Google Patent | Measurement Method And System

Patent: Measurement Method And System

Publication Number: 10598929

Publication Date: 20200324

Applicants: Google

Abstract

Methods and systems for determining an individual gaze value are disclosed herein. An exemplary method involves: (a) receiving gaze data for a first wearable computing device, wherein the gaze data is indicative of a wearer-view associated with the first wearable computing device, and wherein the first wearable computing device is associated with a first user-account; (b) analyzing the gaze data from the first wearable computing device to detect one or more occurrences of one or more advertisement spaces in the gaze data; (c) based at least in part on the one or more detected advertisement-space occurrences, determining an individual gaze value for the first user-account; and (d) sending a gaze-value indication, wherein the gaze-value indication indicates the individual gaze value for the first user-account.

BACKGROUND

Unless otherwise indicated herein, the materials described in this section are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section.

Computing devices such as personal computers, laptop computers, tablet computers, cellular phones, and countless types of Internet-capable devices are increasingly prevalent in numerous aspects of modern life. Over time, the manner in which these devices are providing information to users is becoming more intelligent, more efficient, more intuitive, and/or less obtrusive.

The trend toward miniaturization of computing hardware, peripherals, as well as of sensors, detectors, and image and audio processors, among other technologies, has helped open up a field sometimes referred to as “wearable computing.” In the area of image and visual processing and production, in particular, it has become possible to consider wearable displays that place a very small image display element close enough to a wearer’s (or user’s) eye(s) such that the displayed image fills or nearly fills the field of view, and appears as a normal sized image, such as might be displayed on a traditional image display device. The relevant technology may be referred to as “near-eye displays.”

Near-eye displays are fundamental components of wearable displays, also sometimes called “head-mounted displays” (HMDs). A head-mounted display places a graphic display or displays close to one or both eyes of a wearer. To generate the images on a display, a computer processing system may be used. Such displays may occupy a wearer’s entire field of view, or only occupy part of wearer’s field of view. Further, head-mounted displays may be as small as a pair of glasses or as large as a helmet.

Emerging and anticipated uses of wearable displays include applications in which users interact in real time with an augmented or virtual reality. Such applications can be mission-critical or safety-critical, such as in a public safety or aviation setting. The applications can also be recreational, such as interactive gaming.

SUMMARY

In one aspect, an exemplary computer-implemented method may involve: (a) receiving gaze data for a first wearable computing device, wherein the gaze data is indicative of a wearer-view associated with the first wearable computing device, and wherein the first wearable computing device is associated with a first user-account; (b) analyzing the gaze data from the first wearable computing device to detect one or more occurrences of one or more advertisement spaces in the gaze data; (c) based at least in part on the one or more detected advertisement-space occurrences, determining an individual gaze value for the first user-account; and (d) sending a gaze-value indication, wherein the gaze-value indication indicates the individual gaze value for the first user-account.

In another aspect, an exemplary system may include a non-transitory computer-readable medium and program instructions stored on the non-transitory computer-readable medium. The program instructions may be executable by at least one processor to: (a) receive gaze data for a first wearable computing device, wherein the gaze data is indicative of a wearer-view associated with the first wearable computing device, and wherein the first wearable computing device is associated with a first user-account; (b) analyze the gaze data from the first wearable computing device to detect one or more occurrences of one or more advertisement spaces in the gaze data; (c) based at least in part on the one or more detected advertisement-space occurrences, determine an individual gaze value for the first user-account; and (d) send a gaze-value indication, wherein the gaze-value indication indicates the individual gaze value for the first user-account.

In yet another aspect, an exemplary article of manufacture may include a computer-readable storage medium having instructions stored thereon that, in response to execution by a processor, cause the processor to perform operations. The instructions may include: (a) instructions for receiving gaze data for a first wearable computing device, wherein the gaze data is indicative of a wearer-view associated with the first wearable computing device, and wherein the first wearable computing device is associated with a first user-account; (b) instructions for analyzing the gaze data from the first wearable computing device to detect one or more occurrences of one or more advertisement spaces in the gaze data; (c) instructions for based at least in part on the one or more detected advertisement-space occurrences, determining an individual gaze value for the first user-account; and (d) instructions for sending a gaze-value indication, wherein the gaze-value indication indicates the individual gaze value for the first user-account.

In a further aspect, an exemplary computer-implemented method may involve: (a) receiving gaze data for a first wearable computing device, wherein the gaze data is indicative of a wearer-view associated with the first wearable computing device, and wherein the first wearable computing device is associated with a first user-account; (b) analyzing the gaze data from the first wearable computing device to detect one or more occurrences of one or more advertisements in the gaze data; (c) based at least in part on the one or more detected advertisement occurrences, determining an individual gaze value for the first user-account; and (d) sending a gaze-value indication to the first user-account, wherein the gaze-value indication indicates the individual gaze value for the first user-account.

In yet a further aspect, an exemplary computer-implemented method may involve: (a) receiving, at a wearable computing device, gaze data that is indicative of a wearer-view associated with the wearable computing device; (b) the wearable computing device analyzing the gaze data to detect one or more occurrences of one or more advertisement spaces in the gaze data; (c) based at least in part on the one or more detected advertisement-space occurrences, the wearable computing device determining an individual gaze value for a user-account that is associated with the wearable computing device; and (d) the wearable computing device displaying the individual gaze value.

In an additional aspect, an exemplary system may include a non-transitory computer-readable medium and program instructions stored on the non-transitory computer-readable medium. The program instructions may be executable by at least one processor to: (a) receive gaze data that is indicative of a wearer-view associated with the wearable computing device; (b) analyze the gaze data to detect one or more occurrences of one or more advertisement spaces in the gaze data; (c) based at least in part on the one or more detected advertisement-space occurrences, determine an individual gaze value for a user-account that is associated with the wearable computing device; and (d) display the individual gaze value.

These as well as other aspects, advantages, and alternatives, will become apparent to those of ordinary skill in the art by reading the following detailed description, with reference where appropriate to the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flow chart illustrating a method according to an exemplary embodiment.

FIG. 2 is a simplified block diagram illustrating a communication network via which gaze data may be collected, according to an exemplary embodiment.

FIG. 3A is a flow chart illustrating a method for determining gaze value, according to an exemplary embodiment.

FIG. 3B is a flow chart illustrating a method for using multiple factors to determine an individual gaze value for a user-account, according to an exemplary embodiment.

FIG. 4 is a flow chart illustrating a method for determining gaze value, according to an exemplary embodiment.

FIG. 5A is a flow chart illustrating a method for determining advertisement value, according to an exemplary embodiment.

FIG. 5B is a flow chart illustrating a method for determining ad value, according to an exemplary embodiment.

FIG. 6 is a flow chart illustrating a method that may be carried out at a wearable computing device, according to an exemplary embodiment.

FIG. 7A illustrates a wearable computing system according to an exemplary embodiment.

FIG. 7B illustrates an alternate view of the wearable computing device illustrated in FIG. 7A.

FIG. 8A illustrates another wearable computing system according to an exemplary embodiment.

FIG. 8B illustrates another wearable computing system according to an exemplary embodiment.

FIG. 9 illustrates a schematic drawing of a wearable computing device according to an exemplary embodiment.

FIG. 10 is another flow chart illustrating a method according to an exemplary embodiment.

FIG. 11A is a flow chart illustrating a method for updating a variable rate for advertisement rights, according to an exemplary embodiment.

FIG. 11B is a flow chart illustrating another method for updating a variable rate for advertisement rights, according to an exemplary embodiment.

FIG. 12 is a flow chart illustrating an auction process for advertisement rights, according to an exemplary embodiment.

FIG. 13 is a flow chart illustrating a method for providing an advertisement space valuation in an advertisement marketplace, according to an exemplary embodiment.

FIG. 14 is flow chart illustrating a method for locating potential advertisement spaces, according to an exemplary embodiment.

FIG. 15 is flow chart illustrating a method for providing a search-request feature, according to an exemplary embodiment.

FIG. 16 is flow chart illustrating a method that provides advertiser-request functionality, according to an exemplary embodiment.

FIG. 17A is a flow chart illustrating a method for determining advertisement value according to an exemplary embodiment.

FIG. 17B is a flow chart illustrating another method for determining advertisement value, according to an exemplary embodiment.

FIG. 18 is a flow chart illustrating a method for using multiple factors to determine the ad-value contribution of a given ad-space occurrence in gaze data, according to an exemplary embodiment.

DETAILED DESCRIPTION

Exemplary methods and systems are described herein. It should be understood that the word “exemplary” is used herein to mean “serving as an example, instance, or illustration.” Any embodiment or feature described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments or features. The exemplary embodiments described herein are not meant to be limiting. It will be readily understood that certain aspects of the disclosed systems and methods can be arranged and combined in a wide variety of different configurations, all of which are contemplated herein.

I.* Overview*

A.* Valuing Ad Space Based on Gaze Data*

Many existing methodologies for valuing physical advertising space involve use of different types of data to estimate how many people view an advertisement space (referred to interchangeably as an “ad space”) and/or how effective the advertisement space is at delivering the intended message to the viewer. These methodologies often rely on demographic information and other such indirect measurements of the potential audience for an ad space. Since these methodologies only estimate how many people actually view an ad space and/or who the people are that actually view the ad space, and do not incorporate actual viewership data, the results are often inaccurate.

Some existing valuation techniques do incorporate actual viewership data, which is typically collected for a test group and then extrapolated to the population as a whole (or to a larger group, such as a target market). However, gathering such viewership data with existing methodologies can often be time-consuming and difficult. For example, such techniques often involve polling people in a test group individually or laboriously observing how many people actually view an ad space (e.g., counting vehicles that pass by a billboard). Because of the effort required, advertising is typically limited to certain defined types of spaces (e.g., billboards, television commercials, websites, etc.) for which representative viewership data can be most-readily obtained.

Since most any physical space that is seen by people has some value for purposes of advertising, current valuation techniques do not allow for capitalization of many would-be advertising spaces. While the individual values of such spaces may be small, the cumulative value of all such spaces may be significant. However, due to the limitations of current advertisement valuation and marketing techniques, much of the potential value of such spaces has not been monetized.

Accordingly, exemplary methods and systems may help to determine the value of advertising spaces in a manner that may be more accurate, and may require less data-collection effort than existing advertisement-valuation techniques. In particular, exemplary methods may utilize “gaze data,” from a number of wearable computers, which is indicative of what the wearers of the wearable computers are actually viewing, in order to value physical spaces.

For example, point-of-view (POV) videos from a number of wearable computers may be analyzed in order to determine how frequently a certain space is captured in the POV videos. Notably, POV video from wearable computers may provide a fairly accurate indication of what a user is actually looking at. Therefore, aggregating such POV videos from a number of users may help to more accurately value advertising rights to physical spaces. Additionally, the wearers of the wearable computing devices may elect to make their respective user-profiles available, such that individual characteristics of each wearer who views an advertisement space may be considered. This information may then be used to determine the value of the physical space.

Furthermore, a cloud-based server system may aggregate gaze data from many wearable computers, and use the gaze data to determine wearer-view data for various advertisement spaces. As such, an exemplary embodiment may provide advertisement valuation that is carried out automatically, without the effort required for manual data collection, and is more accurate, as the valuation is based on data that more-accurately captures what people are actually viewing.

B.* Gaze Valuation for Individual Users*

In a further aspect, an exemplary method may be implemented to determine what an individual user’s gaze is worth. In particular, a user who is wearing a wearable computer with a head-mounted display (HMD) may send POV video from a camera attached to their HMD to an advertisement server system. Further, the user may opt in to a program where the POV video (and possibly other forms of gaze data) can be used for gaze valuation and/or to value ad spaces. Accordingly, the server system may analyze the gaze data to detect when the user views ad spaces. The individual gaze value for the user can then be determined based on the ad spaces that the user has viewed.

Further, in many instances, additional information, such as consumer data, demographic information, income, job title, hobbies, and/or interests, among others, may also be considered when determining a gaze value. For example, consider two users who view the exact same advertisements. In this scenario, the gaze value for one of these people might still be higher than for the other if, for example, one person has a significantly higher income than the other. Other examples are also possible.

Yet further, the historical efficacy of advertisements may be considered when determining a gaze value. For example, consider again two people who view the exact same advertisements. If, in the past, one user seems to have been influenced more by advertisements (e.g., as indicated by a pattern of purchasing products subsequent to viewing advertisements for the products), then this user’s gaze value may be higher. Other examples are also possible.

To obtain their gaze value, a user may create a user-account and register a wearable computing device (and possibly other devices) to their user-account. As such, when the server receives gaze data from a given device, the server may associate the gaze data with the user-account to which the given device is registered. Then, each time the server detects an advertisement space in gaze data associated with a given user-account, the server may determine what the occurrence of the ad space is worth (e.g., what having the user view the ad space is worth to an advertiser). This value may be referred to as the “gaze-value contribution” for the occurrence of the ad space in the gaze data. As such, the server may determine the user’s individual gaze value based on gaze-value contributions from a number of ad spaces that occur in the user’s gaze data.

As a specific example, the individual gaze value may be calculated as a dollar amount per day. As such, the server may monitor a given user’s gaze data for occurrences of ad spaces, determine a gaze-value contribution for each occurrence of an ad space that is detected during a one-day period, and then determine an individual gaze value by summing gaze-value contributions from the one-day period. Alternatively, the server may sum the gaze-value contributions for ad-space occurrences on a daily basis, and determine the individual gaze value by averaging the daily total over a number of days. Other variations are of course possible.

Providing users with individual gaze values may be useful in various scenarios. In one aspect, the ability to learn an individual gaze value may be used as an incentive for a user to opt in to a program where the user provides and authorizes use of their gaze data. In particular, when gaze data is used to value advertisement spaces, increasing the number of wearable computing devices from which gaze data is available will typically increase the number of ad spaces that can be valued and/or improve how accurately these ad spaces are valued. Accordingly, a user may be provided with access to individual gaze valuation functions only after the user has created a user-account, agreed to provide gaze data from their wearable computing device (and possibly from other devices that the user may optionally associate with their user account), and authorized their gaze data to be used for purposes of advertisement valuation. Since knowing what their individual gaze is worth may be interesting to many users, access to this functionality may be an incentive for such users to provide and authorize use of their gaze data.

Furthermore, in some embodiments, individual gaze value may be more than just a metric that interests users. Rather, individual gaze value functionality may be utilized to determine payments that are actually paid out users who provide gaze data. More specifically, since gaze data is typically indicative of what a user is actually viewing, an ad space marketplace may be established where advertisers pay for rights to ad spaces that are valued using gaze data, and a portion of the money paid by the advertisers is distributed to the users who provide the gaze data. In particular, when an occurrence of an ad space is detected in gaze data for a given user-account, the server system may update wearer-view data used for valuation of the ad space, and may also determine a value to the advertiser of the particular user viewing the ad space (e.g., a gaze-value contribution for the occurrence of the ad space in the user’s gaze data). A portion of this value may then be credited to the user-account and/or paid out to the user.

As an example of one such application, an ad marketplace may be set up to pay users who provide gaze data a 5% commission on ad spaces they view. As such, users who allow their gaze data to be used for ad valuation may be paid 5% of their individual gaze value in exchange for use of their gaze data. Other examples are also possible.

Note that herein, when gaze data is said to be associated with a given user-account, it should generally be understood that this gaze data was sent by a device that is associated with the given user-account (e.g., a device that is registered with the user-account). Further, gaze data and/or other information that is associated with a user-account may also be said to be associated with a user since, functionally, associating gaze data or any other data with a user will generally be accomplished by associating the data with the user’s user account.

In a further aspect, when a user creates a user-account for which a gaze value may be determined, a user-profile for the user-account may be created as well. The user-profile may include or provide access to various types of information, from various sources, which is related to the user. For simplicity, examples set forth herein may simply refer to a user-account as including the information included in the associated user-profile. However, this should not be read as requiring that a user-account include a user-profile. It is possible, in some embodiments, that a user-account may not have an associated user-profile.

C.* Display on Non-Traditional Surfaces*

In a further aspect, exemplary methods and systems may automatically collect wearer-view data for a large number of advertisement spaces. This may allow for valuation and monetization of many physical spaces that have value for purposes of advertising, and might not otherwise be capitalized.

For example, the shortcomings of existing advertisement valuation are especially problematic when it comes to individuals who wish to associate themselves with a brand or product (e.g., individuals who wish to be sponsored). Because of the cost and/or effort involved in using common valuation techniques to gather viewership data for the average person, sponsorship is generally limited to high-visibility individuals (e.g., famous athletes and musicians). Such high-visibility individuals are typically the most valuable to an advertiser, such that the cost of evaluating the sponsorship is justified by the value to the advertiser. For instance, a famous race-car driver can readily sell advertising space on his or her clothing or on their car. However, there is no market for the average person to do the same (in fact, individuals often pay more to have a brand logo on their clothing). Typically, however, there is still value to the average person promoting a product in this manner. Advantageously, by economically and accurately determining the advertisement value of physical spaces associated with the average person, an exemplary embodiment may help open up sponsorship opportunities for almost anyone.

However, it should be understood that exemplary embodiments may generally be used to value almost any type of physical space. To provide just a few examples, advertisement values may be determined for: (a) the back of the screen of a laptop computer, (b) an article of clothing, (c) a billboard, (d) a surface on an automobile, (e) a body surface, (f) a space on a webpage, (g) a print advertisement space, (h) a surface on product packaging, and/or (i) a pet. Many other types of advertisement spaces may also be valued utilizing an exemplary embodiment.

Further, an exemplary methods and systems may be used to value physical spaces types for various different advertisement formats such as: (a) print advertisements, (b) computer-generated images, (c) video, (d) peel and stick paper advertisements, (e) two-dimensional projections, (f) a three-dimensional projections, (g) iron-on images, (h) temporary tattoos, and/or (i) other advertising formats.

D.* Advertisement Marketplace*

visibility individuals (e.g., famous athletes and musicians). Such high-visibility individuals are typically the most valuable to an advertiser, such that the cost of evaluating the sponsorship is justified by the value to the advertiser. For instance, a famous race-car driver can readily sell advertising space on his or her clothing or on their car. However, there is no market for the average person to do the same (in fact, individuals often pay more to have a brand logo on their clothing). Typically, however, there is still value to the average person promoting a product in this manner. Advantageously, by economically and accurately determining the advertisement value of physical spaces associated with the average person, an exemplary embodiment may help open up sponsorship opportunities for almost anyone.

However, it should be understood that exemplary embodiments may generally be used to value almost any type of physical space. To provide just a few examples, advertisement values may be determined for: (a) the back of the screen of a laptop computer, (b) an article of clothing, (c) a billboard, (d) a surface on an automobile, (e) a body surface, (f) a space on a webpage, (g) a print advertisement space, (h) a surface on product packaging, and/or (i) a pet. Many other types of advertisement spaces may also be valued utilizing an exemplary embodiment.

Further, an exemplary methods and systems may be used to value physical spaces types for various different advertisement formats such as: (a) print advertisements, (b) computer-generated images, (c) video, (d) peel and stick paper advertisements, (e) two-dimensional projections, (f) a three-dimensional projections, (g) iron-on images, (h) temporary tattoos, and/or (i) other advertising formats.

B.* Advertisement Marketplace*

Provided with the ability to determine an advertising value for almost any physical space, there is a need for a marketplace system to facilitate transactions involving use of such physical spaces as advertisement spaces. Accordingly, exemplary methods and systems may help to provide an advertisement marketplace.

In an exemplary marketplace, gaze-data-based valuation may be used to price advertising rights. For instance, in some applications, advertisement rights to an advertisement space may be listed at the advertisement value, or at a fixed rate that is based on the advertisement value. In other instances, advertisement rights may be listed at a variable rate. For example, an initial rate may be based on the advertisement value at or near the time of purchase. The system may then adjust this rate based on views of the advertisement during the advertising period (e.g., based on how often the advertisement space is detected in subsequent gaze data). Other gaze-data-based pricing structures for advertisement spaces are also possible.

Note that in an exemplary embodiment, the advertisement value upon which the listing price is based may be a “relative advertisement value.” More specifically, the relative advertisement value may be determined pre-sale, and thus may differ from the price that the advertisement space ultimately sells for in an open market. For example, a relative advertisement value may be determined for an advertisement space before any advertisement is placed, based on gaze data in which the bare advertisement space is detected. As such, the selling price may ultimately differ based on what the market is willing to pay for the advertisement space. Thus, in some embodiments the true or official advertisement value may be considered to be the market price, and thus may differ from the relative advertisement value.

In some embodiments, an exemplary marketplace may include various features to assist a user who wishes to list an advertisement space for sale in the marketplace. For instance, an exemplary system may support valuation requests, which allows a user to request and be provided with gaze-data-based advertisement values for the user’s advertisement spaces. Such valuation requests may help users evaluate whether or not to list an advertisement space in the marketplace. More specifically, once provided with the advertisement value for their advertisement space, a user may then elect to list the advertisement space at a listing price that is based on this advertisement value.

Further, an exemplary system may allow a user to sell advertising rights for a wide variety of physical spaces. For instance, an exemplary system may have pre-defined types of physical spaces that can be valued as an advertisement space and listed for sale (e.g., higher-visibility types of physical spaces such as a billboard, the back of a laptop computer, the front of a shirt, etc.). As such, an exemplary system may automatically search gaze data for the pre-defined types of physical spaces, and in so doing may identify potential advertisement spaces. Once a physical space has been identified as a potential advertisement space, the system may allow a user to sell advertisement rights to the advertisement space via the advertisement marketplace.

An exemplary advertisement marketplace may additionally or alternatively allow a user to dynamically define a physical space as an advertisement space, even if it is not pre-defined as such. For instance, the system may provide features via which a user can submit images, video, and/or other information that allows the system to detect when an advertisement space occurs in gaze data. After receiving such information, the system can search for the user-defined advertisement space in gaze data, so that the advertisement space can be valued and/or listed in the advertisement marketplace.

In some embodiments, an exemplary system may provide a user who wishes to list advertisement spaces with suggestions of advertisement spaces that can be listed by the user. In particular, the marketplace system may search gaze data (and possibly other data sources as well) for physical spaces that are associated with the given user and that are usable as advertisement spaces. The system may do so automatically or on request by a given user. In either case, the user may then be provided with suggestions of unlisted advertisement spaces (possibly including valuations of each advertisement space), which the user can list in the advertisement marketplace. This may be particularly useful in the scenario where a user is unaware that a certain physical space is usable as an advertisement space. In this scenario, the suggestions may inform a user of the existence of advertisement spaces that the user was previously unaware of. Of course, ad-space suggestions may be useful in other scenarios as well.

An exemplary system may also include various features to assist an advertiser who wishes to purchase an advertisement space. For instance, a marketplace system may allow an advertiser to search, browse, and/or purchase advertisement spaces that are listed in the marketplace.

Furthermore, an exemplary system may allow an advertiser to identify or define an advertisement space for which they are interested in purchasing advertisement rights. In this regard, the advertiser may be provided with similar features as those provided to a user wishing to list an advertisement space, which allow the advertiser to dynamically define a physical space as an advertisement space, and/or to identify a pre-defined type of advertisement space. Once an advertisement space has been identified, the marketplace system may identify a user that is authorized to list the advertisement space, and notify the user that there is interest in their advertisement space.

In a further aspect, an exemplary marketplace may include features to facilitate a transaction to purchase advertisement rights between the user who listed the advertisement space and the advertiser who is purchasing the advertisement space. The advertisement marketplace may also facilitate completion of the contract created between the seller and the purchaser after such a transaction. In particular, when an advertiser purchases an advertisement space, an exemplary marketplace system may create and maintain a record of a contract between the advertiser and user who sold the advertisement. The system may also provide features to facilitate performance of the contract. For instance, a server may search gaze data received post-contract to determine that the advertisement specified by the advertiser is being displayed in the advertisement space in accordance with the contract. Further, the system may facilitate billing the advertiser, and possibly even transferring funds between user-accounts for the advertiser and the seller.

Note that herein, when gaze data is said to be associated with a given user-account, it should generally be understood that this gaze data was sent by a device that is associated with the given user-account (e.g., a device that is registered with the user-account). Further, gaze data and/or other information that is associated with a user-account may also be said to be associated with a user since, functionally, associating gaze data or any other data with a user will generally be accomplished by associating the data with the user’s user account.

In a further aspect, when a user creates a user-account for which a gaze value may be determined, a user-profile for the user-account may be created as well. The user-profile may include or provide access to various types of information, from various sources, which is related to the user. For simplicity, examples set forth herein may simply refer to a user-account as including the information included in the associated user-profile. However, this should not be read as requiring that a user-account include a user-profile. It is possible, in some embodiments, that a user-account may not have an associated user-profile. Furthermore, herein, the term user-profile may more generally be understood to refer to any information or collection of information related to a given user. As such, a user-profile may be specifically created for a user-account or may simply take the form of data that is associated with a given user.

II.* Exemplary Methods*

FIG. 1 is a flow chart illustrating a method according to an exemplary embodiment. The method 100 shown in FIG. 1 may be implemented by a computing device, and in particular, by a server system, in order to determine a gaze value for a wearable computing device and/or for a user-profile associated with the wearable computing device. According to an exemplary embodiment, the gaze value is based on point-of-view gaze data received from a wearable computing device (which may be referred to interchangeably as a wearable computing device or a wearable computer). Further, a server system that implements an exemplary method may be referred to as a gaze-valuation system, as a gaze-valuation server, as an ad-valuation server, or simply as a server system or server.

As shown by block 102, method 100 involves a gaze-valuation server receiving gaze data for a first wearable computing device, which is associated with a first user-account. The server may analyze the gaze data from the first wearable computing device to detect occurrences of advertisement spaces in the gaze data, as shown by block 104. Then, based at least in part on the detected ad-space occurrences, the server may determine an individual gaze value for the first user-account, as shown by block 106. The server may then send a gaze-value indication, which indicates the individual gaze value, to the first user-account, as shown by block 108.

In an exemplary method 100, the gaze data received for a given wearable computing device is generally indicative of the wearer-view associated with the wearable computing device. For example, server may receive gaze data from a wearable computing device in the form of point-of-view (POV) video that is captured at the wearable computing device. As such, the POV video may be monitored in order to detect when advertisement spaces occur in the video.

In an exemplary method, such as method 100, gaze data may additionally or alternatively take forms other than point-of-view video. For example, the gaze data may take the form of point-of-view images captured by a forward- or outward-facing camera on a wearable computing device or another device. As a specific example, a given wearable computing device may periodically take a picture using a camera on an HMD that is generally aligned with the wearer’s field of view. The wearable computing device may send these periodically-captured pictures to the server system for use in an exemplary method. Other examples are also possible.

Since the gaze data from a given wearable computing device is generally indicative of the wearer-view of the wearable computing device’s wearer, the gaze data may be interpreted to be generally indicative of what the wearer of the device is actually looking at. For instance, the gaze data may be analyzed to determine information such as when a wearer is looking at a particular ad space and/or how long the wearer was looking at the particular ad space, among other information. Accordingly, the gaze data may be used to determine a gaze value for the wearer.

In an exemplary embodiment, the individual gaze value for a user (which may also be referred to as the gaze value) is indicative of the value of the user’s gaze to advertisers. More specifically, the value of the user’s gaze may represent the cumulative value to advertisers of the user viewing advertisements over time. As such, determining the individual gaze value may involve determining what each view is worth to an advertiser (e.g., what each occurrence of an ad space in gaze data associated with the given user is worth) and calculating a total value for all of the user’s views.

Exemplary systems will now be described before further details of exemplary methods are set forth.

III.* Exemplary Server Systems*

FIG. 2 is a simplified block diagram illustrating a communication network via which gaze data may be received, according to an exemplary embodiment. As shown, communication network 200 includes a number of wearable computing devices 202A to 202D, which are configured to communicate with a server system 204 via one or more networks 206. An exemplary network, such as communication network 200, may also include computing devices other than wearable computing devices, such as laptop computer 203 and mobile phone 205, for instance. As such, an exemplary advertisement marketplace may be implemented in a network such as communication network 200.

In order to facilitate an exemplary method, the users of wearable computing devices 202A to 202D may register their respective devices and opt in to programs via which the users submit gaze data from their respective devices. As such, wearable computing devices 202A to 202D may send gaze data to the server system 204, which the server system 204 may then analyze to help determine advertisement values for advertisement spaces, possibly to valuate advertisement spaces as well. Further, in some embodiments, laptop 203, mobile phone 205, and/or other computing devices may provide supplemental gaze data, which may be used by server system 204 to supplement the gaze data from wearable computing devices 202A to 202D.

In an exemplary embodiment, the server system 204 may be a computing system including one or more computing devices. In particular, server system 204 may be a cloud-based server system that is configured to receive gaze data, and to determine a gaze value for at least one of wearable computing devices 202A to 202D. In a further aspect, the server system 204 may also be configured to utilize the gaze data to value advertising spaces and/or support an advertisement-space marketplace for advertising spaces.

As noted, the gaze data in an exemplary embodiment may include point-of-view videos captured by a number of wearable computing devices. For example, some or all of the wearable computing devices 202A to 202D may include or take the form of glasses-style HMDs that each include a forward-facing video camera for taking point-of-view video (e.g., video that generally captures the perspective of a person wearing the HMD). As such, when the HMD is worn, the forward-facing camera will capture video and/or images that are generally indicative of what the wearer of the HMD sees. Note that exemplary glasses-style HMDs will be described in greater detail with reference to FIGS. 7A, 7B, 8A, 8B, and 9.

Further, server system 204 may include or be in communication with an ad-valuation server 212 and an ad-marketplace server 214. In some embodiments, ad-valuation server 212 and ad-marketplace server 214 may be separate server systems, which each include one or more computing devices. In other embodiments, some or all of the functionality attributed to ad-valuation server 212 and ad-marketplace server 214 may be provided by a single server system, which may include one or more computing devices.

In an exemplary embodiment, ad-valuation server 212 may be configured to receive gaze data from wearable computing devices 202A to 202D. Further, ad-valuation server 212 may analyze the received gaze data for occurrences of one or more ad spaces, and generate wearer-view data for the ad spaces based on occurrences of the ad spaces in the gaze data.

In a further aspect, the server system 204 may include or have access to a wearer-view database 208 that includes wearer-view data for a number of advertisement spaces (e.g., ad spaces indicated by ad-space database 210). When ad-valuation server 212 generates wearer-view data, ad-valuation server 212 may store the generated data in wearer-view database 208. Accordingly, server system 204 may access the wearer-view database 208 to retrieve wearer-view data for a given ad space, which in turn may be used to determine the ad value for the given ad space.

To assist the server in detecting occurrences of various ad spaces in gaze data, advertisement server 204 may include or have access to an ad-space database 210 that includes information that can be used to identify various ad spaces. Accordingly, ad server system 204 may use the identifying information from ad space database 210 to determine when ad spaces occur in gaze data from wearable computing devices 202A to 202D. Further, in embodiments that utilize location data for ad spaces, ad-space database 210 may also store location information for individual ad spaces.

In another aspect, ad-valuation server 212 and/or other components of system 204 may additionally or alternatively be configured to use gaze data to determine an individual gaze value for a given user-account. As such, ad-valuation server 212 and/or other components of system 204 may include program instructions stored in a tangible computer-readable medium that are executable to provide the functionality described herein, and possibly to provide other functionality as well.

In another aspect, server system 204 may include ad-marketplace server 214, which is configured to provide an advertisement marketplace via which advertisement spaces that are valued by ad-valuation server 212 can be bought and sold. Further, ad-marketplace server 214 may facilitate transactions between parties in such an advertisement marketplace. As such, computing devices such as wearable computing devices 202A to 202D, laptop computer 203, and/or mobile phone 205, may be provided with advertisement marketplace functions via the server system 204, and in particular, via ad-marketplace server 214.

Data related to advertisement space in the advertisement marketplace may be stored in ad-space database 210. For instance, ad-marketplace server 214 and/or other components of server system 204 may support an advertisement marketplace including features for listing advertisement rights to an advertisement space for sale, a bidding system for physical spaces (e.g., auction functionality), organization and indexing of available physical spaces, searching and/or browsing listings for advertisement spaces, tracking usage of advertisement spaces, calculation of fees and other billing functions, and/or portfolio management for sellers and purchasers of advertisement space, among other features.

Further, server system 204 may provide access to an advertisement marketplace via a website, via a standalone application, and/or via other points of access. Data related to listings and/or transactions in the advertisement marketplace may then be stored in ad-space database 210.

IV.* Detecting Advertisement Spaces in Gaze Data*

As noted above, an exemplary method 100 may involve analysis of gaze data to detect when advertisement spaces occurs in the gaze data. To do so, an exemplary server system 200 may employ various types of video and/or image-processing techniques. For instance, advertisement server system 204 may implement various well known and yet-to-be-developed techniques for object recognition in video and/or still images in the process of recognizing advertising spaces.