U.S. patent application number 16/736269 was filed with the patent office on 2020-05-07 for digital rights management using a digital agent.
This patent application is currently assigned to AT&T INTELLECTUAL PROPERTY I, L.P.. The applicant listed for this patent is AT&T INTELLECTUAL PROPERTY I, L.P. AT&T MOBILITY II LLC. Invention is credited to Ginger Chien, Adrianne Binh Luu, Leonid Razoumov, Nemmara K. Shankaranarayanan, Dana Tardelli.
Application Number | 20200143012 16/736269 |
Document ID | / |
Family ID | 48655536 |
Filed Date | 2020-05-07 |
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United States Patent
Application |
20200143012 |
Kind Code |
A1 |
Tardelli; Dana ; et
al. |
May 7, 2020 |
DIGITAL RIGHTS MANAGEMENT USING A DIGITAL AGENT
Abstract
A method for digital rights management includes a digital agent
for contacting a media host. Media content is compared to a user
profile and an identification confidence level is assigned to the
media based on the comparison. A digital agent contacts a host of
the media based on the identification confidence level, the type of
media, and the context of the media. The digital agent requests one
or more actions of a media host based on user designations
concerning information related to the media. The identification
confidence level is generated based on a plurality of user
characteristic confidence levels which are generated based on media
being analyzed.
Inventors: |
Tardelli; Dana; (Atlanta,
GA) ; Chien; Ginger; (Bellevue, WA) ; Luu;
Adrianne Binh; (Roswell, GA) ; Razoumov; Leonid;
(Riverdale, NY) ; Shankaranarayanan; Nemmara K.;
(Bridgewater, NJ) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
AT&T INTELLECTUAL PROPERTY I, L.P.
AT&T MOBILITY II LLC |
Atlanta
Atlanta |
GA
GA |
US
US |
|
|
Assignee: |
AT&T INTELLECTUAL PROPERTY I,
L.P.
Atlanta
GA
AT&T MOBILITY II LLC
Atlanta
GA
|
Family ID: |
48655536 |
Appl. No.: |
16/736269 |
Filed: |
January 7, 2020 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
14794334 |
Jul 8, 2015 |
10565353 |
|
|
16736269 |
|
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|
|
13333132 |
Dec 21, 2011 |
9135410 |
|
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14794334 |
|
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06N 20/00 20190101;
G06F 21/10 20130101; G06N 99/00 20130101 |
International
Class: |
G06F 21/10 20060101
G06F021/10; G06N 20/00 20060101 G06N020/00 |
Claims
1. A method of operating a media server, the method comprising:
receiving seed media associated with a user, the seed media
comprising images of the user; generating a plurality of
characteristics of the user based on the seed media; generating a
profile of the user based on the plurality of characteristics;
scanning a network to identify media content related to the
profile; generating an identification confidence level based on the
media content related to the profile; and contacting an entity
based on the identification confidence level.
2. The method of claim 1, wherein the seed media further comprises
video of the user.
3. The method of claim 2, wherein the plurality of characteristics
further comprise at least one of a gait of the user, a gesture of
the user, or a body shape of the user.
4. The method of claim 3, wherein the plurality of characteristics
further comprise clothing worn by the user.
5. The method of claim 3, wherein the plurality of characteristics
further comprise at least one of a location of the user on a
specific date, people with which the user is associated, or
relationships of the user.
6. The method of claim 1, further comprising: updating the profile
of the user using the media content to generate an updated profile
of the user, the updating based on the identification confidence
level.
7. The method of claim 6, further comprising: scanning the network
to identify media content related to the updated profile of the
user; generating a second identification confidence level based on
the media content related to the updated profile of the user; and
contacting the entity based on a value of the second identification
confidence level.
8. The method of claim 1, wherein the generating the identification
confidence level comprises comparing the media content to each of
the plurality of characteristics of the profile.
9. The method of claim 1, wherein the contacting the entity is in
response to the identification confidence level being equal to or
greater than a threshold.
10. An apparatus comprising: a processor; and a memory that stores
executable instructions that, when executed by the processor,
facilitate performance of operations, comprising: receiving seed
media associated with a user, the seed media comprising images of
the user; generating a plurality of characteristics of the user
based on the seed media; generating a profile of the user based on
the plurality of characteristics; scanning a network to identify
media content related to the profile; generating an identification
confidence level based on the media content related to the profile;
and contacting an entity based on the identification confidence
level.
11. The apparatus of claim 10, wherein the seed media further
comprises video of the user.
12. The apparatus of claim 11, wherein the plurality of
characteristics further comprise at least one of a gait of the
user, a gesture of the user, or a body shape of the user.
13. The apparatus of claim 12, wherein the plurality of
characteristics further comprise clothing worn by the user.
14. The apparatus of claim 12, wherein the plurality of
characteristics further comprise at least one of a location of the
user on a specific date, people with which the user is associated,
or relationships of the user.
15. The apparatus of claim 10, the operations further comprising:
updating the profile of the user using the media content to
generate an updated profile of the user, the updating based on the
identification confidence level.
16. A machine-readable storage medium, comprising executable
instructions that, when executed by a processor, facilitate
performance of operations, comprising: receiving seed media
associated with a user, the seed media comprising images of the
user; generating a plurality of characteristics of the user based
on the seed media; generating a profile of the user based on the
plurality of characteristics; scanning a network to identify media
content related to the profile; generating an identification
confidence level based on the media content related to the profile;
and contacting an entity based on the identification confidence
level.
17. The machine-readable storage medium of claim 16, wherein the
seed media further comprises video of the user.
18. The machine-readable storage medium of claim 17, wherein the
plurality of characteristics further comprise at least one of a
gait of the user, a gesture of the user, or a body shape of the
user.
19. The machine-readable storage medium of claim 18, wherein the
plurality of characteristics further comprise clothing worn by the
user.
20. The machine-readable storage medium of claim 18, wherein the
plurality of characteristics further comprise at least one of a
location of the user on a specific date, people with which the user
is associated, or relationships of the user.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a Continuation of prior U.S. Utility
patent application Ser. No. 14/794,334, filed Jul. 8, 2015, which
is a Continuation of U.S. Utility patent application Ser. No.
13/333,132, filed Dec. 21, 2011, and issued on Sep. 15, 2015, as
U.S. Pat. No. 9,135,410, all are herein incorporated by reference
in their entirety.
FIELD OF THE DISCLOSURE
[0002] The present disclosure relates generally to image analysis,
person recognition, and ownership identification, and more
particularly to digital rights management using a digital
agent.
BACKGROUND
[0003] The Internet allows anyone to publish media such as images
and documents soon after generation or creation. Media such as
images may be posted without identification of the people depicted
in the images. In addition, media posted online may be copied by
others and used without attributing the media to the author of the
media. Further, media depicting a particular person may be posted
by another in a malicious manner. Media may also be plagiarized or
altered. Users who want to make sure that any images depicting them
are used in a non-malicious manner or properly identify the user
must spend a significant amount of time searching networks (such as
the internet) to find these images. Similarly, a user who wants to
determine if their work has been plagiarized must spend a
significant amount of time searching networks. After an image is
found or plagiarism of a user's work has been determined, the user
must contact the host of the media in order to request certain
corrective actions be taken. This combination of searching and
requesting correction adds to an even greater amount of time
required by a user.
SUMMARY
[0004] The present disclosure provides a method and apparatus for
digital rights management using a digital agent.
[0005] In one embodiment, a method for digital rights management
includes comparing media content to a user profile. An
identification confidence level is assigned to the media based on
the comparing. A host of the media is contacted based on the
identification confidence level. The comparing media content to a
user profile, in one embodiment, comprises comparing the media
content to a plurality of user characteristics, determining a
characteristic confidence level for each of the plurality of
characteristics, and assigning an identification confidence level
based on the characteristic confidence levels. A user profile is
generated based on received seed media describing a user wherein a
plurality of user characteristics are generated based on the seed
media. A host providing media may be contacted based on media type
and/or media content. A host can be contacted via email which can
contain one of a request to license the media, a request to
identify a user depicted in the media, and a request to remove the
media from display.
[0006] These and other advantages of the inventive concept will be
apparent to those of ordinary skill in the art by reference to the
following detailed description and the accompanying drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
[0007] FIG. 1 depicts a system for managing digital rights using a
digital agent;
[0008] FIG. 2 depicts a flow chart for identifying media related to
a user and contacting a host providing the media;
[0009] FIG. 3 depicts a flow chart for generating a user profile
based on seed media;
[0010] FIG. 4 depicts a table storing user profiles;
[0011] FIG. 5 depicts a flow chart for determining an
identification confidence level based on a plurality of
characteristics;
[0012] FIG. 6 depicts a table storing media and related
information;
[0013] FIG. 7 depicts a table storing licensing information related
to media; and
[0014] FIG. 8 depicts a high-level block diagram of computer which
can be used for implementing a media server, digital agent, and
user devices.
DETAILED DESCRIPTION
[0015] FIG. 1 depicts a system for personal digital rights
management using a digital agent. Media server 102 is a computing
device for receiving, analyzing, identifying, categorizing, and
transmitting media. Media server 102, in one embodiment, is a
computer. Media server 102 is connected to network 104 which can be
a wireline or wireless network, local area network or wide area
network (e.g., the internet) or combination of such networks. User
device 106 is in communication with media server 102 via network
104. User device 106 is, in one embodiment, a handheld computing
device such as a smart phone. In other embodiments, user device 106
can be other computing devices such as a desktop computer, laptop
computer, cell phone, personal digital assistant, etc. Additional
user devices 108,110 are also in communication with media server
102 as well as with each other and user device 106 via network
104.
[0016] Media server 102 is in communication with media database 112
which stores various media such as images, videos, documents,
audio, web/digital contents (e.g., RSS feeds, blogs, emails),
etc.
[0017] Media server 102 is also in communication with user profile
database 114 which stores information related to a user's profile
which is derived as described below. Media server 102 is also in
communication with license database 116 which stores information
related to licensing and related agreements pertaining to a user's
media.
[0018] The system of FIG. 1 operates to aid a user in digital
rights management using a digital agent. Before the digital agent
searches for media on a network, a user profile is generated. The
user profile stores user characteristics such as facial dimensions
for use with facial recognition, body dimensions, a voice profile
for use with voice recognition, the user's location at different
times, etc. The user characteristics are used to identify the user
depicted in media found while searching a network. Seed media is
used to initialize the user profile. Seed media is media provided
by a user that is known to describe the user. For example, seed
media provided by a user can include one or more images or videos
of the user. After the user profile is generated, the digital agent
scours networks to find media which depicts the user by comparing
characteristics of media found on the networks to characteristics
stored in the user profile.
[0019] Since exact identification of a user in media, such as an
image, is not always possible, an identification confidence level
is assigned to media determined to possibly depict the user. This
identification confidence level is based on one or more
characteristic confidence levels each of which indicate how closely
user characteristics depicted in media found on a network match
user characteristics stored in the user profile. For example, a
user's face depicted in an image may be identified as a match with
a certain characteristic confidence level. A user's location
depicted in an image may be identified as a match with another
characteristic confidence level. The two characteristic confidence
levels are used to determine the identification confidence level.
The digital agent may contact a host providing media related to a
particular user based on user defined criteria such as the type of
media provided by the host and the identification confidence level
associated with the media. For example, the digital agent may email
the host and request that the host accept the terms of a licensing
agreement in order to continue providing the media. It should be
noted that although media is described above as including images
and video, media can also include audio, text, digital renderings,
etc. In general, any type of media that a user wants to protect or
enforce their rights over can be analyzed. Further, it should be
noted that although a user profile is initially generated using
seed media, media subsequently analyzed can be used to update
and/or modify a user profile.
[0020] Media server 102 is configured to operate digital agent 118.
Digital agent 118 scans network 104 for media and determines media
that may be related to a particular user. Digital agent 118 is an
emissary of a user and acts on the user's behalf, in this example,
managing the digital security and rights of the user. Media server
102, in one embodiment, is configured to contact entities hosting
media that is related to a particular user.
[0021] FIG. 2 depicts method 200 for managing digital rights using
a digital agent. At step 202 media is acquired for analysis. In one
embodiment, media server 102 acquires media from network 104. The
acquired media can be any type of media such as an image, video,
document, etc. At step 204 the content of the acquired media is
compared to a user profile. For example, an image acquired from
network 104 can be compared to a user profile stored in user
profile database 114 which includes data pertaining to
identification of a user, such as data required to perform facial
recognition of a user. An identification confidence level is
assigned to the acquired media, in one embodiment, based on the
comparison of the content of the acquired media to the user
profile. The confidence level indicates the level of accuracy of
the identification and, in one embodiment, can be a value from 0 to
100 with a higher value indicating a higher level of confidence.
For example, if the acquired media is an image, a user may be
identified in the image with a certain level of confidence
depending on facial recognition and other factors (discussed in
detail below).
[0022] At step 208, a host of the acquired media is contacted based
on the identification confidence level. For example, a user may
configure digital agent 118 to contact hosts providing media if the
media is determined to depict a user with an identification
confidence level of a specific value or greater (e.g., if
identification confidence level is 85 or greater, then host is
contacted.) The substance of the contact with the host depends on
user defined factors such as the identification of media related to
the user, the type of media, the identification confidence level,
and the context of the media. For example, an image of a user
assigned an identification confidence level of 85 and depicts the
user at a charity event but the user's name is not indicated. Based
on these factors, digital agent 118 can automatically contact the
entity hosting the image and request that the user's name be
indicated with the image. Digital agent 118 can contact the entity
hosting the image via any form of communication available to reach
the hosting entity (e.g., via email, voice, voicemail, instant
messaging, etc.). In one embodiment, an intermediating agent (e.g.,
a request broker) can translate and reformat requests to be sent to
a host as needed. In addition, the intermediating agent can perform
other functions such as locating the ultimate responsible hosting
or transmitting party when offending media is initially found on a
non-responsible site such as a public bulletin board or leveraging
a standing relationship with a host that allows for faster
resolution than through a direct owner request.
[0023] At step 210, agreement data is received from the host. For
example, the host may indicate that a web page may be altered to
display the user's name in a caption of the image depicting the
user. At step 212, the agreement data from the host is stored, for
example, in a database such as license database 116.
[0024] Before searching for media related to a particular user is
performed, a user's profile is determined. A user's profile is
determined using media which is known to describe the user and/or
the user's work (referred to as seed media). For example, a
particular user can provide one or more images and videos which
depict the user (i.e., seed media). The seed media provided can be
analyzed to determine characteristics which identify the user and
media associated with the user (e.g., documents written by the
user, etc.)
[0025] FIG. 3 depicts method 300 for generating a user profile
based on seed media. At step 302, seed media describing a user is
received. Seed media, in one embodiment, is media which depicts a
particular user. For example, media such as images and videos which
depict the user can be used as seed media. Generally, seed media
unambiguously depicts a user so that an accurate user profile can
be generated. For example, images used as seed media should provide
clear depictions of a user from multiple perspectives. Videos used
as seed media should provide various examples of a user's gait,
gestures, etc. Audio used as seed media should provide various user
voice samples sufficient to generate a reliable voice profile of a
user. In one embodiment, a user supplies the seed media to generate
a user profile for the user, however, a person other than the user
may provide the seed media as well to generate a user profile as
well.
[0026] At step 304, a plurality of user characteristics are
generated based on the seed media. User characteristics, in one
embodiment, are elements which can be used to identify a user. For
example, a voice profile for a user can be generated based on audio
seed media. Data for use with facial recognition can be generated
based on image seed media. Patterns concerning a user's gait,
gestures, and body shape can be generated for use in detecting user
characteristics.
[0027] At step 306, a determination is made as to whether there is
additional seed media describing a user. If there is additional
media, the method repeats steps 302 and 304 for the additional
media. If there is no additional media, a user profile is generated
based on the media describing the user. The user profile comprises
the plurality of user characteristics generated based on seed media
in step 304.
[0028] Depending on the type of seed media, various additional user
characteristics can be identified. For example, both image and
video media can be used to generate additional user characteristics
such as user location at specific dates and times, clothing owned
or worn by a user, body movements particular to the specific user,
facial ticks, people/places users have been associated with, etc.
Seed media can include a user's first-order characteristics (i.e.,
a user's immediate characteristics such as physical dimensions of
the user's face and body) as well as secondary attributes such as a
user's relationships with others. The secondary attributes can help
identify a primary subject. For example, it is known that a user
and a particular person are generally in one another's presence. If
an image shows a front view of the particular person and the
backside of an unidentified person, the unidentified person may be
identified as the user based on the knowledge that the user and the
particular person are generally in one another's presence.
[0029] Seed media can also comprise other media such as documents
(e.g., documents authored or contributed to by user), calendar
entries (as well as general future plans), location information,
lifestyle data (e.g., purchases, interests, likes/dislikes),
habits, personal preferences, correspondence and communications
(including text, voice, video, etc.), predefined events and
actions, quirks, values/morals, occupation, employers, etc.
[0030] The user profile generated in step 308 can be stored in a
database, such as user profile database 114. FIG. 4 depicts user
profile table 400 comprising multiple records 402, 404, 406,
wherein each record stores user profile data pertaining to a
particular user. Profile ID 408 uniquely identifies each user
profile. Additional columns store user information such as name
410, date of birth 412, height 414, and weight 416. Linguistics 418
stores data pertaining to a user's voice for use in voice
recognition. Schedule 420 stores information pertaining to a user's
schedule which can be used to aid in the identification of a user
in media. Similarly, location 422 stores information pertaining to
a user's location. Authorship 424 identifies documents authored by
a user either solely or in conjunction with additional authors. It
should be noted that in one embodiment entries (also referred to as
cells) contain data representing a single value. For example, cells
in location 422 column may contain a single location, such as
Albuquerque, N. Mex. in record 404. In other embodiments, cells may
contain files or links to files containing multiple values over
time. For example, location 422 cell of record 402 states
"JS11071958.loc" which identifies a file containing multiple user
locations at various times. By using a file, the location of a
particular user at specific times can be determined which can aid
in identification of a user in media. For example, if an image
depicts a user at a specific location at a specific time, a file
stored in location 422 can be used to confirm that the user was
indeed located at the specific location at a specific time as
determined by the image and associated data (e.g., an EXIF file
associated with the image).
[0031] As previously described in conjunction with FIG. 2, media
content is compared to a user profile (step 204) and an
identification confidence level is assigned to the media (step
206). FIG. 5 depicts a flow chart further defining steps 204 and
206 of FIG. 2. At step 502, media content is compared to a
plurality of user characteristics. For example, a video depicting a
person can be analyzed using voice recognition to identify the
person in the image. The data for use in identifying the person, in
this case, would be linguistics characteristics such as the data
stored in or identified by linguistics 418 column of FIG. 4.
Additional characteristics such as height 414, weight 416, and
schedule 420 can be compared to the media as well.
[0032] At step 504, a characteristic confidence level for each of a
plurality of characteristics is determined. For example, media
content compared with user characteristics may not result in a
perfect match. Depending on the content of the media, such as the
length of a voice sample, a characteristic confidence level may be
less than 100 (i.e., a perfect match). In these situations, a
characteristic confidence level of less than 100 may be determined
based on how well the media content matches a corresponding
characteristic. A characteristic confidence level is determined for
each characteristic compared to media content.
[0033] At step 506, an identification confidence level is assigned
to the media based on the characteristic confidence levels. In one
embodiment, the identification confidence level is an average of
the all the characteristic confidence levels related to the media
being analyzed. In other embodiments, other methods of generating
an identification confidence level may be used.
[0034] At step 508, the media, identification confidence level and
characteristic confidence levels are stored, for example, in a
database such as media database 112 shown in FIG. 1. At step 510,
one or more user profiles (e.g., user profile records 402, 404, 406
of table 400 shown in FIG. 4) are updated based on the media
content. Thus, although a user profile is initially generated using
seed media, media that is subsequently analyzed may be used to
update and/or modify the user profile.
[0035] FIG. 6 depicts media table 600 storing data related to
media, such as seed media (described in conjunction with FIG. 3) or
media analyzed as depicted in FIG. 2. Media and related information
are stored in records 602, 604, and 606. Each piece of media has a
unique identification number stored in media ID 608. Information
related to media is stored in additional columns including media
type 610, date created 612, ownership 614, content 616, and related
media 618, and file location 624 which indicates where the media is
stored. Information concerning the content of the media is stored
in additional columns such as person depicted 620. It should be
noted that table 600 is exemplary and media tables may include
additional columns for storing additional information such as
location depicted, objects depicted, etc. Identification confidence
level 622 stores a value of 1-100 which indicates the probability
that an identification, such as the identification of a person, is
correct. A confidence level of 100 indicates that the
identification is absolutely correct. Values less than 100 indicate
the probability that the identification is correct. Although not
shown in table 600, additional columns for other characteristics
and characteristic confidence levels may be listed as well.
[0036] Returning to FIG. 2, steps 208-212 pertain to digital agent
118 contacting a host of media regarding the use of media
identified as owned by a particular user. For example, a particular
user may designate that any image of the user found that is being
provided by a host should indicate the user's name when the image
is displayed. The user may further designate that actions should be
taken for images having an identification confidence level of
greater than a threshold level (e.g., 85) that are displayed
without indicating the user's name. The host providing the image of
the user may be contacted to indicate the user's desire to have the
user's name displayed with the image. Contact with the host may be
made via email, telephone, or other type of correspondence.
Communications from the host concerning an agreement are stored,
for example, in a database such as licensing database 116 shown in
FIG. 1. In one embodiment, a workflow system automatically manages
owner-host communications. Automated actions and closure of open
requests, in one embodiment, are enhanced by establishing
deterministic end-to-end automation and uniform data protocols. For
example, an owner request can be in a specific format which elicits
a response from a host in a specific format wherein the format is
known and used by both parties.
[0037] In one embodiment, a default action is taken based on how
the media provided by a host can be used or shared and whether the
media is determined to have a confidence level of greater than a
threshold value. For example, if the confidence level is at 85% or
more for the media and the host is sharing the media in a way that
only allows others (those besides the host) to access (e.g., view
or listen) then the digital agent would automatically grant
permission to the host to share in this case--assuming the image is
displayed with the user name or other agreed upon information
(e.g., age, height, weight, etc.). If the digital agent determines
that the host allows others to do more than access (e.g., view or
listen) the media (e.g., download and/or modify) then the digital
agent can be configured to contact the user to receive additional
details concerning how to proceed. In one embodiment, the digital
agent can send a host additional documents or messages informing
the host of potential action that may be taken by an owner of the
media provided by the host.
[0038] FIG. 7 depicts licensing table 700 which contains licensing
records 702, 704, and 706 which each store licensing information
pertaining to media. Each piece of media is identified by media ID
708 which, in one embodiment, is the same value used in media ID
608 of FIG. 6. Information concerning the media is contained in
media type 710 and date created 712. Ownership 714 identifies the
owner(s) of the related media. Information concerning licensing are
stored in licensed to 716, date licensed 718, and license term 720.
The location of documents memorializing the agreement are
identified by agreement storage location 722.
[0039] It should be noted that the system and methods described
above can be used by a particular user to search for media related
to other users. For example, a user can provide seed media
identifying a celebrity. This seed media can then be used to
generate a user profile of the celebrity which can then be used to
search for media related to the celebrity. Although the user can
search for media related to the celebrity, the user, in one
embodiment, is restricted from employing digital agent 118 to
obtain license agreements or instructing hosts how to present media
without the consent of the user identified by the user profile.
[0040] Media server 102, digital agent 118, and user devices
106-110 may be implemented using a computer. A high-level block
diagram of such a computer is illustrated in FIG. 8. Computer 802
contains a processor 804 which controls the overall operation of
the computer 802 by executing computer program instructions which
define such operation. The computer program instructions may be
stored in a storage device 812, or other computer readable medium
(e.g., magnetic disk, CD ROM, etc.), and loaded into memory 810
when execution of the computer program instructions is desired.
Thus, the method steps of FIGS. 2, 3, and 5 can be defined by the
computer program instructions stored in the memory 810 and/or
storage 812 and controlled by the processor 804 executing the
computer program instructions. For example, the computer program
instructions can be implemented as computer executable code
programmed by one skilled in the art to perform an algorithm
defined by the method steps of FIGS. 2, 3, and 5. Accordingly, by
executing the computer program instructions, the processor 804
executes an algorithm defined by the method steps of FIGS. 2, 3,
and 5. The computer 802 also includes one or more network
interfaces 806 for communicating with other devices via a network.
The computer 802 also includes input/output devices 808 that enable
user interaction with the computer 802 (e.g., display, keyboard,
mouse, speakers, buttons, etc.) One skilled in the art will
recognize that an implementation of an actual computer could
contain other components as well, and that FIG. 8 is a high level
representation of some of the components of such a computer for
illustrative purposes.
[0041] The foregoing Detailed Description is to be understood as
being in every respect illustrative and exemplary, but not
restrictive, and the scope of the inventive concept disclosed
herein is not to be determined from the Detailed Description, but
rather from the claims as interpreted according to the full breadth
permitted by the patent laws. It is to be understood that the
embodiments shown and described herein are only illustrative of the
principles of the inventive concept and that various modifications
may be implemented by those skilled in the art without departing
from the scope and spirit of the inventive concept. Those skilled
in the art could implement various other feature combinations
without departing from the scope and spirit of the inventive
concept.
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