U.S. patent application number 16/011984 was filed with the patent office on 2019-12-19 for starting electronic communication based on captured image.
The applicant listed for this patent is Microsoft Technology Licensing, LLC. Invention is credited to Jingwei Huang, Haoyang Li, Viet Hung Nguyen, Haowen Ning, Christopher Szeto.
Application Number | 20190387155 16/011984 |
Document ID | / |
Family ID | 68840532 |
Filed Date | 2019-12-19 |
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United States Patent
Application |
20190387155 |
Kind Code |
A1 |
Szeto; Christopher ; et
al. |
December 19, 2019 |
STARTING ELECTRONIC COMMUNICATION BASED ON CAPTURED IMAGE
Abstract
Techniques for starting an electronic communication based on a
captured image are disclosed herein. In some embodiments, a
computer system detects that an image has been captured by a camera
on a first mobile device of a first user, where the captured image
has been captured by the camera at a point in time, and, in
response to detecting that the image has been captured, the
computer system identifies at least one other user in the captured
image. In some example embodiments, the computer system transmits a
message to an electronic destination associated with the other
user(s) based on the identifying of the other user(s) in the
captured image.
Inventors: |
Szeto; Christopher;
(Mountain View, CA) ; Nguyen; Viet Hung; (Fremont,
CA) ; Huang; Jingwei; (Campbel, CA) ; Ning;
Haowen; (Sunnyvale, CA) ; Li; Haoyang; (San
Jose, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Microsoft Technology Licensing, LLC |
Redmond |
WA |
US |
|
|
Family ID: |
68840532 |
Appl. No.: |
16/011984 |
Filed: |
June 19, 2018 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H04N 5/23209 20130101;
H04N 5/23241 20130101; G06K 9/00288 20130101; H04N 7/18 20130101;
H04L 51/32 20130101; G06K 9/00677 20130101; H04N 5/23219 20130101;
H04N 5/23206 20130101; H04L 51/10 20130101 |
International
Class: |
H04N 5/232 20060101
H04N005/232 |
Claims
1. A computer-implemented method comprising: detecting, by a
computer system comprising a memory and at least one hardware
processor, that an image has been captured by a camera on a first
mobile device of a first user, the captured image having been
captured by the camera at a point in time; in response to detecting
that the image has been captured, identifying, by the computer
system, at least one other user in the captured image, the
identifying comprising: determining a location of the first mobile
device for the point in time; identifying a plurality of candidate
users based on a determination that the plurality of candidate
users are located near the determined location of the first mobile
device for the point in time; for each one of the candidate users,
accessing at least one profile image of the one of the candidate
users from a corresponding profile of the one of the candidate
users on a social networking service; for each one of the candidate
users, comparing the at least one profile image of the one of the
candidate user with the captured image; and determining that a
subset of the candidate users are present in the captured image
based on the comparing, the subset of the candidate users being
identified as the at least one other user in the captured image;
and transmitting, by the computer system, a message to an
electronic destination associated with the at least one other user
based on the identifying of the at least one other user in the
captured image.
2. The computer-implemented method of claim 1, wherein the
identifying further comprises: causing a user interface to be
displayed on the first mobile device, the user interface displaying
an indication of each candidate user in the subset of candidate
users, and the user interface being configured to receive user
input from the first user to confirm, for each one of the candidate
users in the subset of candidate users, whether the one of the
candidate users is present in the captured image; and receiving,
from the first mobile device, user input confirming that the subset
of candidate users are present in the captured image, wherein the
determining that the subset of the candidate users are present in
the captured image is further based on user input confirming that
the subset of candidate users are present in the captured
image.
3. The computer-implemented method of claim 2, further comprising:
determining, by the computer system, a corresponding level of
relevance for each candidate user in the subset of candidate users;
and ranking, by the computer system, the candidate users in the
subset of candidate users based on their corresponding levels of
relevance, wherein the indications of the candidate users in the
subset of candidate users are displayed in an order based on the
ranking.
4. The computer-implemented method of claim 1, further comprising
generating, by the computer system, the message in response to the
determining that the subset of the candidate users are present in
the captured image.
5. The computer-implemented method of claim 4, wherein the
generating the message comprises automatically including the
captured image in the message without receiving a user instruction
from the first mobile device to include the captured image in the
message.
6. The computer-implemented method of claim 4, wherein the
generating the message comprises automatically addressing the
message to the electronic destination without the first user
specifying the electronic destination.
7. The computer-implemented method of claim 1, further comprising:
determining, by the computer system, that an additional user in the
captured image cannot be identified in the identifying of at least
one other user in the captured image; causing, by the computer
system, a user interface to be displayed on the first mobile
device, the user interface displaying an indication of the
additional user, and the user interface being configured to receive
an identification of the additional user from the first user; and
receiving, by the computer system, the identification of the
additional user from the first mobile device, wherein the message
is transmitted to an electronic destination associated with the
additional user based on the identification of the additional
user.
8. The computer-implemented method of claim 7, wherein the
comparing of the at least one profile image of the one of the
candidate user with the captured image is based on a facial
recognition model, and the method further comprises: modifying, by
the computer system, the facial recognition model using one or more
machine learning operations based on the captured image and the
identification of the additional user.
9. The computer-implemented method of claim 1, wherein performance
of the identifying the at least one other user in the captured
image is conditioned upon a determination the captured image
includes the first user.
10. A system comprising: at least one hardware processor; and a
non-transitory machine-readable medium embodying a set of
instructions that, when executed by the at least one hardware
processor, cause the at least one processor to perform operations,
the operations comprising: detecting that an image has been
captured by a camera on a first mobile device of a first user, the
captured image having been captured by the camera at a point in
time; in response to detecting that the image has been captured,
identifying at least one other user in the captured image, the
identifying comprising: determining a location of the first mobile
device for the point in time; identifying a plurality of candidate
users based on a determination that the plurality of candidate
users are located near the determined location of the first mobile
device for the point in time; for each one of the candidate users,
accessing at least one profile image of the one of the candidate
users from a corresponding profile of the one of the candidate
users on a social networking service; for each one of the candidate
users, comparing the at least one profile image of the one of the
candidate user with the captured image; and determining that a
subset of the candidate users are present in the captured image
based on the comparing, the subset of the candidate users being
identified as the at least one other user in the captured image;
and transmitting a message to an electronic destination associated
with the at least one other user based on the identifying of the at
least one other user in the captured image.
11. The system of claim 10, wherein the identifying further
comprises: causing a user interface to be displayed on the first
mobile device, the user interface displaying an indication of each
candidate user in the subset of candidate users, and the user
interface being configured to receive user input from the first
user to confirm, for each one of the candidate users in the subset
of candidate users, whether the one of the candidate users is
present in the captured image; and receiving, from the first mobile
device, user input confirming that the subset of candidate users
are present in the captured image, wherein the determining that the
subset of the candidate users are present in the captured image is
further based on user input confirming that the subset of candidate
users are present in the captured image.
12. The system of claim 11, further comprising: determining a
corresponding level of relevance for each candidate user in the
subset of candidate users; and ranking the candidate users in the
subset of candidate users based on their corresponding levels of
relevance, wherein the indications of the candidate users in the
subset of candidate users are displayed in an order based on the
ranking.
13. The system of claim 10, further comprising generating the
message in response to the determining that the subset of the
candidate users are present in the captured image.
14. The system of claim 13, wherein the generating the message
comprises automatically including the captured image in the message
without receiving a user instruction from the first mobile device
to include the captured image in the message.
15. The system of claim 13, wherein the generating the message
comprises automatically addressing the message to the electronic
destination without the first user specifying the electronic
destination.
16. The system of claim 10, further comprising: determining that an
additional user in the captured image cannot be identified in the
identifying of at least one other user in the captured image;
causing a user interface to be displayed on the first mobile
device, the user interface displaying an indication of the
additional user in the captured image, and the user interface being
configured to receive an identification of the additional user from
the first user; and receiving the identification of the additional
user from the first mobile device, wherein the message is
transmitted to an electronic destination associated with the
additional user based on the identification of the additional
user.
17. The system of claim 16, wherein the comparing of the at least
one profile image of the one of the candidate user with the
captured image is based on a facial recognition model, and the
method further comprises: modifying the facial recognition model
using one or more machine learning operations based on the captured
image and the identification of the additional user.
18. The system of claim 10, wherein performance of the identifying
the at least one other user in the captured image is conditioned
upon a determination the captured image includes the first
user.
19. A non-transitory machine-readable medium embodying a set of
instructions that, when executed by at least one hardware
processor, cause the processor to perform operations, the
operations comprising: detecting that an image has been captured by
a camera on a first mobile device of a first user, the captured
image having been captured by the camera at a point in time; in
response to detecting that the image has been captured, identifying
at least one other user in the captured image, the identifying
comprising: determining a location of the first mobile device for
the point in time; identifying a plurality of candidate users based
on a determination that the plurality of candidate users are
located near the determined location of the first mobile device for
the point in time; for each one of the candidate users, accessing
at least one profile image of the one of the candidate users from a
corresponding profile of the one of the candidate users on a social
networking service; for each one of the candidate users, comparing
the at least one profile image of the one of the candidate user
with the captured image; and determining that a subset of the
candidate users are present in the captured image based on the
comparing, the subset of the candidate users being identified as
the at least one other user in the captured image; and transmitting
a message to an electronic destination associated with the at least
one other user based on the identifying of the at least one other
user in the captured image.
20. The non-transitory machine-readable medium of claim 19, wherein
the identifying further comprises: causing a user interface to be
displayed on the first mobile device, the user interface displaying
an indication of each candidate user in the subset of candidate
users, and the user interface being configured to receive user
input from the first user to confirm, for each one of the candidate
users in the subset of candidate users, whether the one of the
candidate users is present in the captured image; and receiving,
from the first mobile device, user input confirming that the subset
of candidate users are present in the captured image, wherein the
determining that the subset of the candidate users are present in
the captured image is further based on user input confirming that
the subset of candidate users are present in the captured image.
Description
TECHNICAL FIELD
[0001] The present application relates generally to systems,
methods, and computer program products for starting electronic
communication based on a captured image.
BACKGROUND
[0002] Starting an electronic communication with other people, such
as an e-mail message, a text message, or a conversation within a
messaging application of a mobile app, often requires multiple
operations to be performed by a user. For example, the user
typically has to manually specify the identities of the other
people or electronic destinations associated with the other people
(e.g., e-mail addresses, phone numbers). Additionally, if the user
wants to include a picture in the electronic communication, such as
a group selfie including the other people, the user has to manually
select the picture to include it in the electronic communication.
As a result of having to perform all of these operations, the
amount of time and complexity that is involved in sending an
electronic communication is increased. Other technical problems may
arise as well.
BRIEF DESCRIPTION OF THE DRAWINGS
[0003] Some embodiments of the present disclosure are illustrated
by way of example and not limitation in the figures of the
accompanying drawings, in which like reference numbers indicate
similar elements.
[0004] FIG. 1 is a block diagram illustrating a client-server
system, in accordance with an example embodiment.
[0005] FIG. 2 is a block diagram showing the functional components
of a social networking service within a networked system, in
accordance with an example embodiment.
[0006] FIG. 3 is a block diagram illustrating a communication
system, in accordance with an example embodiment.
[0007] FIG. 4 illustrates a user interface displaying a captured
image and an indication of candidate users identified as being
present in the captured image, in accordance with an example
embodiment.
[0008] FIG. 5 illustrates a user interface displaying a
conversation started based on a captured image, in accordance with
an example embodiment.
[0009] FIG. 6 is a flowchart illustrating a method of starting a
communication based on a captured image, in accordance with an
example embodiment.
[0010] FIG. 7 is a flowchart illustrating a method of identifying
users in a captured image, in accordance with an example
embodiment.
[0011] FIG. 8 is a flowchart illustrating another method of
identifying users in a captured image, in accordance with an
example embodiment.
[0012] FIG. 9 is a flowchart illustrating yet another method of
identifying users in a captured image, in accordance with an
example embodiment.
[0013] FIG. 10 is a flowchart illustrating yet another method of
identifying users in a captured image, in accordance with an
example embodiment.
[0014] FIG. 11 is a block diagram illustrating a mobile device, in
accordance with some example embodiments.
[0015] FIG. 12 is a block diagram of an example computer system on
which methodologies described herein may be executed, in accordance
with an example embodiment.
DETAILED DESCRIPTION
[0016] Example methods and systems of starting an electronic
communication based on a captured image are disclosed. In the
following description, for purposes of explanation, numerous
specific details are set forth in order to provide a thorough
understanding of example embodiments. It will be evident, however,
to one skilled in the art that the present embodiments may be
practiced without these specific details.
[0017] Some or all of the above problems may be addressed by one or
more example embodiments disclosed herein. Some technical effects
of the system and method of the present disclosure are to reduce
the number of operations that need to be performed to start an
electronic communication with other users by starting the
electronic communication based on a captured image of the other
users. The system can identify other users in a captured image by
comparing user profile images with the captured image, and then use
those identifications to determine electronic destinations for
transmitting the electronic communication. Furthermore, the system
can minimize the search space of user profile images that are
compared with the captured image by filtering the user profile
images used based on location of the corresponding users, thereby
improving the speed of the identification process, and consequently
improving the speed of starting the electronic communication.
Additionally, other technical effects will be apparent from this
disclosure as well.
[0018] In some example embodiments, operations are performed by a
computer system (or other machine) having a memory and at least one
hardware processor, with the operations comprising: detecting that
an image has been captured by a camera on a first mobile device of
a first user, the captured image having been captured by the camera
at a point in time; in response to detecting that the image has
been captured, identifying at least one other user in the captured
image; and transmitting a message to an electronic destination
associated with the at least one other user based on the
identifying of the at least one other user in the captured
image.
[0019] In some example embodiments, the identifying comprises:
determining a location of the first mobile device for the point in
time; identifying a plurality of candidate users based on a
determination that the plurality of candidate users are located
near the determined location of the first mobile device for the
point in time; for each one of the candidate users, accessing at
least one profile image of the one of the candidate users from a
corresponding profile of the one of the candidate users on a social
networking service; for each one of the candidate users, comparing
the at least one profile image of the one of the candidate user
with the captured image; and determining that a subset of the
candidate users are present in the captured image based on the
comparing, the subset of the candidate users being identified as
the at least one other user in the captured image.
[0020] In some example embodiments, the identifying further
comprises: causing a user interface to be displayed on the first
mobile device, the user interface displaying an indication of each
candidate user in the subset of candidate users, and the user
interface being configured to receive user input from the first
user to confirm, for each one of the candidate users in the subset
of candidate users, whether the one of the candidate users is
present in the captured image; and receiving, from the first mobile
device, user input confirming that the subset of candidate users
are present in the captured image, wherein the determining that the
subset of the candidate users are present in the captured image is
further based on user input confirming that the subset of candidate
users are present in the captured image.
[0021] In some example embodiments, the operations further
comprise: determining a corresponding level of relevance for each
candidate user in the subset of candidate users; and ranking the
candidate users in the subset of candidate users based on their
corresponding levels of relevance, wherein the indications of the
candidate users in the subset of candidate users are displayed in
an order based on the ranking.
[0022] In some example embodiments, the operations further comprise
generating the message in response to the determining that the
subset of the candidate users are present in the captured
image.
[0023] In some example embodiments, the generating the message
comprises automatically including the captured image in the message
without receiving a user instruction from the first mobile device
to include the captured image in the message.
[0024] In some example embodiments, the generating the message
comprises automatically addressing the message to the electronic
destination without the first user specifying the electronic
destination.
[0025] In some example embodiments, the operations further
comprise: determining that an additional user in the captured image
cannot be identified in the identifying of at least one other user
in the captured image; causing a user interface to be displayed on
the first mobile device, the user interface displaying an
indication of the additional user in the captured image, and the
user interface being configured to receive an identification of the
additional user from the first user; and receiving the
identification of the additional user from the first mobile device,
wherein the message is transmitted to an electronic destination
associated with the additional user based on the identification of
the additional user.
[0026] In some example embodiments, the comparing of the at least
one profile image of the one of the candidate user with the
captured image is based on a facial recognition model, and the
operations further comprise: modifying the facial recognition model
using one or more machine learning operations based on the captured
image and the identification of the additional user.
[0027] In some example embodiments, performance of the identifying
the at least one other user in the captured image is conditioned
upon a determination the captured image includes the first
user.
[0028] The methods or embodiments disclosed herein may be
implemented as a computer system having one or more modules (e.g.,
hardware modules or software modules). Such modules may be executed
by one or more processors of the computer system. The methods or
embodiments disclosed herein may be embodied as instructions stored
on a machine-readable medium that, when executed by one or more
processors, cause the one or more processors to perform the
instructions.
[0029] FIG. 1 is a block diagram illustrating a client-server
system 100, in accordance with an example embodiment. A networked
system 102 provides server-side functionality via a network 104
(e.g., the Internet or Wide Area Network (WAN)) to one or more
clients. FIG. 1 illustrates, for example, a web client 106 (e.g., a
browser) and a programmatic client 108 executing on respective
client machines 110 and 112.
[0030] An Application Program Interface (API) server 114 and a web
server 116 are coupled to, and provide programmatic and web
interfaces respectively to, one or more application servers 118.
The application servers 118 host one or more applications 120. The
application servers 118 are, in turn, shown to be coupled to one or
more database servers 124 that facilitate access to one or more
databases 126. While the applications 120 are shown in FIG. 1 to
form part of the networked system 102, it will be appreciated that,
in alternative embodiments, the applications 120 may form part of a
service that is separate and distinct from the networked system
102.
[0031] Further, while the system 100 shown in FIG. 1 employs a
client-server architecture, the present disclosure is of course not
limited to such an architecture, and could equally well find
application in a distributed, or peer-to-peer, architecture system,
for example. The various applications 120 could also be implemented
as standalone software programs, which do not necessarily have
networking capabilities.
[0032] The web client 106 accesses the various applications 120 via
the web interface supported by the web server 116. Similarly, the
programmatic client 108 accesses the various services and functions
provided by the applications 120 via the programmatic interface
provided by the API server 114.
[0033] FIG. 1 also illustrates a third party application 128,
executing on a third party server machine 130, as having
programmatic access to the networked system 102 via the
programmatic interface provided by the API server 114. For example,
the third party application 128 may, utilizing information
retrieved from the networked system 102, support one or more
features or functions on a website hosted by the third party. The
third party website may, for example, provide one or more functions
that are supported by the relevant applications of the networked
system 102.
[0034] In some embodiments, any website referred to herein may
comprise online content that may be rendered on a variety of
devices, including but not limited to, a desktop personal computer,
a laptop, and a mobile device (e.g., a tablet computer, smartphone,
etc.). In this respect, any of these devices may be employed by a
user to use the features of the present disclosure. In some
embodiments, a user can use a mobile app on a mobile device (any of
machines 110, 112, and 130 may be a mobile device) to access and
browse online content, such as any of the online content disclosed
herein. A mobile server (e.g., API server 114) may communicate with
the mobile app and the application server(s) 118 in order to make
the features of the present disclosure available on the mobile
device.
[0035] In some embodiments, the networked system 102 may comprise
functional components of a social networking service. FIG. 2 is a
block diagram showing the functional components of a social
networking system 210, including a data processing module referred
to herein as a communication system 216, for use in social
networking system 210, consistent with some embodiments of the
present disclosure. In some embodiments, the communication system
216 resides on application server(s) 118 in FIG. 1. However, it is
contemplated that other configurations are also within the scope of
the present disclosure.
[0036] As shown in FIG. 2, a front end may comprise a user
interface module (e.g., a web server) 212, which receives requests
from various client-computing devices, and communicates appropriate
responses to the requesting client devices. For example, the user
interface module(s) 212 may receive requests in the form of
Hypertext Transfer Protocol (HTTP) requests, or other web-based,
application programming interface (API) requests. In addition, a
member interaction detection module 213 may be provided to detect
various interactions that members have with different applications,
services and content presented. As shown in FIG. 2, upon detecting
a particular interaction, the member interaction detection module
213 logs the interaction, including the type of interaction and any
meta-data relating to the interaction, in a member activity and
behavior database 222.
[0037] An application logic layer may include one or more various
application server modules 214, which, in conjunction with the user
interface module(s) 212, generate various user interfaces (e.g.,
web pages) with data retrieved from various data sources in the
data layer. With some embodiments, individual application server
modules 214 are used to implement the functionality associated with
various applications and/or services provided by the social
networking service. In some example embodiments, the application
logic layer includes the communication system 216.
[0038] As shown in FIG. 2, a data layer may include several
databases, such as a database 218 for storing profile data,
including both member profile data and profile data for various
organizations (e.g., companies, schools, etc.). Consistent with
some embodiments, when a person initially registers to become a
member of the social networking service, the person will be
prompted to provide some personal information, such as his or her
name, age (e.g., birthdate), gender, interests, contact
information, home town, address, the names of the member's spouse
and/or family members, educational background (e.g., schools,
majors, matriculation and/or graduation dates, etc.), employment
history, skills, professional organizations, and so on. This
information is stored, for example, in the database 218. Similarly,
when a representative of an organization initially registers the
organization with the social networking service, the representative
may be prompted to provide certain information about the
organization. This information may be stored, for example, in the
database 218, or another database (not shown). In some example
embodiments, the profile data may be processed (e.g., in the
background or offline) to generate various derived profile data.
For example, if a member has provided information about various job
titles the member has held with the same company or different
companies, and for how long, this information can be used to infer
or derive a member profile attribute indicating the member's
overall seniority level, or seniority level within a particular
company. In some example embodiments, importing or otherwise
accessing data from one or more externally hosted data sources may
enhance profile data for both members and organizations. For
instance, with companies in particular, financial data may be
imported from one or more external data sources, and made part of a
company's profile. Additionally, one or more profile images (e.g.,
photos of the member) may be stored in the database 218.
[0039] Once registered, a member may invite other members, or be
invited by other members, to connect via the social networking
service. A "connection" may require or indicate a bi-lateral
agreement by the members, such that both members acknowledge the
establishment of the connection. Similarly, with some embodiments,
a member may elect to "follow" another member. In contrast to
establishing a connection, the concept of "following" another
member typically is a unilateral operation, and at least with some
embodiments, does not require acknowledgement or approval by the
member that is being followed. When one member follows another, the
member who is following may receive status updates (e.g., in an
activity or content stream) or other messages published by the
member being followed, or relating to various activities undertaken
by the member being followed. Similarly, when a member follows an
organization, the member becomes eligible to receive messages or
status updates published on behalf of the organization. For
instance, messages or status updates published on behalf of an
organization that a member is following will appear in the member's
personalized data feed, commonly referred to as an activity stream
or content stream. In any case, the various associations and
relationships that the members establish with other members, or
with other entities and objects, are stored and maintained within a
social graph, shown in FIG. 2 with database 220.
[0040] As members interact with the various applications, services,
and content made available via the social networking system 210,
the members' interactions and behavior (e.g., content viewed, links
or buttons selected, messages responded to, etc.) may be tracked
and information concerning the member's activities and behavior may
be logged or stored, for example, as indicated in FIG. 2 by the
database 222. This logged activity information may then be used by
the communication system 216. The members' interactions and
behavior may also be tracked, stored, and used by a pre-fetch
system 400 residing on a client device, such as within a browser of
the client device, as will be discussed in further detail
below.
[0041] In some embodiments, databases 218, 220, and 222 may be
incorporated into database(s) 126 in FIG. 1. However, other
configurations are also within the scope of the present
disclosure.
[0042] Although not shown, in some embodiments, the social
networking system 210 provides an application programming interface
(API) module via which applications and services can access various
data and services provided or maintained by the social networking
service. For example, using an API, an application may be able to
request and/or receive one or more navigation recommendations. Such
applications may be browser-based applications, or may be operating
system-specific. In particular, some applications may reside and
execute (at least partially) on one or more mobile devices (e.g.,
phone, or tablet computing devices) with a mobile operating system.
Furthermore, while in many cases the applications or services that
leverage the API may be applications and services that are
developed and maintained by the entity operating the social
networking service, other than data privacy concerns, nothing
prevents the API from being provided to the public or to certain
third-parties under special arrangements, thereby making the
navigation recommendations available to third party applications
and services.
[0043] Although the communication system 216 is referred to herein
as being used in the context of a social networking service, it is
contemplated that it may also be employed in the context of any
website or online services. Additionally, features of the present
disclosure can be used or presented in the context of a web page or
any other user interface view, including, but not limited to, a
user interface on a mobile device or on desktop software.
[0044] FIG. 3 is a block diagram illustrating a communication
system 216, in accordance with an example embodiment. In some
example embodiments, the communication system 216 comprises any
combination of one or more of an identification module 310, a
transmission module 220, and one or more databases 330. The modules
310 and 320 and the database(s) 330 can reside on a computer
system, or other machine, having a memory and at least one
processor (not shown). In some embodiments, the modules 310 and 320
and the database(s) 330 can be incorporated into the application
server(s) 118 in FIG. 1. In some example embodiments, the
database(s) 330 is incorporated into database(s) 126 in FIG. 1 and
can include any combination of one or more of databases 218, 220,
and 222 in FIG. 2. However, it is contemplated that other
configurations of the modules 310 and 320, as well as the
database(s) 330, are also within the scope of the present
disclosure.
[0045] In some example embodiments, one or more of the modules 310
and 320 is configured to provide a variety of user interface
functionality, such as generating user interfaces, interactively
presenting user interfaces to the user, receiving information from
the user (e.g., interactions with user interfaces), and so on.
Presenting information to the user can include causing presentation
of information to the user (e.g., communicating information to a
device with instructions to present the information to the user).
Information may be presented using a variety of means including
visually displaying information and using other device outputs
(e.g., audio, tactile, and so forth). Similarly, information may be
received via a variety of means including alphanumeric input or
other device input (e.g., one or more touch screen, camera, tactile
sensors, light sensors, infrared sensors, biometric sensors,
microphone, gyroscope, accelerometer, other sensors, and so forth).
In some example embodiments, one or more of the modules 310 and 320
is configured to receive user input. For example, one or more of
the modules 310 and 320 can present one or more GUI elements (e.g.,
drop-down menu, selectable buttons, text field) with which a user
can submit input.
[0046] In some example embodiments, one or more of the modules 310
and 320 is configured to perform various communication functions to
facilitate the functionality described herein, such as by
communicating with the social networking system 210 via the network
104 using a wired or wireless connection. Any combination of one or
more of the modules 310 and 320 may also provide various web
services or functions, such as retrieving information from the
third party servers 130 and the social networking system 210.
Information retrieved by the any of the modules 310 and 320 may
include profile data corresponding to users and members of the
social networking service of the social networking system 210.
[0047] Additionally, any combination of one or more of the modules
310 and 320 can provide various data functionality, such as
exchanging information with the database(s) 330. For example, any
of the modules 310 and 320 can access profile data, social graph
data, and member activity and behavior data from the databases 218,
220, and 222 in FIG. 2, as well as exchange information with third
party servers 130, client machines 110, 112, and other sources of
information.
[0048] In some example embodiments, the identification module 310
is configured to detect that an image has been captured by a camera
on a mobile device (e.g., smartphone, tablet computer) of a first
user. The image is captured by the camera at a particular point in
time (e.g., Jun. 2, 2018 at 6:52 pm), and the identification module
310 may associate the particular point in time with the captured
image, such as by storing the particular point in time in the
database(s) 330 in association with the captured image.
[0049] The captured image may be a group selfie that includes the
first user of the mobile device and at least one other user. In
some example embodiments, the identification module 310 is
configured to identify the other user(s) in the captured image in
response to, or otherwise based on, the detecting that the image
has been captured. For example, the identification module 310 may
compare images of users who could potentially be present in the
captured image, who may be referred to herein as candidate users,
with the captured image using one or more facial recognition
operations to match the faces of candidate users with the faces of
the other users in the captured image. In some example embodiments,
the identification module 310 uses profile images of users from a
social networking service for comparing with the captured image so
that the identity of the users can be determined by the profile
images. For example, the identification module 310 can determine
that a profile image belongs to John Smith based the profile image
being stored by the social networking service as a profile image
for John Smith, and then determine that John Smith is present in
the captured image based on a match between the profile image and
one of the faces in the captured image.
[0050] However, a technical problem arises in the massive number of
profile images that exist, which creates an extraordinarily large
search space with which to compare the captured image, resulting in
slow performance speed for identifying the users in the captured
image. The identification module 310 may solve this technical
problem by restricting the search space to include only candidate
users that are determined to have been located near (e.g., within a
particular distance of) the location where the image was captured
during the time the image was captured. For example, in some
example embodiments, the identification module 310 is configured to
determine a location of the mobile device used to capture the image
for the point in time at which the image was captured, and then
identify a plurality of candidate users based on a determination
that each one of the plurality of candidate users is or was located
near the determined location of the mobile device for that point in
time. The identification module 310 may determine the location of
the mobile device in a variety of ways, including, but not limited
to, using GPS data of the mobile device or using self-reported
positioning or check-in data of the user associated with the mobile
device.
[0051] In some example embodiments, the identification module 310
is configured to, for each one of the candidate users, access at
least one profile image of the candidate user from a corresponding
profile of the candidate user on a social networking service (e.g.,
from the database(s) 330 in FIG. 3 or the database 218 in FIG. 2),
and then compare the accessed profile image(s) of the candidate
user with the captured image. For example, the identification
module 310 may use one or more facial recognition operations to
determine if there is a match between the accessed profile image(s)
and any faces in the captured image. In some example embodiments,
the identification module 310 is configured to determine whether or
not a candidate user is present in the captured image based on the
comparison of the profile image(s) of the candidate user with the
captured image. For example, if the identification module 310
determines that there is a match between the profile image and the
captured image, then the identification module 310 determines that
the candidate user is present in the captured image. In this
respect, the identification module 310 may determine that a subset
of the candidate users (e.g., a portion of the candidate users less
than all of the candidate users) are present in the captured image
based on the comparison operation(s) performed by the
identification module 310. In some example embodiments, the
identification module 310 is configured to identify this subset of
the plurality of candidate users as the other user(s) in the
captured image.
[0052] In some example embodiments, the identification module 310
is also configured to determine whether or not the first user is
present in the captured image. For example, the identification
module 310 may determine the identity of the first user of the
mobile device, such as based on an IP address of the mobile device,
then locate a profile image of the identified first user, and
compare the profile image of the first user with the captured
image, similar to the comparison of the profile images of the
candidate users with the captured image. In some example
embodiments, the identification module 310 is configured to
condition its performance of the identifying the other user(s) in
the captured image upon a determination the captured image includes
the first user. By enforcing this requirement that the first user
be present in the captured image in order for the identifying of
the other user(s) to be performed, the identification module 310
may prevent the first user from simply taking pictures of strangers
in order to determine their identity, since the first user would be
forced to take a group selfie in order for the identification
module 310 to identify any other users. This feature helps protect
the privacy and security of other users.
[0053] In some example embodiments, the transmission module 320 is
configured to transmit a message to an electronic destination
associated with identified other user(s) based on the identifying
of the other user(s) in the captured image. Examples of electronic
destinations include, but are not limited to, e-mail addresses or
accounts, cell phone numbers or accounts, messaging application
addresses or accounts, and social networking addresses or accounts.
Other types of electronic destinations that can be associated with
users are also within the scope of the present disclosure.
[0054] In some example embodiments, the transmission module 320 is
configured to generate the message in response to the identifying
of the other user(s) in the captured image. In some example
embodiments, the generating the message comprises automatically
including the captured image in the message without receiving a
user instruction from the mobile device to include the captured
image in the message. For example, the first user does not need to
actively select the captured image for inclusion in the message.
Rather, the captured image would automatically be included in the
message simply by the first user taking the group selfie.
[0055] In some example embodiments, the transmission module 320 is
configured to, in generating the message, automatically address the
message to the electronic destination(s) of the identified other
user(s) without the first user specifying the electronic
destination. For example, the first user does not need to actively
select or enter any electronic destinations for the message.
Rather, electronic destination(s) would automatically be determined
and inserted into the destination field of the message based on the
identification of the other user(s) simply by the first user taking
the group selfie.
[0056] In some example embodiments, the identification module 310
is configured to provide a preview of the identified other user(s)
that will be included in the message for the first user to confirm
or correct. FIG. 4 illustrates a user interface 400 displaying a
captured image 410 and an indication 420 of candidate users
identified as being present in the captured image 410, in
accordance with an example embodiment. The captured image 410
includes the faces of users 412, which may include a first user
412-A to whom the mobile device used to capture the image 410
belongs, as well as other users 412-B, 412-C, and 412-D. The
preview of the captured image 410 may include corresponding
boundaries 414-A, 414-B, 414-C, and 414-D (e.g., boxes) around the
faces of the users 412 in the captured image 410, thereby revealing
which faces in the captured image 410 were used as the basis for
identifying the users present in the captured image 410. The
indication 420 may include a corresponding image and name of each
user 412 that is identified, as well as other information that can
be retrieved from the profile of the user 412, such as job title,
company, etc.
[0057] In some example embodiments, the user interface 400 is
configured to receive user input from the first user to confirm,
for each one of the candidate users in the subset of candidate
users (e.g., indicated by the indication 420), whether the
candidate user is present in the captured image 410. The user
interface 400 may display one or more selectable user interface
elements 422 that the user may select to provide input confirming
whether or not each candidate user indicated by the indication 420
should be included in the message based on the captured image 410.
In the example shown in FIG. 4, the identified candidate users
included in the indication 420 are automatically selected as being
present in the captured image, and are therefore to be
automatically included as recipients of the message to be generated
and transmitted based on the captured image 410. By de-selecting a
candidate user, such as via the corresponding selectable user
interface element 422, the candidate user may be removed from
inclusion as a recipient of the message to be generates and
transmitted based on the captured image 410.
[0058] Although the example shown in FIG. 4 only shows, via the
indication 420, a few other users being presented for possible
inclusion in a message, it is possible that the number of other
users can be large. Since the amount of display area available on
mobile devices is very limited, a technical problem arises in
effectively providing a preview of potential recipients of the
message. In some example embodiments, the transmission module 320
prioritizes the order in which the other users are presented in the
indication 420 based on their level of relevance to the first user.
For example, in some example embodiments, the transmission module
320 determines a corresponding level of relevance for each
candidate user in the subset of candidate users, and then ranks the
candidate users in the subset of candidate users based on their
corresponding levels of relevance. The indications 420 of the
candidate users in the subset of candidate users are then displayed
in the user interface 400 in an order based on the ranking, such as
the candidate user with the highest level of relevance being
displayed at the top, the candidate user the second highest level
of relevance being displayed immediately under the candidate user
with the highest level of relevance, and so on and so forth.
[0059] The level of relevance may be determined based on a variety
of factors, including, but not limited to, the level of connection
between the candidate user and the first user (e.g., users that are
directly connected with the first user have a higher level of
connection with, and thus a higher level of relevance to, the first
user than users that are indirectly connected to the first user
through other users), and the level of similarity between the
profile data of the candidate user and the profile data of the
first user (e.g., users that have similar jobs or interests as the
first user have a higher level of similarity, and thus relevance,
to the first user than users that do not have similar jobs or
interests as the first user). Other types of factors for
determining the level of relevance are also within the scope of the
present disclosure.
[0060] In some example embodiments, the identification module 310
is configured to determine that one or more additional users in the
captured image cannot be identified, and to display an indication
of the additional user(s). The determination that the additional
user(s) cannot be identified may be based on the identification
module 310 searching through a pool of images (e.g., profile images
accessed via a database of a social networking service) to find a
match with the specific face in the captured image that the
identification module 310 is attempting to identify, and the
identification module 310 not finding a match. In FIG. 4, the user
interface 400 displays an indication 450 of user 412-C, who cannot
be identified. The indication 450 comprises an image of the face of
user 412-C. Additionally, the user interface 400 may also be
configured to receive an identification of the additional user(s)
from the first user via one or more user interface elements. For
example, the user interface 400 may provide a text box 452 in which
the first user may enter the name of the additional user, and then
select a selectable user interface element 454 to cause the
identification module 310 to search a database of users to find the
identification of the additional user using the entered name. For
example, the identification module 310 may perform a search of
profiles on a social networking service to find a profile with a
name that matches the entered name, and then identify the
additional user using the matched profile. In some example
embodiments, the user interface 400 may also provide a selectable
user interface element (not shown) that the first user can select
in order to browse a list of users (e.g., a list of members of a
social networking service) from which the first user can select a
user to be identified as the additional user. The first user can
select, via a selectable user interface element, to include the
identified additional user as a recipient of the message.
[0061] Additionally, the user interface 400 may provide user
interface elements (not shown) that enable the first user to
correct the identification of the other user(s) indicated in the
indication 420, such as by enabling the first user to enter the
correct identity of the other user(s) or to browse and select the
correct identity of the other user(s).
[0062] In some example embodiments, the identification module 310
is configured to compare the profile image(s) of the candidate
users with the captured image based on a facial recognition model.
The identification module 310 may learn from the user input
correcting the identity of another user and from the user input
identifying another user that originally could not be identified by
the identification module 310 in order to modify the facial
recognition model using machine learning. For example, in some
example embodiments, the identification module 310 is configured to
modify the facial recognition model using one or more machine
learning operations based on the captured image 410 and the
identification of any additional users not originally identified
and/or the corrected identification of any other users that were
originally identified.
[0063] In some example embodiments, the user interface 400 provides
one or more user interface elements configured to enable the first
user to enter text to be included in the message to the other
users. For example, the user interface 400 may display a text box
in which the first user may enter text 430. Once the first user has
confirmed the identification of the other users to be included as
recipients of the message and the first user has entered any text
to be included in the message, the first user can select a
selectable user interface element 440 that is configured to
generate and transmit the message based on the identified other
user(s), the captured image, and any text entered by the user to be
included in the message.
[0064] In some example embodiments, the transmission of the
generated message creates a conversation between the first user and
any other user(s) included as recipients of the message. FIG. 5
illustrates a user interface 500 displaying a conversation 510
started based on a transmission of a message 520 generated based on
the captured image 410, in accordance with an example embodiment.
In one example, since the other user 412-C was not identified in
FIG. 4, the message was not transmitted to any electronic
destination associated with the other user 412-C, and the other
user 412-C is therefore not included as part of the conversation
510. The message 520 includes the captured image 410 and any text
430 entered by the first user to be included in the message 520. In
some example embodiments, the user interface 500 displays one or
more user interface elements, such as a text box 530 and a
selectable "SEND" button, configured to enable the recipient of the
message and participants of the conversation to reply to the
message 520 and add to the conversation 510.
[0065] FIG. 6 is a flowchart illustrating a method 600 of starting
a communication based on a captured image, in accordance with an
example embodiment. The method 600 can be performed by processing
logic that can comprise hardware (e.g., circuitry, dedicated logic,
programmable logic, microcode, etc.), software (e.g., instructions
run on a processing device), or a combination thereof. In one
implementation, the method 600 is performed by the communication
system 216 of FIGS. 2-3, as described above.
[0066] At operation 610, the communication system 216 detects that
an image has been captured by a camera on a first mobile device of
a first user. In some example embodiments, the captured image has
been captured by the camera at a particular point in time. The
communication system 216 may detect that the image has been
captured by the camera in response to, or otherwise based on, the
image having been captured by the camera.
[0067] At operation 620, the communication system 216, in response
to detecting that the image has been captured, identifies at least
one other user in the captured image. The communication system 216
may compare images of candidate users who could potentially be
present in the captured image with the captured image using one or
more facial recognition operations to match the faces of candidate
users with the faces of the users in the captured image. In some
example embodiments, the communication system 216 uses profile
images of users from a social networking service for comparing with
the captured image so that the identity of the users can be
determined by the profile images. In some example embodiments, the
performance of the identifying the other user(s) in the captured
image is conditioned upon a determination that the captured image
includes the first user.
[0068] At operation 630, the communication system 216 transmits a
message to an electronic destination associated with the other
user(s) based on the identifying of the other user(s) in the
captured image. In some example embodiments, operation 630
comprises generating the message in response to, or otherwise based
on, the determination that other users are present in the captured
image. In some example embodiments, the generating of the message
comprises automatically including the captured image in the message
without receiving a user instruction from the first mobile device
to include the captured image in the message. In some example
embodiments, the generating of the message comprises automatically
addressing the message to the electronic destination(s) of the
other user(s) without the first user specifying the electronic
destination.
[0069] It is contemplated that any of the other features described
within the present disclosure can be incorporated into the method
600.
[0070] FIG. 7 is a flowchart illustrating a method 700 of
identifying users in a captured image, in accordance with an
example embodiment. The method 700 can be performed by processing
logic that can comprise hardware (e.g., circuitry, dedicated logic,
programmable logic, microcode, etc.), software (e.g., instructions
run on a processing device), or a combination thereof. In one
implementation, the method 700 is performed by the communication
system 216 of FIGS. 2-3, as described above.
[0071] At operation 710, the communication system 216 determines a
location of the first mobile device for the particular point in
time at which the image was captured by the camera on the mobile
device of the first user. The communication system 216 may
determine the location of the first mobile device in a variety of
ways, including, but not limited to, using GPS data of the mobile
device or using self-reported positioning or check-in data of the
user associated with the mobile device.
[0072] At operation 720, the communication system 216 identifies a
plurality of candidate users based on a determination that the
plurality of candidate users are located near the determined
location of the first mobile device for the particular point in
time. The location of the candidate users may be determined in a
variety of ways, including, but not limited to, using GPS data of
their corresponding mobile devices or using self-reported
positioning or check-in data of the candidate users.
[0073] At operation 730, the communication system 216, for each one
of the candidate users identified at operation 720, accesses at
least one profile image of the candidate user from a corresponding
profile of the candidate user on a social networking service. At
operation 740, the communication system 216, for each one of the
candidate users, compares the profile image(s) of the candidate
user with the captured image. At operation 750, the communication
system 216 determines that a subset of the candidate users are
present in the captured image based on the comparison of the
profile image(s) with the captured image, with the subset of the
candidate users being identified as the other user(s) in the
captured image.
[0074] It is contemplated that any of the other features described
within the present disclosure can be incorporated into the method
700.
[0075] FIG. 8 is a flowchart illustrating another method 800 of
identifying users in a captured image, in accordance with an
example embodiment. The method 800 can be performed by processing
logic that can comprise hardware (e.g., circuitry, dedicated logic,
programmable logic, microcode, etc.), software (e.g., instructions
run on a processing device), or a combination thereof. In one
implementation, the method 800 is performed by the communication
system 216 of FIGS. 2-3, as described above.
[0076] At operation 810, the communication system 216 causes a user
interface to be displayed on the first mobile device. In some
example embodiments, the user interface displays an indication of
each candidate user in the subset of candidate users, and the user
interface is configured to receive user input from the first user
to confirm, for each one of the candidate users in the subset of
candidate users, whether the candidate user is present in the
captured image.
[0077] At operation 820, the communication system 216 receives,
from the first mobile device, user input confirming that the subset
of candidate users are present in the captured image. In some
example embodiments, the determination that the subset of the
candidate users are present in the captured image, at operation 750
in FIG. 7, is further based on user input confirming that the
subset of candidate users are present in the captured image.
[0078] It is contemplated that any of the other features described
within the present disclosure can be incorporated into the method
800.
[0079] FIG. 9 is a flowchart illustrating yet another method 900 of
identifying users in a captured image, in accordance with an
example embodiment. The method 900 can be performed by processing
logic that can comprise hardware (e.g., circuitry, dedicated logic,
programmable logic, microcode, etc.), software (e.g., instructions
run on a processing device), or a combination thereof. In one
implementation, the method 900 is performed by the communication
system 216 of FIGS. 2-3, as described above.
[0080] In some example embodiments, the method 900 comprises
operations 910 and 920 preceding operation 810 of FIG. 8. At
operation 910, the communication system 216 determines a
corresponding level of relevance for each candidate user in the
subset of candidate users. The level of relevance may be determined
based on a variety of factors, including, but not limited to, the
level of connection between the candidate user and the first user
(e.g., users that are directly connected with the first user have a
higher level of connection with, and thus a higher level of
relevance to, the first user than users that are indirectly
connected to the first user through other users), and the level of
similarity between the profile data of the candidate user and the
profile data of the first user (e.g., users that have similar jobs
or interests as the first user have a higher level of similarity,
and thus relevance, to the first user than users that do not have
similar jobs or interests as the first user). Other types of
factors for determining the level of relevance are also within the
scope of the present disclosure.
[0081] At operation 920, the communication system 216 ranks the
candidate users in the subset of candidate users based on their
corresponding levels of relevance. For example, the candidate users
having the highest level of relevance may be given the highest
priority in the ranking. At operation 810, the indications of the
candidate users in the subset of candidate users are displayed in
an order based on the ranking.
[0082] It is contemplated that any of the other features described
within the present disclosure can be incorporated into the method
900.
[0083] FIG. 10 is a flowchart illustrating yet another method 1000
of identifying users in a captured image, in accordance with an
example embodiment. The method 1000 can be performed by processing
logic that can comprise hardware (e.g., circuitry, dedicated logic,
programmable logic, microcode, etc.), software (e.g., instructions
run on a processing device), or a combination thereof. In one
implementation, the method 1000 is performed by the communication
system 216 of FIGS. 2-3, as described above.
[0084] In some example embodiments, the method 100 comprises
operations 1010, 1020, and 1030 following operation 620 of FIG. 6
and preceding operation 630 of FIG. 6. At operation 1010, the
communication system 216 determines that an additional user in the
captured image cannot be identified in the identifying operation
620. The determination that the additional user(s) cannot be
identified may be based on the communication system 216 searching
through a pool of images (e.g., profile images accessed via a
database of a social networking service) to find a match with the
specific face in the captured image that the communication system
216 is attempting to identify, and the communication system 216 not
finding a match.
[0085] At operation 1020, the communication system 216 causes a
user interface to be displayed on the first mobile device. In some
example embodiments, the user interface displays an indication of
the additional user in the captured image, and the user interface
is configured to receive an identification of the additional user
from the first user. For example, the user interface may provide a
text box in which the first user may enter the name of the
additional user, and then select a selectable user interface
element to cause the communication system 216 to search a database
of users to find the identification of the additional user using
the entered name. For example, the communication system 216 may
perform a search of profiles on a social networking service to find
a profile with a name that matches the entered name, and then
identify the additional user using the matched profile. In some
example embodiments, the user interface may also provide a
selectable user interface element that the first user can select in
order to browse a list of users (e.g., a list of members of a
social networking service) from which the first user can select a
user to be identified as the additional user. The first user can
select, via a selectable user interface element, to include the
identified additional user as a recipient of the message.
[0086] At operation 1030, the communication system 216 receives the
identification of the additional user from the first mobile device.
At operation 630, the message is transmitted to an electronic
destination associated with the additional user based on the
identification of the additional user at operation 1030.
[0087] It is contemplated that any of the other features described
within the present disclosure can be incorporated into the method
1000.
Example Mobile Device
[0088] FIG. 11 is a block diagram illustrating a mobile device
1100, according to an example embodiment. The mobile device 1100
can include a processor 1102. The processor 1102 can be any of a
variety of different types of commercially available processors
suitable for mobile devices 1100 (for example, an XScale
architecture microprocessor, a Microprocessor without Interlocked
Pipeline Stages (MIPS) architecture processor, or another type of
processor). A memory 1104, such as a random access memory (RAM), a
Flash memory, or other type of memory, is typically accessible to
the processor 1102. The memory 1104 can be adapted to store an
operating system (OS) 1106, as well as application programs 1108,
such as a mobile location-enabled application that can provide
location-based services (LBSs) to a user. The processor 1102 can be
coupled, either directly or via appropriate intermediary hardware,
to a display 1110 and to one or more input/output (I/O) devices
1112, such as a keypad, a touch panel sensor, a microphone, and the
like. Similarly, in some embodiments, the processor 1102 can be
coupled to a transceiver 1114 that interfaces with an antenna 1116.
The transceiver 1114 can be configured to both transmit and receive
cellular network signals, wireless data signals, or other types of
signals via the antenna 1116, depending on the nature of the mobile
device 1100. Further, in some configurations, a GPS receiver 1118
can also make use of the antenna 1116 to receive GPS signals.
Modules, Components and Logic
[0089] Certain embodiments are described herein as including logic
or a number of components, modules, or mechanisms. Modules may
constitute either software modules (e.g., code embodied (1) on a
non-transitory machine-readable medium or (2) in a transmission
signal) or hardware-implemented modules. A hardware-implemented
module is tangible unit capable of performing certain operations
and may be configured or arranged in a certain manner. In example
embodiments, one or more computer systems (e.g., a standalone,
client or server computer system) or one or more processors may be
configured by software (e.g., an application or application
portion) as a hardware-implemented module that operates to perform
certain operations as described herein.
[0090] In various embodiments, a hardware-implemented module may be
implemented mechanically or electronically. For example, a
hardware-implemented module may comprise dedicated circuitry or
logic that is permanently configured (e.g., as a special-purpose
processor, such as a field programmable gate array (FPGA) or an
application-specific integrated circuit (ASIC)) to perform certain
operations. A hardware-implemented module may also comprise
programmable logic or circuitry (e.g., as encompassed within a
general-purpose processor or other programmable processor) that is
temporarily configured by software to perform certain operations.
It will be appreciated that the decision to implement a
hardware-implemented module mechanically, in dedicated and
permanently configured circuitry, or in temporarily configured
circuitry (e.g., configured by software) may be driven by cost and
time considerations.
[0091] Accordingly, the term "hardware-implemented module" should
be understood to encompass a tangible entity, be that an entity
that is physically constructed, permanently configured (e.g.,
hardwired) or temporarily or transitorily configured (e.g.,
programmed) to operate in a certain manner and/or to perform
certain operations described herein. Considering embodiments in
which hardware-implemented modules are temporarily configured
(e.g., programmed), each of the hardware-implemented modules need
not be configured or instantiated at any one instance in time. For
example, where the hardware-implemented modules comprise a
general-purpose processor configured using software, the
general-purpose processor may be configured as respective different
hardware-implemented modules at different times. Software may
accordingly configure a processor, for example, to constitute a
particular hardware-implemented module at one instance of time and
to constitute a different hardware-implemented module at a
different instance of time.
[0092] Hardware-implemented modules can provide information to, and
receive information from, other hardware-implemented modules.
Accordingly, the described hardware-implemented modules may be
regarded as being communicatively coupled. Where multiple of such
hardware-implemented modules exist contemporaneously,
communications may be achieved through signal transmission (e.g.,
over appropriate circuits and buses) that connect the
hardware-implemented modules. In embodiments in which multiple
hardware-implemented modules are configured or instantiated at
different times, communications between such hardware-implemented
modules may be achieved, for example, through the storage and
retrieval of information in memory structures to which the multiple
hardware-implemented modules have access. For example, one
hardware-implemented module may perform an operation, and store the
output of that operation in a memory device to which it is
communicatively coupled. A further hardware-implemented module may
then, at a later time, access the memory device to retrieve and
process the stored output. Hardware-implemented modules may also
initiate communications with input or output devices, and can
operate on a resource (e.g., a collection of information).
[0093] The various operations of example methods described herein
may be performed, at least partially, by one or more processors
that are temporarily configured (e.g., by software) or permanently
configured to perform the relevant operations. Whether temporarily
or permanently configured, such processors may constitute
processor-implemented modules that operate to perform one or more
operations or functions. The modules referred to herein may, in
some example embodiments, comprise processor-implemented
modules.
[0094] Similarly, the methods described herein may be at least
partially processor-implemented. For example, at least some of the
operations of a method may be performed by one or more processors
or processor-implemented modules. The performance of certain of the
operations may be distributed among the one or more processors, not
only residing within a single machine, but deployed across a number
of machines. In some example embodiments, the processor or
processors may be located in a single location (e.g., within a home
environment, an office environment or as a server farm), while in
other embodiments the processors may be distributed across a number
of locations.
[0095] The one or more processors may also operate to support
performance of the relevant operations in a "cloud computing"
environment or as a "software as a service" (SaaS). For example, at
least some of the operations may be performed by a group of
computers (as examples of machines including processors), these
operations being accessible via a network (e.g., the Internet) and
via one or more appropriate interfaces (e.g., Application Program
Interfaces (APIs).)
Electronic Apparatus and System
[0096] Example embodiments may be implemented in digital electronic
circuitry, or in computer hardware, firmware, software, or in
combinations of them. Example embodiments may be implemented using
a computer program product, e.g., a computer program tangibly
embodied in an information carrier, e.g., in a machine-readable
medium for execution by, or to control the operation of, data
processing apparatus, e.g., a programmable processor, a computer,
or multiple computers.
[0097] A computer program can be written in any form of programming
language, including compiled or interpreted languages, and it can
be deployed in any form, including as a stand-alone program or as a
module, subroutine, or other unit suitable for use in a computing
environment. A computer program can be deployed to be executed on
one computer or on multiple computers at one site or distributed
across multiple sites and interconnected by a communication
network.
[0098] In example embodiments, operations may be performed by one
or more programmable processors executing a computer program to
perform functions by operating on input data and generating output.
Method operations can also be performed by, and apparatus of
example embodiments may be implemented as, special purpose logic
circuitry, e.g., a field programmable gate array (FPGA) or an
application-specific integrated circuit (ASIC).
[0099] The computing system can include clients and servers. A
client and server are generally remote from each other and
typically interact through a communication network. The
relationship of client and server arises by virtue of computer
programs running on the respective computers and having a
client-server relationship to each other. In embodiments deploying
a programmable computing system, it will be appreciated that both
hardware and software architectures merit consideration.
Specifically, it will be appreciated that the choice of whether to
implement certain functionality in permanently configured hardware
(e.g., an ASIC), in temporarily configured hardware (e.g., a
combination of software and a programmable processor), or a
combination of permanently and temporarily configured hardware may
be a design choice. Below are set out hardware (e.g., machine) and
software architectures that may be deployed, in various example
embodiments.
Example Machine Architecture and Machine-Readable Medium
[0100] FIG. 12 is a block diagram of an example computer system
1200 on which methodologies described herein may be executed, in
accordance with an example embodiment. In alternative embodiments,
the machine operates as a standalone device or may be connected
(e.g., networked) to other machines. In a networked deployment, the
machine may operate in the capacity of a server or a client machine
in server-client network environment, or as a peer machine in a
peer-to-peer (or distributed) network environment. The machine may
be a personal computer (PC), a tablet PC, a set-top box (STB), a
Personal Digital Assistant (PDA), a cellular telephone, a web
appliance, a network router, switch or bridge, or any machine
capable of executing instructions (sequential or otherwise) that
specify actions to be taken by that machine. Further, while only a
single machine is illustrated, the term "machine" shall also be
taken to include any collection of machines that individually or
jointly execute a set (or multiple sets) of instructions to perform
any one or more of the methodologies discussed herein.
[0101] The example computer system 1200 includes a processor 1202
(e.g., a central processing unit (CPU), a graphics processing unit
(GPU) or both), a main memory 1204 and a static memory 1206, which
communicate with each other via a bus 1208. The computer system
1200 may further include a graphics display unit 1210 (e.g., a
liquid crystal display (LCD) or a cathode ray tube (CRT)). The
computer system 1200 also includes an alphanumeric input device
1212 (e.g., a keyboard or a touch-sensitive display screen), a user
interface (UI) navigation device 1214 (e.g., a mouse), a storage
unit 1216, a signal generation device 1218 (e.g., a speaker) and a
network interface device 1220.
Machine-Readable Medium
[0102] The storage unit 1216 includes a machine-readable medium
1222 on which is stored one or more sets of instructions and data
structures (e.g., software) 1224 embodying or utilized by any one
or more of the methodologies or functions described herein. The
instructions 1224 may also reside, completely or at least
partially, within the main memory 1204 and/or within the processor
1202 during execution thereof by the computer system 1200, the main
memory 1204 and the processor 1202 also constituting
machine-readable media.
[0103] While the machine-readable medium 1222 is shown in an
example embodiment to be a single medium, the term
"machine-readable medium" may include a single medium or multiple
media (e.g., a centralized or distributed database, and/or
associated caches and servers) that store the one or more
instructions 1224 or data structures. The term "machine-readable
medium" shall also be taken to include any tangible medium that is
capable of storing, encoding or carrying instructions (e.g.,
instructions 1224) for execution by the machine and that cause the
machine to perform any one or more of the methodologies of the
present disclosure, or that is capable of storing, encoding or
carrying data structures utilized by or associated with such
instructions. The term "machine-readable medium" shall accordingly
be taken to include, but not be limited to, solid-state memories,
and optical and magnetic media. Specific examples of
machine-readable media include non-volatile memory, including by
way of example semiconductor memory devices, e.g., Erasable
Programmable Read-Only Memory (EPROM), Electrically Erasable
Programmable Read-Only Memory (EEPROM), and flash memory devices;
magnetic disks such as internal hard disks and removable disks;
magneto-optical disks; and CD-ROM and DVD-ROM disks.
Transmission Medium
[0104] The instructions 1224 may further be transmitted or received
over a communications network 1226 using a transmission medium. The
instructions 1224 may be transmitted using the network interface
device 1220 and any one of a number of well-known transfer
protocols (e.g., HTTP). Examples of communication networks include
a local area network ("LAN"), a wide area network ("WAN"), the
Internet, mobile telephone networks, Plain Old Telephone Service
(POTS) networks, and wireless data networks (e.g., WiFi and WiMax
networks). The term "transmission medium" shall be taken to include
any intangible medium that is capable of storing, encoding or
carrying instructions for execution by the machine, and includes
digital or analog communications signals or other intangible media
to facilitate communication of such software.
[0105] Although an embodiment has been described with reference to
specific example embodiments, it will be evident that various
modifications and changes may be made to these embodiments without
departing from the broader spirit and scope of the present
disclosure. Accordingly, the specification and drawings are to be
regarded in an illustrative rather than a restrictive sense. The
accompanying drawings that form a part hereof, show by way of
illustration, and not of limitation, specific embodiments in which
the subject matter may be practiced. The embodiments illustrated
are described in sufficient detail to enable those skilled in the
art to practice the teachings disclosed herein. Other embodiments
may be utilized and derived therefrom, such that structural and
logical substitutions and changes may be made without departing
from the scope of this disclosure. This Detailed Description,
therefore, is not to be taken in a limiting sense, and the scope of
various embodiments is defined only by the appended claims, along
with the full range of equivalents to which such claims are
entitled. Although specific embodiments have been illustrated and
described herein, it should be appreciated that any arrangement
calculated to achieve the same purpose may be substituted for the
specific embodiments shown. This disclosure is intended to cover
any and all adaptations or variations of various embodiments.
Combinations of the above embodiments, and other embodiments not
specifically described herein, will be apparent to those of skill
in the art upon reviewing the above description.
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