, by the processor, data indicating a user input provided by a user. The method further includes determining, by the processor, a correspondence between the user input and the triggering user input based on a comparison of the data indicating the user input and the data indicating the triggering user input. The correspondence indicates a similarity between the triggering user input and the user input. The method further includes identifying, by the processor, a particular augmented-reality visual of the plurality of augmented-reality visuals that is viewed by the user based on the correspondence and storing the identified augmented-reality visual.

Additional features and advantages of exemplary embodiments of the present disclosure will be set forth in the description which follows, and in part will be obvious from the description, or will be learned by the practice of such exemplary embodiments. The foregoing summary is not an extensive overview, and it is not intended to identify key elements or indicate a scope. Rather the foregoing summary identifies aspects of embodiments as a prelude to the detailed description presented below.

BRIEF DESCRIPTION OF THE DRAWINGS

Features, embodiments, and advantages of the present disclosure are better understood when the following Detailed Description is read with reference to the accompanying drawings.

FIG. 1 is an example of a computing environment in which an augmented-reality visual identification system identifies an augmented-reality visual that influences user behavior in a virtual commerce environment, according to certain embodiments.

FIG. 2 is a flow chart depicting an example of a process for identifying an augmented-reality visual that influences user behavior in a virtual commerce environment, according to certain embodiments.

FIG. 3 is an example of an augmented-reality visual that simulates a virtual commerce environment, according to certain embodiments.

FIG. 4 is another example of an augmented-reality visual that simulates the virtual commerce environment of FIG. 3 , according to certain embodiments.

FIG. 5 is a flow chart depicting an example of a process for identifying an augmented-reality visual based on an epoch time, according to certain embodiments.

FIG. 6 is an example of a block diagram of a computing device that executes an augmented-reality visual identification system to identify augmented-reality visuals that influences user behavior in a virtual commerce environment, according to certain embodiments.

DETAILED DESCRIPTION

Various embodiments of the present disclosure involve determining a correlation or relationship between augmented-reality (“AR”) visuals (e.g., images or frames) provided to a user in a virtual commerce (“v-commerce”) environment and user behavior in the v-commerce environment by analyzing the AR visuals and user input in the v-commerce environment. For example, various embodiments of the present disclosure involve detecting or identifying one or more AR visuals that cause, or influence, a particular user behavior in a v-commerce environment. As described above, some existing v-commerce systems do not capture or track data indicating the various AR visuals generated and provided to the user in an AR or v-commerce environment. Moreover, some existing v-commerce applications do not account for an effect that a particular AR visual has on a user's behavior in the v-commerce environment or may not account for user behavior before or after viewing a particular AR visual. Certain embodiments address these issues by identifying or detecting one or more AR visuals that influence a user's behavior in a v-commerce environment (e.g., influence the user's decision to make a purchase) based on data indicating various AR visuals provided to the user in the v-commerce environment, which improves the recommendation of various actions to the user. For example, in some embodiments, identifying AR visuals that influence user behavior in v-commerce environments provides users with content with which the user is more likely to engage (e.g., by increasing a likelihood of a user interacting with a virtual object or making a purchase by providing or recommending visuals that are likely to influence user behavior).

In one example, an AR device simulates a v-commerce environment by recognizing a physical object in a physical space and displaying an AR environment that includes the recognized physical object and the physical space. The AR device supplements or augments the physical object or space by generating a virtual object and concurrently displaying the virtual object, along with the physical object or space in the AR environment. As an example, if the virtual object is a virtual chair, the virtual chair is used to supplement or augment a physical room in the AR environment. In the v-commerce environment, a virtual object in the AR environment corresponds to a real world physical object that may be available for sale. In this example, the AR device detects user input provided by the user as the user interacts with the v-commerce environment, such as, for example, user input indicating a change in location or orientation of a virtual object in the v-commerce environment, user input indicating a request for information about a real world physical object represented by a virtual object in the v-commerce environment (e.g., to request information about a price or availability of the real world physical object), or user input to purchase the real world physical object. The AR device also analyzes and stores the detected user input. In this example, the AR device generates and outputs one or more AR visuals that include, for example, one or more of the physical space, the physical object, and the virtual objects, in response to the detected user input.

An AR visual identification system, which includes one or more computing devices, obtains data about the v-commerce environment. The data indicates various AR visuals generated and provided to the user in the v-commerce environment. The data also includes data indicating one or more triggering user inputs. A triggering user input includes, for example, a predetermined or a particular user input that may be provided by the user while viewing, or interacting with, the v-commerce environment. As an illustrative example, the data indicates that a triggering user input is any user input indicating a request for information about a real world physical object represented by a virtual object in the v-commerce environment. As another example, the data indicates that a triggering user input is any user input provided by the user to purchase the real world physical object represented by the virtual object. The AR visual identification system also obtains data indicating one or more user inputs provided by the user of the AR device. In some embodiments, the AR visual identification system detects the various user inputs provided by the user of the AR device. The AR visual identification system then determines or identifies one or more AR visuals of the various AR visuals based on the data received. For example, the AR visual identification system analyzes the data indicating user input and data indicating a triggering user input and identifies an AR visual if the user provides user input that corresponds to the triggering user input (e.g., provides user input that is similar to the triggering user input). As an illustrative example, the AR visual identification system detects user input and determines that the user input corresponds to the triggering user input and identifies one or more AR visuals viewed by the user at or near a time that the user provides the user input corresponding to the triggering user input. For example, the AR visual identification system identifies the AR image viewed by the user as the user provides user input requesting information about a real world physical object represented by a virtual object in the v-commerce environment.

In some embodiments, the identified AR visual is the AR visual viewed by the user that affects the user's behavior in the v-commerce environment. For example, the identified AR visual is the AR visual that influenced the user, or caused the user, to provide the triggering user input (e.g., to provide user input requesting information about the real world physical object represented by the virtual object or to purchase the real world physical object). Thus, in some embodiments, the AR visual identification system stores data indicating the identified AR visual and the identified AR visual is used to improve recommendation of various actions to the user (e.g., to recommend, to the user, various additional virtual objects representing real world physical objects available for sale based on the physical space, the physical objects, or the virtual objects in the identified AR visual).

In some embodiments, the AR visual identification system identifies an AR visual that influences user behavior in a v-commerce environment regardless of whether the user provides user input that corresponds to a triggering user input. For example, the user may not provide user input as the user views the v-commerce environment, or the user may not provide user input that corresponds to a triggering user input. In these embodiments, the AR visual identification system selects an AR visual of various AR visuals provided to the user based on an epoch time (e.g., a particular or calculated time) after the user begins to view the v-commerce environment by selecting the AR visual viewed by the user at, or near, the epoch time. For example, the AR visual selects an AR visual that is provided to the user at the epoch time. In some examples, the epoch time corresponds to a time after the user begins to view the v-commerce environment at which the user is likely to provide a user input that corresponds to a predefined triggering user input. For example, the AR visual identification system obtains data indicating a time stamp corresponding to a time that each of the various AR visuals is provided to the user. The AR visual identification system determines or calculates the epoch time or receives data indicating the epoch time. The AR visual identification system then determines or identifies an AR visual that is provided to the user or viewed by the user at or near the epoch time. As an example, the identified AR visual is the AR visual viewed by the user at the epoch time or immediately before the epoch time. In certain embodiments, the AR visual identification system trains a machine-learning algorithm to calculate or predict the epoch time using various methods and techniques. For example, the AR visual identification system trains the machine-learning algorithm to predict the epoch time based on data indicating various users' interaction with one or more v-commerce environments generated by the AR device. As an example, the AR visual identification system trains the machine-learning algorithm to determine a probability distribution of a particular epoch time (e.g., a probability distribution of a user providing user input corresponding to a triggering user input at or near a particular epoch time). The AR visual identification system then uses the determined probability distribution to predict the epoch time. For example, based on the probability distribution, the machine learning algorithm predicts a particular epoch time after a user begins to view a v-commerce environment at which the user is likely to provide user input that corresponds to a triggering user input. In this example, the AR visual identification system trains the machine-learning algorithm to predict or calculate the epoch time and identifies an AR visual among a plurality of AR visuals based on the epoch time as described above.

In some examples, a user accesses the AR visual identification system described above via an online service. For example, the online service includes one or more computing systems

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation application of U.S. patent application Ser. No. 16/189,638, filed Nov. 13, 2018, allowed, which is a continuation application of and claims priority to U.S. patent application Ser. No. 15/433,834, filed on Feb. 15, 2017, now issued as U.S. Pat. No. 10,163,269 the contents of which are incorporated herein by reference in their entireties.

TECHNICAL FIELD

This disclosure generally relates to virtual commerce and more specifically relates to identifying or determining one or more augmented reality visuals that influence user behavior in virtual commerce environments to personalize the virtual commerce environment to a user (e.g., via recommendations of various actions).

BACKGROUND

Augmented reality (“AR”) devices provide an augmented reality environment in which physical objects or “real world” objects are concurrently displayed with virtual objects in a virtual space. To provide the AR environment, some AR devices recognize one or more physical objects in a physical space using various image recognition methods and techniques. For example, AR devices capture images of the physical objects or the physical space and transmit the images of the physical objects or physical space to a server that performs the image recognition operations. The AR device generates and displays an AR environment that includes the recognized physical objects and the physical space. The AR device then generates one or more virtual objects and supplements or augments the physical object and physical space with the virtual objects by displaying the virtual objects, along with the physical objects. Other AR devices provide the AR environment by recognizing specific codes disposed on a physical object and displaying one or more virtual objects, along with the physical object “augmented” with the virtual object. A user of the AR device views the AR environment and provides user input to interact with, or manipulate, the virtual object or the physical object in the AR environment. As the AR device generates and provides the AR environment and as the user interacts with the AR environment, the AR device generates and provides various AR visuals (e.g., images or frames) to the user.

In virtual commerce (“v-commerce”) systems, an AR device provides an AR or v-commerce environment in which virtual objects correspond to “real world” physical objects that are available for sale and the virtual objects are used to “augment” a physical space or a physical object. The v-commerce system allows users to interact with the virtual objects, the physical objects, and the physical space as the user engages in commerce (e.g., as the user decides whether to purchase a real world physical object that corresponds to a virtual object).

Existing v-commerce systems and applications have limitations as they do not capture or track data indicating the various AR visuals generated and provided to a user in an AR or v-commerce environment and data indicating user behavior with regard to each AR visual. Thus, some existing v-commerce systems and applications do not identify AR visuals that influence or impact user behavior, which are useful and beneficial to enhance the v-commerce experience.

SUMMARY

Various embodiments of the present disclosure provide systems and methods for determining a correlation between augmented reality visuals (e.g., images or frames) and user behavior in a virtual-commerce environment. For example, various embodiments of the present disclosure provide systems and methods for determining augmented reality visuals that cause, or influence, user behavior in virtual-commerce environments, which can be used to improve personalization of an augmented reality environments for users.

In one example, a method for enhancing personalization of a virtual-commerce environment by identifying an augmented reality visual of the virtual-commerce environment includes obtaining, by a processor, data indicating a plurality of augmented-reality visuals generated in a virtual-commerce environment and provided for view by a user. The method further includes obtaining, by the processor, data indicating a triggering user input. The triggering user input indicates a predetermined user input provideable by the user as the user views an augmented-reality visual of the plurality of augmented-reality visuals and detectable by the processor. The method further includes obtaining, by the processor, data indicating a user input provided by a user. The method further includes determining, by the processor, a correspondence between the user input and the triggering user input based on a comparison of the data indicating the user input and the data indicating the triggering user input. The correspondence indicates a similarity between the triggering user input and the user input. The method further includes identifying, by the processor, a particular augmented-reality visual of the plurality of augmented-reality visuals that is viewed by the user based on the correspondence and storing the identified augmented-reality visual.

Additional features and advantages of exemplary embodiments of the present disclosure will be set forth in the description which follows, and in part will be obvious from the description, or will be learned by the practice of such exemplary embodiments. The foregoing summary is not an extensive overview, and it is not intended to identify key elements or indicate a scope. Rather the foregoing summary identifies aspects of embodiments as a prelude to the detailed description presented below.

BRIEF DESCRIPTION OF THE DRAWINGS

Features, embodiments, and advantages of the present disclosure are better understood when the following Detailed Description is read with reference to the accompanying drawings.

FIG. 1 is an example of a computing environment in which an augmented-reality visual identification system identifies an augmented-reality visual that influences user behavior in a virtual commerce environment, according to certain embodiments.

FIG. 2 is a flow chart depicting an example of a process for identifying an augmented-reality visual that influences user behavior in a virtual commerce environment, according to certain embodiments.

FIG. 3 is an example of an augmented-reality visual that simulates a virtual commerce environment, according to certain embodiments.

FIG. 4 is another example of an augmented-reality visual that simulates the virtual commerce environment of FIG. 3 , according to certain embodiments.

FIG. 5 is a flow chart depicting an example of a process for identifying an augmented-reality visual based on an epoch time, according to certain embodiments.

FIG. 6 is an example of a block diagram of a computing device that executes an augmented-reality visual identification system to identify augmented-reality visuals that influences user behavior in a virtual commerce environment, according to certain embodiments.

DETAILED DESCRIPTION

Various embodiments of the present disclosure involve determining a correlation or relationship between augmented-reality (“AR”) visuals (e.g., images or frames) provided to a user in a virtual commerce (“v-commerce”) environment and user behavior in the v-commerce environment by analyzing the AR visuals and user input in the v-commerce environment. For example, various embodiments of the present disclosure involve detecting or identifying one or more AR visuals that cause, or influence, a particular user behavior in a v-commerce environment. As described above, some existing v-commerce systems do not capture or track data indicating the various AR visuals generated and provided to the user in an AR or v-commerce environment. Moreover, some existing v-commerce applications do not account for an effect that a particular AR visual has on a user's behavior in the v-commerce environment or may not account for user behavior before or after viewing a particular AR visual. Certain embodiments address these issues by identifying or detecting one or more AR visuals that influence a user's behavior in a v-commerce environment (e.g., influence the user's decision to make a purchase) based on data indicating various AR visuals provided to the user in the v-commerce environment, which improves the recommendation of various actions to the user. For example, in some embodiments, identifying AR visuals that influence user behavior in v-commerce environments provides users with content with which the user is more likely to engage (e.g., by increasing a likelihood of a user interacting with a virtual object or making a purchase by providing or recommending visuals that are likely to influence user behavior).

In one example, an AR device simulates a v-commerce environment by recognizing a physical object in a physical space and displaying an AR environment that includes the recognized physical object and the physical space. The AR device supplements or augments the physical object or space by generating a virtual object and concurrently displaying the virtual object, along with the physical object or space in the AR environment. As an example, if the virtual object is a virtual chair, the virtual chair is used to supplement or augment a physical room in the AR environment. In the v-commerce environment, a virtual object in the AR environment corresponds to a real world physical object that may be available for sale. In this example, the AR device detects user input provided by the user as the user interacts with the v-commerce environment, such as, for example, user input indicating a change in location or orientation of a virtual object in the v-commerce environment, user input indicating a request for information about a real world physical object represented by a virtual object in the v-commerce environment (e.g., to request information about a price or availability of the real world physical object), or user input to purchase the real world physical object. The AR device also analyzes and stores the detected user input. In this example, the AR device generates and outputs one or more AR visuals that include, for example, one or more of the physical space, the physical object, and the virtual objects, in response to the detected user input.

An AR visual identification system, which includes one or more computing devices, obtains data about the v-commerce environment. The data indicates various AR visuals generated and provided to the user in the v-commerce environment. The data also includes data indicating one or more triggering user inputs. A triggering user input includes, for example, a predetermined or a particular user input that may be provided by the user while viewing, or interacting with, the v-commerce environment. As an illustrative example, the data indicates that a triggering user input is any user input indicating a request for information about a real world physical object represented by a virtual object in the v-commerce environment. As another example, the data indicates that a triggering user input is any user input provided by the user to purchase the real world physical object represented by the virtual object. The AR visual identification system also obtains data indicating one or more user inputs provided by the user of the AR device. In some embodiments, the AR visual identification system detects the various user inputs provided by the user of the AR device. The AR visual identification system then determines or identifies one or more AR visuals of the various AR visuals based on the data received. For example, the AR visual identification system analyzes the data indicating user input and data indicating a triggering user input and identifies an AR visual if the user provides user input that corresponds to the triggering user input (e.g., provides user input that is similar to the triggering user input). As an illustrative example, the AR visual identification system detects user input and determines that the user input corresponds to the triggering user input and identifies one or more AR visuals viewed by the user at or near a time that the user provides the user input corresponding to the triggering user input. For example, the AR visual identification system identifies the AR image viewed by the user as the user provides user input requesting information about a real world physical object represented by a virtual object in the v-commerce environment.

In some embodiments, the identified AR visual is the AR visual viewed by the user that affects the user's behavior in the v-commerce environment. For example, the identified AR visual is the AR visual that influenced the user, or caused the user, to provide the triggering user input (e.g., to provide user input requesting information about the real world physical object represented by the virtual object or to purchase the real world physical object). Thus, in some embodiments, the AR visual identification system stores data indicating the identified AR visual and the identified AR visual is used to improve recommendation of various actions to the user (e.g., to recommend, to the user, various additional virtual objects representing real world physical objects available for sale based on the physical space, the physical objects, or the virtual objects in the identified AR visual).

In some embodiments, the AR visual identification system identifies an AR visual that influences user behavior in a v-commerce environment regardless of whether the user provides user input that corresponds to a triggering user input. For example, the user may not provide user input as the user views the v-commerce environment, or the user may not provide user input that corresponds to a triggering user input. In these embodiments, the AR visual identification system selects an AR visual of various AR visuals provided to the user based on an epoch time (e.g., a particular or calculated time) after the user begins to view the v-commerce environment by selecting the AR visual viewed by the user at, or near, the epoch time. For example, the AR visual selects an AR visual that is provided to the user at the epoch time. In some examples, the epoch time corresponds to a time after the user begins to view the v-commerce environment at which the user is likely to provide a user input that corresponds to a predefined triggering user input. For example, the AR visual identification system obtains data indicating a time stamp corresponding to a time that each of the various AR visuals is provided to the user. The AR visual identification system determines or calculates the epoch time or receives data indicating the epoch time. The AR visual identification system then determines or identifies an AR visual that is provided to the user or viewed by the user at or near the epoch time. As an example, the identified AR visual is the AR visual viewed by the user at the epoch time or immediately before the epoch time. In certain embodiments, the AR visual identification system trains a machine-learning algorithm to calculate or predict the epoch time using various methods and techniques. For example, the AR visual identification system trains the machine-learning algorithm to predict the epoch time based on data indicating various users' interaction with one or more v-commerce environments generated by the AR device. As an example, the AR visual identification system trains the machine-learning algorithm to determine a probability distribution of a particular epoch time (e.g., a probability distribution of a user providing user input corresponding to a triggering user input at or near a particular epoch time). The AR visual identification system then uses the determined probability distribution to predict the epoch time. For example, based on the probability distribution, the machine learning algorithm predicts a particular epoch time after a user begins to view a v-commerce environment at which the user is likely to provide user input that corresponds to a triggering user input. In this example, the AR visual identification system trains the machine-learning algorithm to predict or calculate the epoch time and identifies an AR visual among a plurality of AR visuals based on the epoch time as described above.

In some examples, a user accesses the AR visual identification system described above via an online service. For example, the online service includes one or more computing systems configured by program code to implement the operations describe above (e.g., implement the operations performed by the AR visual identification system) and the user accesses the online service using a client device (e.g., a mobile telephone) via a data network.

As used herein, the term “augmented reality device” is used to refer to any device configured to generate or display an augmented reality environment, simulate an augmented reality environment, or generate an augmented reality visual.

As used herein, the term “augmented reality” or “augmented reality environment” is used to refer to an environment in which physical objects in a physical space are concurrently displayed with virtual objects in a virtual space.

As used herein, the term “virtual commerce,” “v-commerce,” or “virtual commerce environment” is used to refer to an augmented reality environment in which one or more virtual objects in the augmented reality environment represent real world physical objects that may be available for purchase by a consumer.

As used herein, the term “augmented reality visual” or “augmented reality image” is used to refer to any image, frame, or content generated or provided to a user as part of an augmented reality environment or as part of a virtual commerce environment.

As used herein, the term “epoch time” is used to refer to a particular or predetermined time during which an augmented reality visual or an augmented reality image is provided to a user of an augmented reality device or viewed by the user.

As used herein, the term “online service” is used to refer to one or more computing resources, including computing systems that may be configured for distributed processing operations, that provide one or more applications accessible via a data network. The collection of computing resources may be represented as a single service. In some embodiments, an online service provides a digital hub for browsing, creating, sharing, and otherwise using electronic content using one or more applications provided via the online service.

FIG. 1 is an example of a computing environment 100 in which an augmented-reality (“AR”) visual identification system 102 identifies an AR visual that influences user behavior in a virtual commerce environment, according to certain embodiments. The computing environment 100 includes the augmented-reality visual identification system 102 (which may be included in or otherwise used by a marketing apparatus), one or more computing devices 104 , and one or more online services 106 . The augmented-reality visual identification system 102 , computing devices 104 , and online services 106 are communicatively coupled via one or more data networks 108 (e.g., the Internet one or more local area networks (“LAN”), wired area networks, one or more wide area networks, or some combination thereof).

Each of the computing devices 104 is connected (or otherwise communicatively coupled) to a marketing apparatus 110 via the data network 108 . A user of one of the computing devices 104 uses various products, applications, or services supported by the marketing apparatus 110 via the data network 108 . Examples of the users include, but are not limited to, marketing professionals who use digital tools to generate, edit, track, or manage online content, or to manage online marketing processes, end users, administrators, users who use document tools to create, edit, track, or manage documents, advertisers, publishers, developers, content owners, content managers, content creators, content viewers, content consumers, designers, editors, any combination of these users, or any other user who uses digital tools to create, edit, track, or manage digital experiences.

Digital tools, as described herein, include a tool that is used for performing a function or a workflow electronically. Examples of the digital tool include, but are not limited to, content creation tool, content editing tool, content publishing tool, content tracking tool, content managing tool, content printing tool, content consumption tool, any combination of these tools, or any other tool that may be used for creating, editing, managing, generating, tracking, consuming or performing any other function or workflow related to content. Digital tools include the augmented-reality visual identification system 102 .

Digital experience, as described herein, includes experience that may be consumed through an electronic device. Examples of the digital experience include, but are not limited to, content creating, content editing, content tracking, content publishing, content posting, content printing, content managing, content viewing, content consuming, any combination of these experiences, or any other workflow or function that may be performed related to content.

Content, as described herein, includes electronic content. Examples of the content include, but are not limited to, image, video, web site, webpage, user interface, menu item, tool menu, magazine, slideshow, animation, social post, comment, blog, data feed, audio, advertisement, vector graphic, bitmap, document, any combination of one or more content, or any other electronic content.

The augmented-reality visual identification system 102 includes one or more devices that provide and execute one or more engines for providing one or more digital experiences to a user. In some examples, the augmented-reality visual identification system 102 is implemented using one or more servers, one or more platforms with corresponding application programming interfaces, cloud infrastructure and the like. In addition, in some examples, each engine is implemented using one or more servers, one or more platforms with corresponding application programming interfaces, cloud infrastructure and the like.

The augmented-reality visual identification system 102 also includes a data storage unit 112 . In some examples, the data storage unit 112 is be implemented as one or more databases or one or more data servers. The data storage unit 112 includes data that may be used by the engines of the augmented-reality visual identification system 102 .

In some embodiments, the augmented-reality visual identification system 102 is divided into two layers of engines. For example, Layer 1 includes core engines that provide workflows to the user and Layer 2 includes shared engines that are shared among the core engines. In some embodiments, any core engine calls any of the shared engines for execution of a corresponding task. In additional or alternative embodiments, the augmented-reality visual identification system 102 does not have layers, and each core engine has an instance of the shared engines. In various embodiments, each core engine accesses the data storage unit 112 directly or through the shared engines.

In some embodiments, the user of the computing device 104 visits a webpage or an application store to explore applications supported by the augmented-reality visual identification system 102 . The augmented-reality visual identification system 102 provides the applications as a software as a service (“SaaS”), or as a standalone application that may be installed on one or more of the computing devices 104 , or as a combination.

In some embodiments, the user creates an account with the augmented-reality visual identification system 102 by providing user details and also by creating login details. In additional or alternative embodiments, the augmented-reality visual identification system 102 automatically creates login details for the user in response to receipt of the user details. The user may also contact the entity offering the services of the augmented-reality visual identification system 102 and get the account created through the entity. The user details are received by a subscription engine 114 and stored as user data 116 in the data storage unit 112 . In some embodiments, the user data 116 further includes account data 118 , under which the user details are stored. In some embodiments, the user is also prompted to install an application manager. The application manager enables the user to manage installation of various applications supported by the augmented-reality visual identification system 102 .

In some embodiments, a user may opt for a trial or a subscription to one or more engines of the augmented-reality visual identification system 102 . Based on the trial account or the subscription details of the user, a user subscription profile 120 is generated by the subscription engine 114 and stored. The user subscription profile 120 is stored in the data storage unit 112 and indicates entitlement of the user to various products or services. The user subscription profile 120 also indicates a type of subscription, e.g., a free trial, a premium subscription, or a regular subscription.

Each engine of the augmented-reality visual identification system 102 also stores customer data 122 for the user in the data storage unit 112 . In some examples, the user or the entity of the user has one or more customers, including potential customers, and hence, the one or more engines of the augmented-reality visual identification system 102 store the customer data 122 . In some examples, the customer data 122 is shared across these engines or is specific to each engine. In some embodiments, access data 124 is a part of the customer data 122 . The access to the customer data 122 is controlled by an access control engine 126 , which may be shared across the engines of the augmented-reality visual identification system 102 or each engine has one instance of the access control engine 126 . The access control engine 126 determines if the user has access to a particular customer data 122 based on the subscription of the user and access rights of the user.

In some examples, a user of the augmented-reality visual identification system 102 enables tracking of content while viewing content, while creating content, or at any point. Various methods of tracking may be used. For example, tracking code is embedded into the content for tracking and sending tracked data to an augmented- reality engine 128 . The augmented- reality engine 128 tracks the data and stores the tracked data as augmented reality data 130 or other data. The augmented- reality engine 128 tracks the data and performs meaningful processing of the augmented reality data 130 or other data to provide various reports to the user. In addition, in some embodiments, the augmented- reality engine 128 also acts as a shared engine and is accessible by other engines to obtain meaningful analysis on the basis of which other engines may offer various functionalities to the user. In additional or alternative embodiments, each engine can have an instance of the augmented- reality engine 128 , which is customized according to a need of that engine. In various embodiments, the augmented- reality engine 128 is used for tracking one or more types of content, such as mobile applications, video, image, animation, website, document, advertisements, etc. In some embodiments, the augmented- reality engine 128 also supports predictive intelligence to provide predictions based on the augmented reality data 130 or other data. In some embodiments, the augmented- reality engine 128 also stitches information tracked from various sources where the content is consumed and provides a holistic view (e.g., a 360 degree view) of the augmented reality data 130 or other user data.

In some embodiments, the augmented-reality visual identification system 102 also includes a content personalization engine 132 . The content personalization engine 132 enables the user to provide different digital experiences to the customers when different customers visit a same webpage or a same application of the user. The content personalization engine 132 provides various workflows to the user to create different versions of the webpage or application or the content and to perform A/B testing. Based on the testing, the user may choose to provide different personalization for different sets of customers. The content personalization engine 132 also uses the customer data 122 . The customer data 122 includes customer profiles. The customers, as described herein, also include mere visitors that are not customers yet. A customer profile includes one or more attributes of the customer. An attribute, as described herein, is a concept using which the customer can be segmented. Examples of the attribute include, but are not limited to, geographic location, age, gender, purchase capacity, language, habits, browsing trends, or any other attribute using which the customers can be segmented.

The customer data 122 , at least some of which may be included in the augmented reality data 130 or stored separately from the augmented reality data 130 , is generated by a customer segmentation engine 134 by collecting data from different sources including electronic sources, such as, for example, the augmented- reality engine 128 , online forms, customer submitting data online, and other online sources, and non-electronic sources including, for example, paper forms and other offline sources. In some examples, customer data 122 is shared between users and some of the customer data 122 is specific to each user and not accessible by other users. The customer segments are used by the customer segmentation engine 134 to personalize content and show relevant content to the customers. In addition, the content personalization engine 132 provides automated workflows to enable the personalization including providing recommendations for the content that should be shown to a particular customer segment.

In some embodiments, the augmented-reality visual identification system 102 includes the augmented- reality engine 128 , an identification engine 140 , and a machine-learning algorithm engine 142 .

The

engines

128 , 140 , 142 each include one or more instructions stored on a computer-readable storage medium and executable by processors of one or more computing devices. When executed by the one or more processors, the computer-executable instructions of the augmented-reality visual identification system 102 cause the augmented-reality visual identification system 102 to identify augmented-reality visuals that influences user behavior in a virtual commerce environment. In additional or alternative embodiments, the

engines

128 , 140 , 142 include hardware, such as a special purpose processing device to perform a certain function or group of functions. Additionally or alternatively, the

engines

128 , 140 , 142 each include a combination of computer-executable instructions and hardware.

In the example depicted in FIG. 1 , one or

more engines

128 , 140 , 142 of the augmented-reality visual identification system 102 and the data storage unit 112 communicate via the data network 108 .

In some embodiments, the augmented- reality engine 128 or the content personalization engine 132 is configured to provide content (e.g., texts, images, sounds, videos, animations, documents, user interfaces, etc.) to a user (e.g., to a user of the augmented-reality visual identification system 102 or a user of the computing device 104 ). As an example, the augmented- reality engine 128 provides an image in any format to the user. If the content includes computer generated images, the augmented- reality engine 128 generates the images and display the images on a display device associated with the augmented-reality visual identification system 102 or the computing device 104 . If the content includes video or still images, the augmented- reality engine 128 generates views of the video or still images for display on the display device. In some embodiments, the augmented- reality engine 128 accesses or obtains the video or still images (e.g., from one or more databases or data sources) and generate views of the video or still images for display on the display device. If the content includes audio content the augmented- reality engine 128 generates electronic signals that will drive a speaker, which may be a part of the display device, to output corresponding sounds. In some embodiments, the content, or the information or data from which the content is derived, may be obtained by the augmented- reality engine 128 from the data storage unit 112 , which may be part of the augmented-reality visual identification system 102 , as illustrated in FIG. 1 , or may be separate from the augmented-reality visual identification system 102 and communicatively coupled to the augmented-reality visual identification system 102 . In some embodiments, the augmented- reality engine 128 generates or accesses content and transmits the content to a display device (e.g., a display device associated with the augmented-reality visual identification system 102 or the computing device 104 ).

For example, the augmented- reality engine 128 includes one or more AR devices and the augmented- reality engine 128 generates an AR environment for display on a display device. The AR environment includes an environment that is at least partially virtual. As an illustrative example, the augmented- reality engine 128 recognizes one or more physical objects in a physical space using various image recognition methods and techniques, such as, for example, by capturing images of the physical objects or the physical space and transmitting the images of the physical objects to a server that performs the image recognition operations or by recognizing specific codes disposed on a physical object. The augmented- reality engine 128 also generates virtual objects (e.g., items, icons, or other user interface components) with which a user of the augmented-reality <figure-callout id="102" label="visual identification system" filenames="US10950060-20210316-D00001.png,US10950060-20210316-D00006.png" state

CLAIMS

Claims ( 20 )

What is claimed is:

1. A method for enhancing personalization of a virtual-commerce environment by identifying augmented-reality visual content of the virtual-commerce environment, the method comprising:

obtaining, by a processor, data indicating a plurality of augmented-reality visuals generated in the virtual-commerce environment and provided for view by a user;

obtaining, by the processor, data indicating a user input provided by the user to generate manipulated augmented-reality visuals from the plurality of augmented-reality visuals;

training, by the processor, a machine-learning algorithm usable to predict an epoch time during which users are likely to provide user inputs corresponding to a triggering user input, wherein training the machine-learning algorithm is performed using covariates generated from the user input provided by the user to generate the manipulated augmented-reality visuals;

predicting, by the processor, the epoch time by applying the machine-learning algorithm to the data indicating the user input;

identifying, by the processor, a particular manipulated augmented-reality visual of the manipulated augmented-reality visuals that is viewed by the user at or nearest the epoch time; and

storing the identified manipulated augmented-reality visual.

2. The method of claim 1 , further comprising:

identifying, by the processor and in response to determining a correspondence between the user input and the triggering user input, an additional particular augmented-reality visual provided to the user at a time associated with the user input.

3. The method of claim 2 , wherein identifying the additional particular augmented-reality visual provided to the user at the time associated with the user input further comprises:

obtaining, by the processor, a time stamp associated with each of the plurality of augmented-reality visuals;

obtaining, by the processor, a time associated with the user input corresponding to the triggering user input; and

identifying, by the processor, the particular augmented-reality visual provided to the user at the time the user provides the user input corresponding to the triggering user input based on a comparison of the time stamp associated with each of the plurality of augmented-reality visuals and the time associated with the user input corresponding to the triggering user input.

4. The method of claim 1 , further comprising:

predicting the epoch time responsive to a determination of a lack of correspondence between the user input and the triggering user input.

5. The method of claim 1 , wherein the covariates comprise the data indicating the plurality of augmented-reality visuals, the data indicating the triggering user input, and the data indicating the user input.

6. The method of claim 1 , wherein the triggering user input corresponds to user input indicating a request for information associated with a virtual object in a virtual-reality visual of the plurality of augmented-reality visuals.

7. The method of claim 1 , further comprising:

identifying, by the processor, a group of augmented-reality visuals based on the user input and the triggering user input;

obtaining, by the processor, accelerometer data associated with each identified augmented-reality visual; and

identifying, by the processor, a subset of the identified group of augmented-reality visuals based on a comparison of the accelerometer data associated with each identified augmented-reality visual and a threshold accelerometer value.

8. A system comprising:

a processing device; and

a non-transitory computer-readable medium communicatively coupled to the processing device, wherein the processing device is configured to perform operations comprising:

obtaining data indicating a plurality of augmented-reality visuals generated in a virtual-commerce environment and provided for view by a user;

obtaining data indicating a user input provided by the user to generate manipulated augmented-reality visuals from the plurality of augmented-reality visuals;

training a machine-learning algorithm usable to predict an epoch time during which users are likely to provide user inputs corresponding to a triggering user input, wherein training the machine-learning algorithm is performed using covariates generated from the user input provided by the user to generate the manipulated augmented-reality visuals;

predicting, by the processing device, the epoch time by applying the machine-learning algorithm to the data indicating the user input;

identifying a particular manipulated augmented-reality visual of the manipulated augmented-reality visuals that is viewed by the user at or nearest the epoch time; and

storing the identified manipulated augmented-reality visual.

9. The system of claim 8 , wherein the processing device is further configured to perform operations comprising:

identifying, in response to determining a correspondence between the user input and the triggering user input, an additional particular augmented-reality visual provided to the user at a time associated with the user input.

10. The system of claim 9 , wherein the operations comprising identifying the additional particular augmented-reality visual provided to the user at the time associated with the user input further comprises:

obtaining a time stamp associated with each of the plurality of augmented-reality visuals;

obtaining a time associated with the user input corresponding to the triggering user input; and

identifying the particular augmented-reality visual provided to the user at the time the user provides the user input corresponding to the triggering user input based on a comparison of the time stamp associated with each of the plurality of augmented-reality visuals and the time associated with the user input corresponding to the triggering user input.

11. The system of claim 8 , wherein predicting the epoch time is performed responsive to a determination of a lack of correspondence between the user input and the triggering user input.

12. The system of claim 8 , wherein the covariates comprise the data indicating the plurality of augmented-reality visuals, the data indicating the triggering user input, and the data indicating the user input.

13. The system of claim 8 , wherein the triggering user input corresponds to user input indicating a request for information associated with a virtual object in a virtual-reality visual of the plurality of augmented-reality visuals.

14. The system of claim 8 , wherein the processing device is further configured to perform operations comprising:

identifying a group of augmented-reality visuals based on the user input and the triggering user input;

obtaining accelerometer data associated with each identified augmented-reality visual; and

identifying a subset of the identified group of augmented-reality visuals based on a comparison of accelerometer data associated with each identified augmented-reality visual and a threshold accelerometer value.

15. A non-transitory computer-readable medium storing program code executable by a processor for enhancing personalization of a virtual-commerce environment by identifying augmented-reality visual content of the virtual-commerce environment, the program code comprising:

program code for obtaining, by the processor, data indicating a plurality of augmented-reality visuals generated in the virtual-commerce environment and provided for view by a user;

program code for obtaining, by the processor, data indicating a user input provided by the user to generate manipulated augmented-reality visuals from the plurality of augmented-reality visuals;

program code for training, by the processor, a machine-learning algorithm usable to predict an epoch time during which users are likely to provide user inputs corresponding to a triggering user input, wherein training the machine-learning algorithm is performed using at least one covariate generated from the user input provided by the user to generate the manipulated augmented-reality visuals;

program code for predicting, by the processor, the epoch time by applying the machine-learning algorithm to the data indicating the user input;

program code for identifying, by the processor, a particular manipulated augmented-reality visual of the manipulated augmented-reality visuals that is viewed by the user at or nearest the epoch time; and

program code for storing, by the processor, the identified manipulated augmented-reality visual.

16. The non-transitory computer-readable medium of claim 15 , further comprising:

program code for identifying, by the processor and in response to determining a correspondence between the user input and the triggering user input, an additional particular augmented-reality visual provided to the user at a time associated with the user input.

17. The non-transitory computer-readable medium of claim 16 , wherein the program code for identifying the additional particular augmented-reality visual based on the correspondence comprises:

program code for obtaining, by the processor, a time stamp associated with each of the plurality of augmented-reality visuals;

program code for obtaining, by the processor, a time associated with the user input corresponding to the triggering user input; and

program code for identifying, by the processor, the additional particular augmented-reality visual provided to the user at the time the user provides the user input corresponding to the triggering user input based on a comparison of the time stamp associated with each of the plurality of augmented-reality visuals and the time associated with the user input corresponding to the triggering user input.

18. The non-transitory computer-readable medium of claim 15 , wherein predicting the epoch time is performed responsive to a determination of a lack of correspondence between the user input and the triggering user input.

19. The non-transitory computer-readable medium of claim 15 , wherein the covariates comprise the data indicating the plurality of augmented-reality visuals, the data indicating the triggering user input, and the data indicating the user input.

20. The non-transitory computer-readable medium of claim 15 , wherein the program code further comprises:

program code for identifying, by the processor, a group of augmented-reality visuals based on the user input and the triggering user input;

program code for obtaining, by the processor, accelerometer data associated with each identified augmented-reality visual; and

program code for identifying, by the processor, a subset of the identified group of augmented-reality visuals based on a comparison of the accelerometer data associated with each identified augmented-reality visual and a threshold accelerometer value.

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