U.S. patent application number 12/722594 was filed with the patent office on 2011-09-15 for interacting with a computer based application.
Invention is credited to Darren Bennett, Matt Coohill, Kevin Geisner, Stephen G. Latta, Relja Markovic, Mark T. Mihelich, Jonathan T. Steed, Christopher Willoughby, Shawn C. Wright.
Application Number | 20110223995 12/722594 |
Document ID | / |
Family ID | 44295602 |
Filed Date | 2011-09-15 |
United States Patent
Application |
20110223995 |
Kind Code |
A1 |
Geisner; Kevin ; et
al. |
September 15, 2011 |
INTERACTING WITH A COMPUTER BASED APPLICATION
Abstract
A computing system runs an application (e.g., video game) that
interacts with one or more actively engaged users. One or more
physical properties of a group are sensed. The group may include
the one or more actively engaged users and/or one or more entities
not actively engaged with the application. The computing system
will determine that the group (or the one or more entities not
actively engaged with the application) have performed a
predetermined action. A runtime condition of the application is
changed in response to determining that the group (or the one or
more entities not actively engaged with the computer based
application) have performed the predetermined action. Examples of
changing a runtime condition include moving an object, changing a
score or changing an environmental condition of a video game.
Inventors: |
Geisner; Kevin; (Mercer
Island, CA) ; Markovic; Relja; (Seattle, WA) ;
Latta; Stephen G.; (Seattle, WA) ; Mihelich; Mark
T.; (Seattle, WA) ; Willoughby; Christopher;
(Kirkland, WA) ; Steed; Jonathan T.; (Redmond,
WA) ; Bennett; Darren; (Seattle, WA) ; Wright;
Shawn C.; (Sammamish, WA) ; Coohill; Matt;
(Redmond, WA) |
Family ID: |
44295602 |
Appl. No.: |
12/722594 |
Filed: |
March 12, 2010 |
Current U.S.
Class: |
463/36 |
Current CPC
Class: |
A63F 2300/1087 20130101;
G06F 3/011 20130101; A63F 13/10 20130101; A63F 2300/1093 20130101;
A63F 2300/8088 20130101; A63F 2300/8023 20130101; A63F 2300/10
20130101; A63F 2300/6045 20130101; G06F 3/017 20130101 |
Class at
Publication: |
463/36 |
International
Class: |
A63F 9/24 20060101
A63F009/24 |
Claims
1. A method for interacting with a computer based application,
comprising: performing the computer based application including
interacting with one or more actively engaged users; automatically
sensing one or more physical properties of one or more entities not
actively engaged with the computer based application; determining
that the one or more entities not actively engaged with the
computer based application have performed a predetermined action;
automatically changing a runtime condition of the computer based
application in response to determining that one or more entities
not actively engaged with the computer based application have
performed the predetermined action; and automatically reporting the
changing of the runtime condition in a user interface of the
computer based application.
2. The method of claim 1, wherein: the automatically sensing one or
more physical properties includes sensing a depth image; the
predetermined action is a gesture; and the determining that the one
or more entities not actively engaged with the computer based
application have performed the predetermined action includes using
the depth image to identify the gesture.
3. The method of claim 1, wherein: the automatically sensing one or
more physical properties includes sensing a depth image and sensing
a visual image; the predetermined action is a gesture; and the
determining that the one or more entities not actively engaged with
the computer based application have performed the predetermined
action includes using the depth image and the visual image to
identify the gesture.
4. The method of claim 1, wherein: the automatically sensing one or
more physical properties includes sensing one or more sounds; and
the determining that the one or more entities not actively engaged
with the computer based application have performed the
predetermined action includes using the one or more sounds to
determine that a predetermined sound event has occurred.
5. The method of claim 1, wherein: the computer based application
is a video game; and the changing a runtime condition of the
computer based application includes changing an appearance of an
item in the video game.
6. The method of claim 1, wherein: the computer based application
is a video game; and the changing a runtime condition of the
computer based application includes changing the score of the video
game.
7. The method of claim 1, further comprising: detecting an emotion
of the one or more entities not actively engaged with the computer
based application using a sensor that also senses information about
the one or more actively engaged users, the automatically changing
a runtime condition is performed in response to detecting the
emotion.
8. The method of claim 1, wherein: the determining that the one or
more entities not actively engaged with the computer based
application have performed a predetermined action comprises
identifying an action performed as a group.
9. The method of claim 1, wherein: the sensing one or more physical
properties of one or more entities not actively engaged with the
computer based application includes sensing motion of a group; the
determining that the one or more entities not actively engaged with
the computer based application have performed a predetermined
action comprises identifying an action of an individual of the
group; and the changing the runtime condition is performed based on
the action of the individual.
10. One or more processor readable storage devices having processor
readable code embodied on the one or more processor readable
storage devices, the processor readable code for programming one or
more processors to perform a method comprising: performing a video
game including interacting with one or more users who are bound to
the video game; receiving information from a first sensor about
moving objects, the moving objects include the one or more bound
users and one or more persons who are not bound to the video game;
automatically determining and characterizing movement of the moving
objects; and automatically changing the computer based video game
in response to movement of the one or more bound users and one or
more persons who are not bound to the video game.
11. The one or more processor readable storage devices of claim 10,
wherein: the receiving information from a first sensor includes
receiving a depth image; the automatically determining and
characterizing movement includes recognizing a gesture using the
depth image.
12. The one or more processor readable storage devices of claim 10,
wherein the method further comprises: receiving sound information
from a second sensor, the sound information is from the one or more
persons who are not bound to the computer based video game, the
changing the video game in performed partially in response to the
sound information.
13. The one or more processor readable storage devices of claim 10,
wherein: the changing the video game includes moving an item in the
video game in response to motion of the one or more persons who are
not bound to the video game.
14. The one or more processor readable storage devices of claim 10,
wherein: the determining and characterizing movement of the moving
objects comprises identifying an action performed as a group.
15. The one or more processor readable storage devices of claim 10,
wherein: the receiving information from a first sensor about moving
objects includes sensing motion of a group; the determining and
characterizing movement of the moving objects includes identifying
an action of an individual of the group; the changing the video
game is performed based on the action of the individual.
16. A computing system, comprising: a camera; and a computer
connected to the camera, the computer includes: a tracking engine
that receives data from the camera and tracks one or more moving
objects, the tracking engine provides output information indicative
of tracking of the one or more moving objects, a software
application in communication with the tracking engine, the software
application interacts with the one or more actively engaged users
based on output information from the tracking engine, a plurality
of filters, each filter of the plurality receives input data about
movement perceptible by the camera, and each filter of the
plurality determines and outputs to the software application
whether one or more entities not actively engaged with the software
application have performed a predetermined action, the software
application makes a change to a runtime condition reported in a
user interface of the software application in response to the
filters indicating that one or more entities not actively engaged
with the software application have performed a predetermined
action, and a recognizer engine that receives data from the camera
and output information from the tracking engine and selectively
provides the data from the camera and output information from the
tracking engine to one or more of the filters as input data for the
respective one or more filters.
17. The computing system of claim 16, wherein: the camera includes
a depth sensor; and the data from the camera includes a depth
image.
18. The computing system of claim 17, wherein: the software
application is a video game; and the change to the runtime
condition is a movement of an object in response to movement of one
or more entities not actively engaged with the video game.
19. The computing system of claim 16, wherein: the software
application is a video game; and each filter of the plurality
determines and outputs to the video game whether one or more
entities not actively engaged with the software application have
performed a different gesture.
20. The computing system of claim 16, wherein: the software
application is a video game; and one particular filter of the
plurality determines and outputs to the video game whether a group
has performed a predetermined motion as an aggregate, the group
including that entities not actively engaged with the software
application and the entities that are actively engaged with the
software application.
Description
BACKGROUND
[0001] Video games continue to become more popular, with more
households now owning video game consoles and/or personal computers
running video games. While one or more people are playing a video
game, it is not unusual for multiple individuals to be watching in
the background. Although playing a video game can be very fun,
watching a video game may not be as engaging.
SUMMARY
[0002] Technology is disclosed that allows users who are not
actively engaged with the video game (e.g., not playing the game)
to interact with and effect the game. This technology can be used
with computer based applications other than video games.
[0003] One embodiment includes performing a computer based
application including interacting with one or more actively engaged
users, automatically sensing one or more physical properties of one
or more entities not actively engaged with the computer based
application, determining that the one or more entities not actively
engaged with the computer based application have performed a
predetermined action, automatically changing a runtime condition of
the computer based application in response to determining that one
or more entities not actively engaged with the computer based
application have performed the predetermined action, and
automatically reporting the changing of the runtime condition in a
user interface of the computer based application.
[0004] One embodiment includes performing the computer based video
game including interacting with one or more users who are bound to
the computer based video game, receiving information from a first
sensor about moving objects, and automatically determining and
characterizing movement of the moving objects. The moving objects
include the one or more bound users and one or more persons who are
not bound to the computer based video game. The process also
includes automatically changing the computer based video game in
response to movement of the one or more bound users and one or more
persons who are not bound to the computer based video game. One
embodiment includes one or more processor readable storage devices
having processor readable code embodied on the one or more
processor readable storage devices. The processor readable code
programs one or more processors to perform any of the methods
described herein.
[0005] One embodiment includes a camera (or other type of sensor)
and a computer connected (directly or indirectly) to the camera.
The computer includes a tracking engine, a software application, a
recognizer engine and a plurality of filters. The tracking engine
receives data from the camera and tracks one or more moving objects
based on the received data. The tracking engine provides output
information indicative of tracking the one or more moving objects.
The software application is in communication with the tracking
engine. The software application interacts with the one or more
actively engaged users based on output information from the
tracking engine. The recognizer engine receives data from the
camera and output information from the tracking engine and
selectively provides the data from the camera and output
information from the tracking engine to one or more of the filters
as input data for the respective one or more filters. Each filter
of the plurality of filters receives input data about movement
perceptible by the camera. Each filter of the plurality of filters
determines and outputs to the software application whether one or
more entities not actively engaged with the software application
have performed a predetermined action. The software application
makes a change to a runtime condition reported in a user interface
of the software application in response to the filters indicating
that one or more entities not actively engaged with the software
application have performed the predetermined action.
[0006] This Summary is provided to introduce a selection of
concepts in a simplified form that are further described below in
the Detailed Description. This Summary is not intended to identify
key features or essential features of the claimed subject matter,
nor is it intended to be used as an aid in determining the scope of
the claimed subject matter. Furthermore, the claimed subject matter
is not limited to implementations that solve any or all
disadvantages noted in any part of this disclosure.
BRIEF DESCRIPTION OF THE DRAWINGS
[0007] FIGS. 1A and 1B illustrate an example embodiment of a
tracking system with a user playing a game.
[0008] FIG. 2 illustrates an example embodiment of a capture device
that may be used as part of the tracking system.
[0009] FIG. 3 depicts an example of a skeleton.
[0010] FIG. 4 illustrates an example embodiment of a computing
system that may be used to track motion and update an application
based on the tracked motion.
[0011] FIG. 5 illustrates another example embodiment of a computing
system that may be used to track motion and update an application
based on the tracked motion.
[0012] FIG. 6 is a flow chart describing one embodiment of a
process for interacting with a computer based application.
[0013] FIG. 7 is a flow chart describing one embodiment of a
process for automatically sensing one or more physical properties
of environment.
[0014] FIG. 8 is a flow chart describing one embodiment of a
process for identify an action or condition based on the sensed one
or more physical properties.
[0015] FIG. 9 is a flow chart describing one embodiment of a
process for identify an action or condition based on the sensed one
or more physical properties.
[0016] FIG. 10 is a flow chart describing one embodiment of a
process for identify an action or condition based on the sensed one
or more physical properties.
[0017] FIG. 11 is a flow chart describing one embodiment of a
process for identify an action or condition based on the sensed one
or more physical properties.
[0018] FIG. 12 is a flow chart describing one embodiment of a
process for identify an action or condition based on the sensed one
or more physical properties.
DETAILED DESCRIPTION
[0019] A computing system runs an application (e.g., video game)
that interacts with one or more actively engaged users.
Additionally, one or more physical properties of a group of people
and/or environment are sensed. The group of people may include the
one or more of the actively engaged users and/or one or more
entities not actively engaged with the application. For example,
the system can sense movement of people who are in the background
and not playing a video game (e.g., people watching others play the
game). The computing system will determine that the group (or the
one or more entities not actively engaged with the application)
have performed a predetermined action. A runtime condition of the
application is changed in response to determining that the group
(or the one or more entities not actively engaged with the computer
based application) have performed the predetermined action.
Examples of changing a runtime condition include moving an object,
changing a score, or changing an environmental condition of a video
game.
[0020] In one embodiment, a video game system (or other data
processing system) tracks users and objects using depth images
and/or visual images. The tracking is then used to update an
application (e.g., a video game). Therefore, a user can manipulate
game characters or other aspects of the application by using
movement of the user's body and/or objects around the user, rather
than (or in addition to) using controllers, remotes, keyboards,
mice, or the like. For example, a video game system will update the
position of images displayed in the video based on the new
positions of the objects or update an avatar based on motion of the
user. If people in the room who are not playing the game perform
certain gestures, make various motions or emit certain sounds, the
video game will react to the gestures, motions and/or sounds of the
people in the room who are not playing the game by making a change
to the game.
[0021] Although the examples below include a video game system, the
technology described herein also applies to other types of data
processing systems and/or other types of applications.
[0022] FIGS. 1A and 1B illustrate an example embodiment of a system
10 with a user 18 playing a boxing game. In an example embodiment,
the system 10 may be used to recognize, analyze, and/or track a
human target such as the user 18 or other objects within range of
tracking system 10.
[0023] As shown in FIG. 1A, tracking system 10 may include a
computing system 12. The computing system 12 may be a computer, a
gaming system or console, or the like. According to an example
embodiment, the computing system 12 may include hardware components
and/or software components such that computing system 12 may be
used to execute applications such as gaming applications,
non-gaming applications, or the like. In one embodiment, computing
system 12 may include a processor such as a standardized processor,
a specialized processor, a microprocessor, or the like that may
execute instructions stored on a processor readable storage device
for performing the processes described herein.
[0024] As shown in FIG. 1A, tracking system 10 may further include
a capture device 20. The capture device 20 may be, for example, a
camera that may be used to visually monitor one or more users, such
as the user 18, such that gestures and/or movements performed by
the one or more users may be captured, analyzed, and tracked to
perform one or more controls or actions within the application
and/or animate an avatar or on-screen character, as will be
described in more detail below.
[0025] According to one embodiment, the tracking system 10 may be
connected to an audio/visual device 16 such as a television, a
monitor, a high-definition television (HDTV), or the like that may
provide game or application visuals and/or audio to a user such as
the user 18. For example, the computing system 12 may include a
video adapter such as a graphics card and/or an audio adapter such
as a sound card that may provide audio/visual signals associated
with the game application, non-game application, or the like. The
audio/visual device 16 may receive the audio/visual signals from
the computing system 12 and may then output the game or application
visuals and/or audio associated with the audio/visual signals to
the user 18. According to one embodiment, the audio/visual device
16 may be connected to the computing system 12 via, for example, an
S-Video cable, a coaxial cable, an HDMI cable, a DVI cable, a VGA
cable, component video cable, or the like.
[0026] As shown in FIGS. 1A and 1B, the tracking system 10 may be
used to recognize, analyze, and/or track a human target such as the
user 18. For example, the user 18 may be tracked using the capture
device 20 such that the gestures and/or movements of user 18 may be
captured to animate an avatar or on-screen character and/or may be
interpreted as controls that may be used to affect the application
being executed by computer environment 12. Thus, according to one
embodiment, the user 18 may move his or her body to control the
application and/or animate the avatar or on-screen character.
Similarly, tracking system 10 may be used to recognize, analyze,
and/or track persons who are watching user 18 play the game so that
movement by those persons watching user 18 play the game will
control movement avatars in the audience at the boxing game
displayed on audio/visual device 16.
[0027] In the example depicted in FIGS. 1A and 1B, the application
executing on the computing system 12 may be a boxing game that the
user 18 is playing. For example, the computing system 12 may use
the audio/visual device 16 to provide a visual representation of a
boxing opponent 22 to the user 18. The computing system 12 may also
use the audio/visual device 16 to provide a visual representation
of a user avatar 24 that the user 18 may control with his or her
movements. For example, as shown in FIG. 1B, the user 18 may throw
a punch in physical space to cause the user avatar 24 to throw a
punch in game space. Thus, according to an example embodiment, the
computer system 12 and the capture device 20 recognize and analyze
the punch of the user 18 in physical space such that the punch may
be interpreted as a game control of the user avatar 24 in game
space and/or the motion of the punch may be used to animate the
user avatar 24 in game space.
[0028] Other movements by the user 18 may also be interpreted as
other controls or actions and/or used to animate the user avatar,
such as controls to bob, weave, shuffle, block, jab, or throw a
variety of different power punches. Furthermore, some movements may
be interpreted as controls that may correspond to actions other
than controlling the user avatar 24. For example, in one
embodiment, the user may use movements to end, pause, or save a
game, select a level, view high scores, communicate with a friend,
etc. According to another embodiment, the user may use movements to
select the game or other application from a main user interface.
Thus, in example embodiments, a full range of motion of the user 18
may be available, used, and analyzed in any suitable manner to
interact with an application.
[0029] In example embodiments, the human target such as the user 18
may have an object. In such embodiments, the user of an electronic
game may be holding the object such that the motions of the user
and the object may be used to adjust and/or control parameters of
the game. For example, the motion of a user holding a racket may be
tracked and utilized for controlling an on-screen racket in an
electronic sports game. In another example embodiment, the motion
of a user holding an object may be tracked and utilized for
controlling an on-screen weapon in an electronic combat game.
Objects not held by the user can also be tracked, such as objects
thrown, pushed or rolled by the user (or a different user) as well
as self propelled objects. In addition to boxing, other games can
also be implemented.
[0030] According to other example embodiments, the tracking system
10 may further be used to interpret target movements as operating
system and/or application controls that are outside the realm of
games. For example, virtually any controllable aspect of an
operating system and/or application may be controlled by movements
of the target such as the user 18.
[0031] FIG. 2 illustrates an example embodiment of the capture
device 20 that may be used in the tracking system 10. According to
an example embodiment, the capture device 20 may be configured to
capture video with depth information including a depth image that
may include depth values via any suitable technique including, for
example, time-of-flight, structured light, stereo image, or the
like. According to one embodiment, the capture device 20 may
organize the depth information into "Z layers," or layers that may
be perpendicular to a Z axis extending from the depth camera along
its line of sight.
[0032] As shown in FIG. 2, the capture device 20 may include an
image camera component 23. According to an example embodiment, the
image camera component 23 may be a depth camera that may capture a
depth image of a scene. The depth image may include a
two-dimensional (2-D) pixel area of the captured scene where each
pixel in the 2-D pixel area may represent a depth value such as a
distance in, for example, centimeters, millimeters, or the like of
an object in the captured scene from the camera.
[0033] As shown in FIG. 2, according to an example embodiment, the
image camera component 23 may include an infra-red (IR) light
component 25, a three-dimensional (3-D) camera 26, and an RGB
camera 28 that may be used to capture the depth image of a scene.
For example, in time-of-flight analysis, the IR light component 25
of the capture device 20 may emit an infrared light onto the scene
and may then use sensors (not shown) to detect the backscattered
light from the surface of one or more targets and objects in the
scene using, for example, the 3-D camera 26 and/or the RGB camera
28. In some embodiments, pulsed infrared light may be used such
that the time between an outgoing light pulse and a corresponding
incoming light pulse may be measured and used to determine a
physical distance from the capture device 20 to a particular
location on the targets or objects in the scene. Additionally, in
other example embodiments, the phase of the outgoing light wave may
be compared to the phase of the incoming light wave to determine a
phase shift. The phase shift may then be used to determine a
physical distance from the capture device to a particular location
on the targets or objects.
[0034] According to another example embodiment, time-of-flight
analysis may be used to indirectly determine a physical distance
from the capture device 20 to a particular location on the targets
or objects by analyzing the intensity of the reflected beam of
light over time via various techniques including, for example,
shuttered light pulse imaging.
[0035] In another example embodiment, the capture device 20 may use
a structured light to capture depth information. In such an
analysis, patterned light (i.e., light displayed as a known pattern
such as grid pattern, a stripe pattern, or different pattern) may
be projected onto the scene via, for example, the IR light
component 25. Upon striking the surface of one or more targets or
objects in the scene, the pattern may become deformed in response.
Such a deformation of the pattern may be captured by, for example,
the 3-D camera 26 and/or the RGB camera 28 (and/or other sensor)
and may then be analyzed to determine a physical distance from the
capture device to a particular location on the targets or objects.
In some implementations, the IR Light component 25 is displaced
from the cameras 24 and 26 so triangulation can be used to
determined distance from cameras 26 and 28. In some
implementations, the capture device 20 will include a dedicated IR
sensor to sense the IR light, or a sensor with an IR filter.
[0036] According to another embodiment, the capture device 20 may
include two or more physically separated cameras that may view a
scene from different angles to obtain visual stereo data that may
be resolved to generate depth information. Other types of depth
image sensors can also be used to create a depth image.
[0037] The capture device 20 may further include a microphone 30.
The microphone 30 may include a transducer or sensor that may
receive and convert sound into an electrical signal. According to
one embodiment, the microphone 30 may be used to reduce feedback
between the capture device 20 and the computing system 12 in the
target recognition, analysis, and tracking system 10. Additionally,
the microphone 30 may be used to receive audio signals that may
also be provided by to computing system 12.
[0038] In an example embodiment, the capture device 20 may further
include a processor 32 that may be in communication with the image
camera component 23. The processor 32 may include a standardized
processor, a specialized processor, a microprocessor, or the like
that may execute instructions including, for example, instructions
for receiving a depth image, generating the appropriate data format
(e.g., frame) and transmitting the data to computing system 12.
[0039] The capture device 20 may further include a memory component
34 that may store the instructions that are executed by processor
32, images or frames of images captured by the 3-D camera and/or
RGB camera, or any other suitable information, images, or the like.
According to an example embodiment, the memory component 34 may
include random access memory (RAM), read only memory (ROM), cache,
flash memory, a hard disk, or any other suitable storage component.
As shown in FIG. 2, in one embodiment, memory component 34 may be a
separate component in communication with the image capture
component 23 and the processor 32. According to another embodiment,
the memory component 34 may be integrated into processor 32 and/or
the image capture component 23.
[0040] As shown in FIG. 2, capture device 20 may be in
communication with the computing system 12 via a communication link
36. The communication link 36 may be a wired connection including,
for example, a USB connection, a Firewire connection, an Ethernet
cable connection, or the like and/or a wireless connection such as
a wireless 802.11b, g, a, or n connection. According to one
embodiment, the computing system 12 may provide a clock to the
capture device 20 that may be used to determine when to capture,
for example, a scene via the communication link 36. Additionally,
the capture device 20 provides the depth information and visual
(e.g., RGB) images captured by, for example, the 3-D camera 26
and/or the RGB camera 28 to the computing system 12 via the
communication link 36. In one embodiment, the depth images and
visual images are transmitted at 30 frames per second. The
computing system 12 may then use the model, depth information, and
captured images to, for example, control an application such as a
game or word processor and/or animate an avatar or on-screen
character.
[0041] Computing system 12 includes depth image processing and
skeletal tracking module 50, which uses the depth images to track
one or more persons detectable by the depth camera. Depth image
processing and skeletal tracking module 50 provides the tracking
information to application 52, which can be a video game,
productivity application, communications application or other
software application, etc. The audio data and visual image data is
also provided to application 52 and depth image processing and
skeletal tracking module 50. Application 52 provides the tracking
information, audio data and visual image data to recognizer engine
54. In another embodiment, recognizer engine 54 receives the
tracking information directly from depth image processing and
skeletal tracking module 50 and receives the audio data and visual
image data directly from capture device 20. Recognizer engine 54 is
associated with a collection of filters 60, 62, 64, . . . , 66,
each comprising information concerning a gesture or other action or
event that may be performed by any person or object detectable by
capture device 20. For example, the data from capture device 20 may
be processed by the filters 60, 62, 64, . . . , 66 to identify when
a user or group of users has performed one or more gestures or
other actions. Those gestures may be associated with various
controls, objects or conditions of application 52. Thus, the
computing environment 12 may use the recognizer engine 54, with the
filters, to interpret movements.
[0042] Capture device 20 of FIG. 2 provides RGB images (or visual
images in other formats or color spaces) and depth images to
computing system 12. A depth image may be a plurality of observed
pixels where each observed pixel has an observed depth value. For
example, the depth image may include a two-dimensional (2-D) pixel
area of the captured scene where each pixel in the 2-D pixel area
may have a depth value such as distance of an object in the
captured scene from the capture device.
[0043] The system will use the RGB images and depth images to track
a user's movements. For example, the system will track a skeleton
of a person using a depth images. There are many methods that can
be used to track the skeleton of a person using depth images. One
suitable example of tracking a skeleton using depth images is
provided in U.S. patent application Ser. No. 12/603,437, "Pose
Tracking Pipeline," filed on Oct. 21, 2009. (hereinafter referred
to as the '437 Application), incorporated herein by reference in
its entirety. The process of the '437 Application includes
acquiring a depth image, down sampling the data, removing and/or
smoothing high variance noisy data, identifying and removing the
background, and assigning each of the foreground pixels to
different parts of the body. Based on those steps, the system will
fit a model with the data and create a skeleton. The skeleton will
include a set of joints and connections between the joints. FIG. 3
shows an example skeleton with 15 joints (j0, j1, j2, j3, j4, j5,
j6, j7, j8, j9, j10, j11, j12, j13, and j14). Each of the joints
represents a place in the skeleton where the skeleton can pivot in
the x, y, z directions or a place of interest on the body. Other
methods for tracking can also be used. Suitable tracking technology
is also disclosed in U.S. patent application Ser. No. 12/475,308,
"Device for Identifying and Tracking Multiple Humans Over Time,"
filed on May 29, 2009, incorporated herein by reference in its
entirety; U.S. patent application Ser. No. 12/696,282, "Visual
Based Identity Tracking," filed on Jan. 29, 2010, incorporated
herein by reference in its entirety; U.S. patent application Ser.
No. 12/641,788, "Motion Detection Using Depth Images," filed on
Dec. 18, 2009, incorporated herein by reference in its entirety;
and U.S. patent application Ser. No. 12/575,388, "Human Tracking
System," filed on Oct. 7, 2009, incorporated herein by reference in
its entirety.
[0044] Gesture recognizer engine 54 (of computing system 12
depicted in FIG. 2) is associated with multiple filters 60, 62, 64,
. . . , 66 to identify a gesture or action. A filter comprises
information defining a gesture, action or condition along with
parameters, or metadata, for that gesture, action or condition. For
instance, a throw, which comprises motion of one of the hands from
behind the rear of the body to past the front of the body, may be
implemented as a gesture comprising information representing the
movement of one of the hands of the user from behind the rear of
the body to past the front of the body, as that movement would be
captured by the depth camera. Parameters may then be set for that
gesture. Where the gesture is a throw, a parameter may be a
threshold velocity that the hand has to reach, a distance the hand
must travel (either absolute, or relative to the size of the user
as a whole), and a confidence rating by the recognizer engine that
the gesture occurred. These parameters for the gesture may vary
between applications, between contexts of a single application, or
within one context of one application over time. In one embodiment,
a filter has a number of inputs and a number of outputs.
[0045] Filters may be modular or interchangeable so that a first
filter may be replaced with a second filter that has the same
number and types of inputs and outputs as the first filter without
altering any other aspect of the recognizer engine architecture.
For instance, there may be a first filter for driving that takes as
input skeletal data and outputs a confidence that the gesture
associated with the filter is occurring and an angle of steering.
Where one wishes to substitute this first driving filter with a
second driving filter--perhaps because the second driving filter is
more efficient and requires fewer processing resources--one may do
so by simply replacing the first filter with the second filter so
long as the second filter has those same inputs and outputs--one
input of skeletal data type, and two outputs of confidence type and
angle type.
[0046] A filter need not have a parameter. For instance, a "user
height" filter that returns the user's height may not allow for any
parameters that may be tuned. An alternate "user height" filter may
have tunable parameters--such as to whether to account for a user's
footwear, hairstyle, headwear and posture in determining the user's
height.
[0047] Inputs to a filter may comprise things such as joint data
about a user's joint position, like angles formed by the bones that
meet at the joint, RGB color data from the scene, and the rate of
change of an aspect of the user. Outputs from a filter may comprise
things such as the confidence that a given gesture is being made,
the speed at which a gesture motion is made, and a time at which a
gesture motion is made.
[0048] Gesture recognizer engine 54 provides functionality to the
filters. In one embodiment, the functionality that the recognizer
engine 54 implements includes an input-over-time archive that
tracks recognized gestures and other input, a Hidden Markov Model
implementation (where the modeled system is assumed to be a Markov
process--one where a present state encapsulates any past state
information necessary to determine a future state, so no other past
state information must be maintained for this purpose--with unknown
parameters, and hidden parameters are determined from the
observable data), as well as other functionality required to solve
particular instances of gesture recognition.
[0049] Filters 60, 62, 64, . . . , 66 are loaded and implemented on
top of recognizer engine 54 and can utilize services provided by
recognizer engine 54 to all filters 60, 62, 64, . . . 66. In one
embodiment, recognizer engine 54 receives data to determine whether
it meets the requirements of any filter 60, 62, 64, . . . , 66.
Since these provided services, such as parsing the input, are
provided once by recognizer engine 54, rather than by each filter
60, 62, 64, . . . ,66, such a service need only be processed once
in a period of time as opposed to once per filter for that period
so the processing required to determine gestures is reduced.
[0050] Application 52 may use the filters 60, 62, 64, . . . , 66
provided by the recognizer engine 54, or it may provide its own
filters which plugs into recognizer engine 54. In one embodiment,
all filters have a common interface to enable this plug-in
characteristic. Further, all filters may utilize parameters, so a
single gesture tool below may be used to debug and tune the entire
filter system.
[0051] More information about recognizer engine 54 can be found in
U.S. patent application Ser. No. 12/422,661, "Gesture Recognizer
System Architecture," filed on Apr. 13, 2009, incorporated herein
by reference in its entirety. More information about recognizing
gestures can be found in U.S. patent application Ser. No.
12/391,150, "Standard Gestures," filed on Feb. 23, 2009; and U.S.
patent application Ser. No. 12/474,655, "Gesture Tool" filed on May
29, 2009. Both of which are incorporated by reference herein in
their entirety.
[0052] FIG. 4 illustrates an example embodiment of a computing
system that may be the computing system 12 shown in FIGS. 1A-2 used
to track motion and/or animate (or otherwise update) an avatar or
other on-screen object displayed by an application. The computing
system such as the computing system 12 described above with respect
to FIGS. 1A-2 may be a multimedia console 100, such as a gaming
console. As shown in FIG. 4, the multimedia console 100 has a
central processing unit (CPU) 101 having a level 1 cache 102, a
level 2 cache 104, and a flash ROM (Read Only Memory) 106. The
level 1 cache 102 and a level 2 cache 104 temporarily store data
and hence reduce the number of memory access cycles, thereby
improving processing speed and throughput. The CPU 101 may be
provided having more than one core, and thus, additional level 1
and level 2 caches 102 and 104. The flash ROM 106 may store
executable code that is loaded during an initial phase of a boot
process when the multimedia console 100 is powered on.
[0053] A graphics processing unit (GPU) 108 and a video
encoder/video codec (coder/decoder) 114 form a video processing
pipeline for high speed and high resolution graphics processing.
Data is carried from the graphics processing unit 108 to the video
encoder/video codec 114 via a bus. The video processing pipeline
outputs data to an A/V (audio/video) port 140 for transmission to a
television or other display. A memory controller 110 is connected
to the GPU 108 to facilitate processor access to various types of
memory 112, such as, but not limited to, a RAM (Random Access
Memory).
[0054] The multimedia console 100 includes an I/O controller 120, a
system management controller 122, an audio processing unit 123, a
network interface controller 124, a first USB host controller 126,
a second USB controller 128 and a front panel I/O subassembly 130
that are preferably implemented on a module 118. The USB
controllers 126 and 128 serve as hosts for peripheral controllers
142(1)-142(2), a wireless adapter 148, and an external memory
device 146 (e.g., flash memory, external CD/DVD ROM drive,
removable media, etc.). The network interface 124 and/or wireless
adapter 148 provide access to a network (e.g., the Internet, home
network, etc.) and may be any of a wide variety of various wired or
wireless adapter components including an Ethernet card, a modem, a
Bluetooth module, a cable modem, and the like.
[0055] System memory 143 is provided to store application data that
is loaded during the boot process. A media drive 144 is provided
and may comprise a DVD/CD drive, Blu-Ray drive, hard disk drive, or
other removable media drive, etc. The media drive 144 may be
internal or external to the multimedia console 100. Application
data may be accessed via the media drive 144 for execution,
playback, etc. by the multimedia console 100. The media drive 144
is connected to the I/O controller 120 via a bus, such as a Serial
ATA bus or other high speed connection (e.g., IEEE 1394).
[0056] The system management controller 122 provides a variety of
service functions related to assuring availability of the
multimedia console 100. The audio processing unit 123 and an audio
codec 132 form a corresponding audio processing pipeline with high
fidelity and stereo processing. Audio data is carried between the
audio processing unit 123 and the audio codec 132 via a
communication link. The audio processing pipeline outputs data to
the A/V port 140 for reproduction by an external audio user or
device having audio capabilities.
[0057] The front panel I/O subassembly 130 supports the
functionality of the power button 150 and the eject button 152, as
well as any LEDs (light emitting diodes) or other indicators
exposed on the outer surface of the multimedia console 100. A
system power supply module 136 provides power to the components of
the multimedia console 100. A fan 138 cools the circuitry within
the multimedia console 100.
[0058] The CPU 101, GPU 108, memory controller 110, and various
other components within the multimedia console 100 are
interconnected via one or more buses, including serial and parallel
buses, a memory bus, a peripheral bus, and a processor or local bus
using any of a variety of bus architectures. By way of example,
such architectures can include a Peripheral Component Interconnects
(PCI) bus, PCI-Express bus, etc.
[0059] When the multimedia console 100 is powered on, application
data may be loaded from the system memory 143 into memory 112
and/or caches 102, 104 and executed on the CPU 101. The application
may present a graphical user interface that provides a consistent
user experience when navigating to different media types available
on the multimedia console 100. In operation, applications and/or
other media contained within the media drive 144 may be launched or
played from the media drive 144 to provide additional
functionalities to the multimedia console 100.
[0060] The multimedia console 100 may be operated as a standalone
system by simply connecting the system to a television or other
display. In this standalone mode, the multimedia console 100 allows
one or more users to interact with the system, watch movies, or
listen to music. However, with the integration of broadband
connectivity made available through the network interface 124 or
the wireless adapter 148, the multimedia console 100 may further be
operated as a participant in a larger network community.
[0061] When the multimedia console 100 is powered ON, a set amount
of hardware resources are reserved for system use by the multimedia
console operating system. These resources may include a reservation
of memory (e.g., 16 MB), CPU and GPU cycles (e.g., 5%), networking
bandwidth (e.g., 8 kbs), etc. Because these resources are reserved
at system boot time, the reserved resources do not exist from the
application's view.
[0062] In particular, the memory reservation preferably is large
enough to contain the launch kernel, concurrent system applications
and drivers. The CPU reservation is preferably constant such that
if the reserved CPU usage is not used by the system applications,
an idle thread will consume any unused cycles.
[0063] With regard to the GPU reservation, lightweight messages
generated by the system applications (e.g., pop ups) are displayed
by using a GPU interrupt to schedule code to render popup into an
overlay. The amount of memory required for an overlay depends on
the overlay area size and the overlay preferably scales with screen
resolution. Where a full user interface is used by the concurrent
system application, it is preferable to use a resolution
independent of application resolution. A scaler may be used to set
this resolution such that the need to change frequency and cause a
TV resynch is eliminated.
[0064] After the multimedia console 100 boots and system resources
are reserved, concurrent system applications execute to provide
system functionalities. The system functionalities are encapsulated
in a set of system applications that execute within the reserved
system resources described above. The operating system kernel
identifies threads that are system application threads versus
gaming application threads. The system applications are preferably
scheduled to run on the CPU 101 at predetermined times and
intervals in order to provide a consistent system resource view to
the application. The scheduling is to minimize cache disruption for
the gaming application running on the console.
[0065] When a concurrent system application requires audio, audio
processing is scheduled asynchronously to the gaming application
due to time sensitivity. A multimedia console application manager
(described below) controls the gaming application audio level
(e.g., mute, attenuate) when system applications are active.
[0066] Input devices (e.g., controllers 142(1) and 142(2)) are
shared by gaming applications and system applications. The input
devices are not reserved resources, but are to be switched between
system applications and the gaming application such that each will
have a focus of the device. The application manager preferably
controls the switching of input stream, without knowledge the
gaming application's knowledge and a driver maintains state
information regarding focus switches. The cameras 26, 28 and
capture device 20 may define additional input devices for the
console 100 via USB controller 126 or other interface.
[0067] FIG. 5 illustrates another example embodiment of a computing
system 220 that may be used to implement the computing system 12
shown in FIGS. 1A-2 to track motion and/or animate (or otherwise
update) an avatar or other on-screen object displayed by an
application. The computing system environment 220 is only one
example of a suitable computing system and is not intended to
suggest any limitation as to the scope of use or functionality of
the presently disclosed subject matter. Neither should the
computing system 220 be interpreted as having any dependency or
requirement relating to any one or combination of components
illustrated in the exemplary operating system 220. In some
embodiments the various depicted computing elements may include
circuitry configured to instantiate specific aspects of the present
disclosure. For example, the term circuitry used in the disclosure
can include specialized hardware components configured to perform
function(s) by firmware or switches. In other examples embodiments
the term circuitry can include a general purpose processing unit,
memory, etc., configured by software instructions that embody logic
operable to perform function(s). In example embodiments where
circuitry includes a combination of hardware and software, an
implementer may write source code embodying logic and the source
code can be compiled into machine readable code that can be
processed by the general purpose processing unit. Since one skilled
in the art can appreciate that the state of the art has evolved to
a point where there is little difference between hardware,
software, or a combination of hardware/software, the selection of
hardware versus software to effectuate specific functions is a
design choice left to an implementer. More specifically, one of
skill in the art can appreciate that a software process can be
transformed into an equivalent hardware structure, and a hardware
structure can itself be transformed into an equivalent software
process. Thus, the selection of a hardware implementation versus a
software implementation is one of design choice and left to the
implementer.
[0068] Computing system 220 comprises a computer 241, which
typically includes a variety of computer readable media. Computer
readable media can be any available media that can be accessed by
computer 241 and includes both volatile and nonvolatile media,
removable and non-removable media. The system memory 222 includes
computer storage media in the form of volatile and/or nonvolatile
memory such as read only memory (ROM) 223 and random access memory
(RAM) 260. A basic input/output system 224 (BIOS), containing the
basic routines that help to transfer information between elements
within computer 241, such as during start-up, is typically stored
in ROM 223. RAM 260 typically contains data and/or program modules
that are immediately accessible to and/or presently being operated
on by processing unit 259. By way of example, and not limitation,
FIG. 4 illustrates operating system 225, application programs 226,
other program modules 227, and program data 228.
[0069] The computer 241 may also include other
removable/non-removable, volatile/nonvolatile computer storage
media. By way of example only, FIG. 4 illustrates a hard disk drive
238 that reads from or writes to non-removable, nonvolatile
magnetic media, a magnetic disk drive 239 that reads from or writes
to a removable, nonvolatile magnetic disk 254, and an optical disk
drive 240 that reads from or writes to a removable, nonvolatile
optical disk 253 such as a CD ROM or other optical media. Other
removable/non-removable, volatile/nonvolatile computer storage
media that can be used in the exemplary operating environment
include, but are not limited to, magnetic tape cassettes, flash
memory cards, digital versatile disks, digital video tape, solid
state RAM, solid state ROM, and the like. The hard disk drive 238
is typically connected to the system bus 221 through an
non-removable memory interface such as interface 234, and magnetic
disk drive 239 and optical disk drive 240 are typically connected
to the system bus 221 by a removable memory interface, such as
interface 235.
[0070] The drives and their associated computer storage media
discussed above and illustrated in FIG. 5, provide storage of
computer readable instructions, data structures, program modules
and other data for the computer 241. In FIG. 5, for example, hard
disk drive 238 is illustrated as storing operating system 258,
application programs 257, other program modules 256, and program
data 255. Note that these components can either be the same as or
different from operating system 225, application programs 226,
other program modules 227, and program data 228. Operating system
258, application programs 257, other program modules 256, and
program data 255 are given different numbers here to illustrate
that, at a minimum, they are different copies. A user may enter
commands and information into the computer 241 through input
devices such as a keyboard 251 and pointing device 252, commonly
referred to as a mouse, trackball or touch pad. Other input devices
(not shown) may include a microphone, joystick, game pad, satellite
dish, scanner, or the like. These and other input devices are often
connected to the processing unit 259 through a user input interface
236 that is coupled to the system bus, but may be connected by
other interface and bus structures, such as a parallel port, game
port or a universal serial bus (USB). The cameras 26, 28 and
capture device 20 may define additional input devices for the
console 100 that connect via user input interface 236. A monitor
242 or other type of display device is also connected to the system
bus 221 via an interface, such as a video interface 232. In
addition to the monitor, computers may also include other
peripheral output devices such as speakers 244 and printer 243,
which may be connected through a output peripheral interface 233.
Capture Device 20 may connect to computing system 220 via output
peripheral interface 233, network interface 237, or other
interface.
[0071] The computer 241 may operate in a networked environment
using logical connections to one or more remote computers, such as
a remote computer 246. The remote computer 246 may be a personal
computer, a server, a router, a network PC, a peer device or other
common network node, and typically includes many or all of the
elements described above relative to the computer 241, although
only a memory storage device 247 has been illustrated in FIG. 5.
The logical connections depicted include a local area network (LAN)
245 and a wide area network (WAN) 249, but may also include other
networks. Such networking environments are commonplace in offices,
enterprise-wide computer networks, intranets and the Internet.
[0072] When used in a LAN networking environment, the computer 241
is connected to the LAN 245 through a network interface or adapter
237. When used in a WAN networking environment, the computer 241
typically includes a modem 250 or other means for establishing
communications over the WAN 249, such as the Internet. The modem
250, which may be internal or external, may be connected to the
system bus 221 via the user input interface 236, or other
appropriate mechanism. In a networked environment, program modules
depicted relative to the computer 241, or portions thereof, may be
stored in the remote memory storage device. By way of example, and
not limitation, FIG. 5 illustrates application programs 248 as
residing on memory device 247. It will be appreciated that the
network connections shown are exemplary and other means of
establishing a communications link between the computers may be
used.
[0073] Either of the systems of FIG. 4 or 5, or a different
computing system, can be used to implement Computing System 12 of
FIG. 2. As explained above, computing system 12 determines the
motions of the users and employs those detected motions to control
a video game or other application. For example, a user's motions
can be used to control an avatar and/or object in a video game. In
some embodiments, the system can simultaneously track multiple
users and allow the motion of multiple users to control or effect
the application.
[0074] In one embodiment, in order for a user's motion to be used
to control an application the user must first be enrolled or bound
to the application. For example, when playing a video game, a
system may ask how many users will be playing that game. After the
users respond with the number of users, the system will ask each
user to identify himself or herself. In one embodiment, each user
will be asked to identify himself or herself by standing in front
of the system so that depth images and/or visual images can be
obtained from multiple angles for that user. For example, the user
may be asked to stand in front of the camera, turn around, and make
various poses while depth images and visual images are obtained.
After the system obtains enough depth and/or visual images, the
system will create a set of identifying data from the images that
uniquely identifies the user. The system will create a unique
identification and associate that unique identification with an
entity (e.g., avatar) or other object in the game/application.
After a user is enrolled in (or bound to) the application, the
system will track the motion of that user while the user is
actively engaged with the application (e.g., playing the game or
using the application). However, in the past, other people in the
room who are not actively engaged with the application, (e.g., not
bound to application, bound to application but not playing current
game, or bound to application but currently not having a turn to
play) do not have a way to interact with the application.
[0075] FIG. 6 is a flow chart describing one embodiment of a
process for running/implementing an application that allows people
who are not actively engaged with the application to interact with
the application. In step 340 of FIG. 6, application 52 interacts
with one or more bound users who are actively engaged with
application 52. Computing system 12 will sense, detect and compute
the movement of various users and that movement will be used to
control a video game or other type of application. For example, a
user's movement can be used to control an avatar. Alternatively, a
game controller can be used to control an avatar.
[0076] In step 342 of FIG. 6, the system will automatically sense
one or more physical properties of the environment that is
detectable by capture device 20. This includes detecting one or
more properties of one or more entities that are bound users who
are actively engaged with application 52, sensing one or more
properties of one or more entities that are not actively engaged
with application 52, and/or other environmental conditions (e.g.
lighting, movement of objects, etc.). In step 344, the system will
identify that an action occurred or condition exists based on the
sensed one or more physical properties from step 342.
[0077] In step 346, the system will automatically change a run time
condition of application 52 in response to identifying the action
or condition in step 344. For example, the system will determine
that one or more persons in the room had made a specific motion or
performed a specific action. In response to that motion or action,
the system will change something about the game. Examples of
changes to the game or application that may be made in response to
recognizing an action or condition include (but at not limited to)
changing the score of one of the users based on the level of
cheering or movement of the group of people in the background,
changing background conditions (e.g., weather or lighting) in the
environment based on background conditions (e.g., lighting or
movement) in the room, moving an avatar or other object in response
to movement of persons in the room (e.g., if one or more bound
users are playing a video game that involves transport on a boat
and a number of background persons in the room stand up, this may
cause the boat to rock in the video game), changing the ability of
an avatar (e.g., increasing the power of a hitter or boxer) in a
video game due to movement or conditions (e.g., volume of cheering)
in the background of the persons playing the game, etc.
Alternatively, crowd noise in a video game can be proportional to
noise in the room of the people playing the video game. In another
alternative, crowd noise in the video game can be responsive to
emotions detected in one or more persons sitting or standing in the
background of a user playing the video game. In a non-video game
example, the brightness of the user interface can change based on
brightness in the room or distance of one or more persons from
capture device 20. Alternatively, font size can change in response
to persons approaching or walking away from capture device 20.
[0078] In step 348 of FIG. 6, the change to application 52 will be
reported in a user interface for application 52. For example, if
the score changes, the score will be updated in the user interface.
If any of the objects in the video game move or otherwise change
appearance, that change of appearance will be depicted in the user
interface of the video game. Similarly, font size or brightness can
change in the user interface for application 52. In other
embodiments, the change in the application could also be reported
via e-mail, text message, printout, speaker, etc.
[0079] The order of the steps depicted in FIG. 6 is one only
possible example. The steps of FIG. 6 can also be performed in
other orders. Additionally, many of the steps can be performed
concurrently. For example, step 340, which includes the application
interacting with bound users, can occur over a prolonged time
during which steps 342-348 are performed repeatedly.
[0080] FIG. 7 is a flow chart describing one embodiment for
automatically sensing one or more physical properties of an
environment, including properties of one or more entities not
actively engaged with the application and bound users who are
actively engaged. The process of FIG. 7 is one example
implementation of step 342 of FIG. 6. In step 402 of FIG. 7,
capture device 20 will sense a depth image. In step 404, that depth
image will be sent to computing system 12. In step 406, capture
device 20 will sense a visual image. In step 408, that visual image
will be sent to computing system 12. In step 410, capture device 20
will sense audio data. In step 412, that audio data will be sent to
computing system 12. In step 414, depth image processing and
skeleton tracking 50 will update the motion tracking based on the
depth image, visual image and/or audio data. In step 416, the depth
image, visual image and/or audio data, as well as tracking
information, will be provided to recognizer engine 54. In step 418,
recognizer engine 54 will process the received data and then call
the appropriate one or more filters in step 420.
[0081] Looking back to FIG. 6, step 344 includes identifying an
action or condition based on the sensed one or more physical
properties from step 342. In one embodiment, step 344 is performed
by filters 60, 62, 64, . . . , 66 (see FIG. 2). In one example, for
each action that an application wishes to detect, there will be a
separate filter. In other implementations, one filter can determine
more than one gesture or action. As explained with respect to FIG.
7, recognizer engine 54 will receive data throughout the
performance of an application. Each filter that is employed will
register with recognizer engine 54, including indicating which data
it is looking for. When recognizer engine 54 sees that the data for
a particular filter is available, recognizer engine 54 will call
the appropriate filter (step 420 of FIG. 7). It is possible that
many filters are called concurrently or in an overlapping manner.
Each of the filters that are called by recognizer engine 54 to look
for a specific set of one or more gestures or actions will
automatically identify an action or condition based on the physical
properties sensed. When a filter determines that a specific gesture
or action it is looking for has occurred, the filter will report
that information to application 52. FIGS. 8-12 are flow charts
describing the operation of various filters 60, 62, 64, . . . , 66
which can be used to implement step 344 of FIG. 6.
[0082] FIG. 8 is a flow chart describing the operation of a filter
that detects movement of a group of people. In one embodiment, the
output of the filter tells application 52 whether a group of people
in front of capture device 20 moved to the left, moved to the
right, moved forward or moved backward. In some embodiments, the
filter will also provide an indication of the magnitude of the
movement. In step 502, the filter will receive new depth image
information, tracking data and visual image information. In other
embodiments, a subset of that information will be provided to the
filter. For example, the filter can operate only on depth image
information, only on tracking data, only on visual images, or two
of the three. In step 504, the filter will identify the position of
foreground blobs. For example, using known techniques in the art,
the system can distinguish between foreground and background pixels
in either the depth image or visual image. One example is to
subtract successive images. Blobs that are moving are foreground
pixels and assumed to be persons in front of capture device 20. In
step 506, the filter will access position data for previous blobs
and previous iterations of the process of FIG. 8. In step 508, the
filter will identify movement of the aggregate group based on the
current and previous data. Thus, the system will look in the
history of images and determine whether the aggregate set of blobs
are moving to the left, the right, forward and/or backward.
[0083] In step 510 (optional), the system will attempt to identify
a specific blob for a specific person. This is contrasted to the
previous steps that looked at the aggregate of blobs and determined
whether the aggregate of blobs are moving in a particular
direction. If there is one person in the room moving in a different
direction than the rest of the group, that person will be
identified in step 510 and previous data will be associated with
that blob in order to determine the direction that person is
moving.
[0084] In step 512, it is determined whether the movement of the
group (or a specific person) is greater than a threshold. The
threshold can be set based on the requirements of the application,
or based on experimentation. If the movement is greater than a
threshold, then the movement is reported in step 514. In one
implementation, the filter will report whether the aggregate group
moved to the left, moved to the right, moved forward, or moved
backward. Optionally, the filter can report the magnitude of the
movement. Additionally (and optionally), the system will report
whether a specific person moved in a different direction than the
rest of the group. If, in step 512, it is determined that the
movement was not greater than a threshold amount of movement, then
the filter will not report anything to application 52.
[0085] In another alternative, the system will use separate filters
for each of the possible directions of movement. For example, there
will be one filter that will attempt to detect movement to the
left, a second filter for detecting movement to the right, a third
filter for detecting movement toward the camera, and a fourth
filter for detecting movement away from the camera. Each of those
filters will operate as described by the flow chart of FIG. 8,
except that the identification of movement in step 508 will only be
in the single direction for that filter and the reporting at step
514 will only be for the specific direction associated with that
filter.
[0086] In addition to tracking movement, filters can be used to
identify specific gestures. For example, if multiple people in a
group raise their hands up in the air, that can trigger an action
in a video game. Alternatively, if multiple people in the
background stand up in a certain order, that can trigger the fans
in a video baseball game (or other sporting event) performing the
wave in a stadium (standing up in sequence). In one embodiment, the
system can have several filters for tracking several gestures, with
each filter attempting to identify a different gesture. FIG. 9
depicts a flow chart describing one embodiment for operation a
filter that identifies a specific gesture. In step 602 of FIG. 9,
the filter will receive skeleton tracking data from depth image
processing and skeleton tracking 50, as described above. In step
604, the filter will access previous tracking data. In step 606,
the filter will attempt to identify the gesture associated with
that particular filter. In step 608, it is determined whether the
gesture was recognized. If the gesture was recognized, then in step
610 the gesture is reported to application 52. If the gesture was
not recognized, then the filter will not report to application 52
(step 612).
[0087] In one embodiment, every time a depth image is provided from
capture device 20, depth image processing and skeleton tracking 50
will update the skeleton tracking and provide the skeleton tracking
data to the filter performing the process of FIG. 9. Each time the
filter receives that skeleton tracking data, the process of FIG. 9
will be started. Note that more information about gestures can be
found in the following three patent applications that are
incorporated by reference herein in their entirety: U.S. patent
application Ser. No. 12/475,208, "Gestures Beyond Skeletal," filed
on May 29, 2009; U.S. patent application Ser. No. 12/391,150,
"Standard Gestures," filed on Feb. 23, 2009; and U.S. patent
application Ser. No. 12/474,655, "Gesture Tool" filed on May 29,
2009.
[0088] FIG. 10 is a flow chart describing one embodiment of a
filter that determines whether the brightness level in the room has
changed. For example, application 52 can use that change of
brightness to change the brightness, font size or other property of
application 52. In step 652, the filter will receive a visual image
from recognizer engine 54. In step 654, the filter will access a
previous set of visual images received. In step 656, the filter
will compare the brightness of the current visual image to the
previous visual images to see if there is a change in brightness.
If the change in brightness is greater than a threshold (step 658),
then the filter reports the change in brightness to application 52.
In one embodiment, the filter will report whether the visual image
is brighter or dimmer than the previous images. If the change in
brightness is not greater than a threshold, then the filter will
not report to application 52 (step 662).
[0089] FIG. 11 is a flow chart describing one embodiment of a
process performed by a filter that determines whether certain
sounds were made in the room. If such sounds are detected,
application 52 may change the sounds in a video game (increase or
decrease background noise/cheering), change the physical abilities
of the avatar playing an event in the video game, perform a command
in a productivity software program, etc. In step 682 of FIG. 11,
the filter receives the sound data from recognizer engine 54. In
step 684, the filter accesses previous sound data. In step 686, the
filter compares the volume of the current sound data to the volume
of previous sound data. If the difference in volume is greater than
a threshold (step 688), then that change in volume will be reported
to the application 52 in step 690. If the change in volume is not
greater than the threshold, then the filter will not report to
application 52 (step 692).
[0090] In an alternative embodiment, instead of trying to identify
whether the volume has changed by a threshold, the filter can
detect whether a certain sound (e.g. predetermined range of pitch
or predetermined range of tone) occurred and report based on
detecting the predetermined sound.
[0091] In another embodiment, a filter can detect whether one or
more persons in front of capture device 20 (including persons bound
to the game and persons not bound and not actively engaged in the
game) have experienced a predefined emotion. If it is detected that
one or more persons have exhibited that predefined emotion, the
application can change one or more properties such as increase the
cheering of the crowd in the background of a video game, change the
emotion of an avatar, undo a change made to a word processing
program, etc.
[0092] FIG. 12 depicts a flow chart describing one embodiment of a
process performed by a filter to detect and report about emotion.
In step 702 of FIG. 12, the filter will receive a visual image. In
step 704, the system will access previous visual images. In step
706, the filter will search for faces in the visual images from
steps 702 and 704. There are many processes for searching for faces
known in the art, many of which are suitable for this
implementation. In step 708, it is determined whether a face was
found in the current image and a sufficient number of the previous
images. If no face was found in the current visual image and/or
enough of the previous visual images, then the system will abort
and not report anything (step 710). If a face is found in the
current visual image and sufficient number of previous images, then
in step 712, the filter will examine the faces for an expression.
There are many expressions that a filter can look for. FIG. 12
provides three examples. In the first example, step 712A, the
system can examine the mouth to look for a smile. In the second
example, step 712B, the system will examine the eyes for widening.
In the third example, step 712C, the filter will examine a mouth
for a curvature downward and a wrinkling of the brow (e.g.,
indicating frown). In one embodiment, the system will look for all
three expressions. In another embodiment, each filter will only
look for one expression. In other embodiments, other expressions
could be identified. Each of the expressions corresponds to an
emotion. For example, a smile corresponds to happy, eyes widening
corresponds to surprise, and a frown corresponds to being unhappy.
If an expression is identified (step 714), then that corresponding
emotion is reported to the application in step 716. If an
expression is not identified (step 714), then nothing is reported
to the application 52 (step 718). In another embodiment, there can
be separate filters for each motion being searched for.
[0093] Using the above techniques, the system will use depth
images, visual images and/or audio information in order to observe
and identify various actions, gestures or conditions in a room
housing capture device 20. In this manner, one or more persons who
are not actively engaged and interacting with an application will
have their actions or gestures cause a change to the application;
thereby, providing those people not otherwise actively engaged with
the application (e.g. video game) with greater interest in what is
happening.
[0094] Although the subject matter has been described in language
specific to structural features and/or methodological acts, it is
to be understood that the subject matter defined in the appended
claims is not necessarily limited to the specific features or acts
described above. Rather, the specific features and acts described
above are disclosed as example forms of implementing the claims. It
is intended that the scope of the invention be defined by the
claims appended hereto.
* * * * *