PATENT DOCUMENT

Publication Number: US-12045392-B1
Application Number: US-202117379698-A
Country: US
Kind Code: B1

Title: Method and device for defining custom hand gestures

Abstract:
In one implementation, a method of defining a custom hand gesture is performed by a device including an image sensor, one or more processors, and non-transitory memory. The method includes receiving a request to define a first hand gesture. The method includes capturing, via the image sensor, a first performance of the first hand gesture. The method includes extracting, from the first performance of the first hand gesture, a first set of features. The method includes defining, based on the first set of features, one or more gesture matching criteria for the first hand gesture.

Claims:
What is claimed is: 
     
       1. A method comprising:
 at a device comprising an image sensor, one or more processors, and non-transitory memory:
 receiving a request to associate a first function with a first hand gesture; 
 in response to receiving the request to associate the first function with the first hand gesture:
 receiving a user input indicating the first function; 
 capturing, via the image sensor, a first performance of the first hand gesture; 
 extracting, from the first performance of the first hand gesture, a first set of features; 
 displaying a prompt requesting a user of the device to confirm whether or not the first hand gesture is the same as a particular known hand gesture from a plurality of known hand gestures with corresponding gesture matching criteria; and 
 in response to the user confirming that the first hand gesture is not the same as the particular known hand gesture:
 displaying a prompt requesting the user to provide a name for the first hand gesture; and 
 defining, based on the first set of features, one or more gesture matching criteria for the first hand gesture, wherein the one or more gesture matching criteria for the first hand gesture correspond to at least one of a first motion or a first pose of one or more hands of the user of the device associated with the first hand gesture; 
 
 
 after associating the first function with the first hand gesture and defining the one or more gesture matching criteria for the first hand gesture, capturing, via the image sensor, a second performance of the first hand gesture; 
 extracting, from the second performance of the first hand gesture, a second set of features; and 
 in response to the second set of features satisfying the one or more gesture matching criteria for the first hand gesture, performing the first function and refining the one or more gesture matching criteria for the first hand gesture based on the second set of features, wherein the one or more refined gesture matching criteria for the first hand gesture correspond to at least one of a second motion or a second pose, different from the first motion or the first pose, of one or more hands of the user of the device associated with the first hand gesture. 
 
 
     
     
       2. The method of  claim 1 , further comprising, in response to receiving the request to associate the first function with the first hand gesture, presenting, via a display, a prompt to perform the first hand gesture, wherein capturing the first performance of the first hand gesture is performed in response to providing the prompt to perform the first hand gesture. 
     
     
       3. The method of  claim 1 , wherein defining the one or more gesture matching criteria for the first hand gesture includes training a neural network classifier on the first set of features. 
     
     
       4. The method of  claim 1 , wherein the first hand gesture is associated with a first direction and wherein performing the first function includes performing the first function with respect to an object within a path extending from a location of the second performance of the first hand gesture in the first direction. 
     
     
       5. The method of  claim 4 , further comprising:
 capturing, via the image sensor, a performance of a second hand gesture, wherein the second hand gesture is associated with a second direction and the object is within a path extending from a location of the performance of the second hand gesture in the second direction; 
 extracting, from the performance of the second hand gesture, a third set of features; and 
 in response to the third set of features satisfying the one or more gesture matching criteria for the second hand gesture, performing a second function with respect to the object. 
 
     
     
       6. The method of  claim 1 , wherein the one or more gesture matching criteria for the first hand gesture include one or more hand position matching criteria and one or more audio matching criteria for the first hand gesture. 
     
     
       7. The method of  claim 6 , further comprising:
 capturing, via the image sensor, a performance of a second hand gesture associated with one or more gesture matching criteria for the second hand gesture including the one or more hand position matching criteria and one or more audio matching criteria for the second hand gesture different than the one or more audio matching criteria for the first hand gesture; 
 extracting, from the performance of the second hand gesture, a third set of features; and 
 in response to the third set of features satisfying the one or more gesture matching criteria for the second hand gesture, performing a second function. 
 
     
     
       8. The method of  claim 1 , wherein defining the one or more gesture matching criteria for the first hand gesture comprises:
 specifying whether the first hand gesture is to be performed with a left hand of the user or a right hand of the user as a part of the gesture matching criteria. 
 
     
     
       9. The method of  claim 1 , wherein defining the one or more gesture matching criteria for the first hand gesture comprises:
 specifying a time duration for performing the first hand gesture as a part of the gesture matching criteria. 
 
     
     
       10. A device comprising:
 an image sensor; 
 a non-transitory memory; and 
 one or more processors to:
 receive a request to associate a first function with a first hand gesture; 
 in response to receiving the request to associate the first function with the first hand gesture:
 receive a user input indicating the first function; 
 capture, via the image sensor, a first performance of the first hand gesture; 
 extract, from the first performance of the first hand gesture, a first set of features; 
 display a prompt requesting a user of the device to confirm whether or not the first hand gesture is the same as a particular known hand gesture from a plurality of known hand gestures with corresponding gesture matching criteria; and 
 in response to the user confirming that the first hand gesture is not the same as the particular known hand gesture:
 display a prompt requesting the user to provide a name for the first hand gesture; and 
 define, based on the first set of features, one or more gesture matching criteria for the first hand gesture, wherein the one or more gesture matching criteria for the first hand gesture correspond to at least one of a first motion or a first pose of one or more hands of the user of the device associated with the first hand gesture; 
 
 
 after associating the first function with the first hand gesture and defining the one or more gesture matching criteria for the first hand gesture, capture, via the image sensor, a second performance of the first hand gesture; 
 extract, from the second performance of the first hand gesture, a second set of features; and 
 in response to the second set of features satisfying the one or more gesture matching criteria for the first hand gesture, perform the first function and refine the one or more gesture matching criteria for the first hand gesture based on the second set of features, wherein the one or more refined gesture matching criteria for the first hand gesture correspond to at least one of a second motion or a second pose, different from the first motion or the first pose, of one or more hands of the user of the device associated with the first hand gesture. 
 
 
     
     
       11. The device of  claim 10 , wherein the one or more processors are to define the one or more gesture matching criteria for the first hand gesture by training a neural network classifier on the first set of features. 
     
     
       12. The device of  claim 10 , wherein the first hand gesture is associated with a first direction and wherein the one or more processors are to perform the first function by performing the first function with respect to an object within a path extending from a location of the second performance of the first hand gesture in the first direction. 
     
     
       13. The device of  claim 12 , wherein the one or more processors are further to:
 capture, via the image sensor, a performance of a second hand gesture, wherein the second hand gesture is associated with a second direction and the object is within a path extending from a location of the performance of the second hand gesture in the second direction; 
 extract, from the performance of the second hand gesture, a third set of features; and 
 in response to the third set of features satisfying the one or more gesture matching criteria for the second hand gesture, perform a second function with respect to the object. 
 
     
     
       14. The device of  claim 10 , wherein the one or more gesture matching criteria for the first hand gesture include one or more hand position matching criteria and one or more audio matching criteria for the first hand gesture. 
     
     
       15. The device of  claim 14 , wherein the one or more processors are further to:
 capture, via the image sensor, a performance of a second hand gesture associated with one or more gesture matching criteria for the second hand gesture including the one or more hand position matching criteria and one or more audio matching criteria for the second hand gesture different than the one or more audio matching criteria for the first hand gesture; 
 extract, from the performance of the second hand gesture, a third set of features; and 
 in response to the third set of features satisfying the one or more gesture matching criteria for the second hand gesture, perform a second function. 
 
     
     
       16. The device of  claim 10 , wherein the one or more processors further cause the device to:
 in response to receiving the request to associate the first function with the first hand gesture, present, via a display, a prompt to perform the first hand gesture, wherein capturing the first performance of the first hand gesture is performed in response to providing the prompt to perform the first hand gesture. 
 
     
     
       17. The device of  claim 10 , wherein defining the one or more gesture matching criteria for the first hand gesture comprises:
 displaying a prompt requesting additional information regarding the first hand gesture; 
 in response to displaying the prompt requesting the additional information, receiving an indication of a time duration for performing the first hand gesture; and 
 including the time duration as a part of the gesture matching criteria. 
 
     
     
       18. A non-transitory computer-readable medium having instructions encoded thereon which, when executed by one or more processors of a device including an image sensor, cause the device to:
 receive a request to associate a first function with a first hand gesture; 
 in response to receiving the request to associate the first function with the first hand gesture:
 receive a user input indicating the first function; 
 capture, via the image sensor, a first performance of the first hand gesture; 
 extract, from the first performance of the first hand gesture, a first set of features; 
 display a prompt requesting a user of the device to confirm whether or not the first hand gesture is the same as a particular known hand gesture from a plurality of known hand gestures with corresponding gesture matching criteria; and 
 in response to the user confirming that the first hand gesture is not the same as the particular known hand gesture:
 display a prompt requesting the user to provide a name for the first hand gesture; and 
 define, based on the first set of features, one or more gesture matching criteria for the first hand gesture, wherein the one or more gesture matching criteria for the first hand gesture correspond to at least one of a first motion or a first pose of one or more hands of the user of the device associated with the first hand gesture; 
 
 
 after associating the first function with the first hand gesture and defining the one or more gesture matching criteria for the first hand gesture, capture, via the image sensor, a second performance of the first hand gesture; 
 extract, from the second performance of the first hand gesture, a second set of features; and 
 in response to the second set of features satisfying the one or more gesture matching criteria for the first hand gesture, perform the first function and refine the one or more gesture matching criteria for the first hand gesture based on the second set of features, wherein the one or more refined gesture matching criteria for the first hand gesture correspond to at least one of a second motion or a second pose, different from the first motion or the first pose, of one or more hands of the user of the device associated with the first hand gesture. 
 
     
     
       19. The method of  claim 1 , further comprising, in response to receiving the request to associate the first function with the first hand gesture, presenting, via a display, a prompt to indicate the first function, wherein receiving the user input indicating the first function is performed in response to providing the prompt to indicate the first function. 
     
     
       20. The method of  claim 1 , further comprising:
 receiving a request to associate a second function with a second hand gesture; and 
 in response to receiving the request to associate the second function with the second hand gesture:
 receiving a user input indicating the second function; 
 capturing, via the image sensor, a first performance of the second hand gesture; and 
 associating the second function with one or more gesture matching criteria for the second hand gesture. 
 
 
     
     
       21. The non-transitory computer-readable medium of  claim 18 , wherein the one or more gesture matching criteria for the first hand gesture include one or more hand position matching criteria and one or more audio matching criteria for the first hand gesture. 
     
     
       22. The non-transitory computer-readable medium of  claim 18 , wherein the instructions further cause the device to:
 in response to receiving the request to associate the first function with the first hand gesture, present, via a display, a prompt to perform the first hand gesture, wherein capturing the first performance of the first hand gesture is performed in response to providing the prompt to perform the first hand gesture. 
 
     
     
       23. The non-transitory computer-readable medium of  claim 18 , wherein the instructions further cause the device to:
 in response to receiving the request to associate the first function with the first hand gesture, present, via a display, a prompt to indicate the first function, wherein receiving the user input indicating the first function is performed in response to providing the prompt to indicate the first function. 
 
     
     
       24. The non-transitory computer-readable medium of  claim 18 , wherein defining the one or more gesture matching criteria for the first hand gesture comprises:
 displaying a prompt requesting additional information regarding the first hand gesture; 
 in response to displaying the prompt requesting the additional information, receiving an indication of whether the first hand gesture is to be performed with a left hand or a right hand; and 
 specifying whether the first hand gesture is to be performed with the left hand or the right hand as a part of the gesture matching criteria.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application claims priority to U.S. Provisional Patent App. No. 63/082,957, filed on Sep. 24, 2020, which is hereby incorporated by reference herein in its entirety. 
    
    
     TECHNICAL FIELD 
     The present disclosure generally relates to systems, methods, and devices for custom hand gestures, and in particular, relates to graphical user interfaces for defining a custom hand gesture and associating a function with the custom hand gesture. 
     BACKGROUND 
     In various implementations, an electronic device detects pre-defined hand gestures performed by a user and, in response, performs a corresponding function. However, in various implementations, a user may be physically unable to perform the pre-defined hand gesture or may desire that a hand gesture perform a different function. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       So that the present disclosure can be understood by those of ordinary skill in the art, a more detailed description may be had by reference to aspects of some illustrative implementations, some of which are shown in the accompanying drawings. 
         FIG.  1    is a block diagram of an example operating environment in accordance with some implementations. 
         FIG.  2    is a block diagram of an example controller in accordance with some implementations. 
         FIG.  3    is a block diagram of an example electronic device in accordance with some implementations. 
         FIGS.  4 A- 4 F  illustrate an XR environment, based on a physical environment, including a graphical user interface for selecting a function and selecting a hand gesture to associate with the function. 
         FIGS.  5 A- 5 L  illustrate the XR environment of  FIG.  4 A  including a graphical user interface for selecting a function and defining a hand gesture to associate with the function. 
         FIGS.  6 A- 6 I  illustrate the XR environment of  FIG.  4 A  including a graphical user interface for selecting a function associated with a target and defining a hand gesture to associate with the function. 
       FIGS.  7 A 1 - 7 H 2  illustrate the XR environment of  FIG.  4 A  in response to detecting various hand gestures. 
         FIG.  8    is a flowchart representation of a method of defining a hand gesture in accordance with some implementations. 
     
    
    
     In accordance with common practice the various features illustrated in the drawings may not be drawn to scale. Accordingly, the dimensions of the various features may be arbitrarily expanded or reduced for clarity. In addition, some of the drawings may not depict all of the components of a given system, method, or device. Finally, like reference numerals may be used to denote like features throughout the specification and figures. 
     SUMMARY 
     Various implementations disclosed herein include devices, systems, and methods for defining a custom hand gesture. In various implementations, the method is performed by a device including an image sensor, one or more processors, and non-transitory memory. The method includes receiving a request to define a first hand gesture. The method includes capturing, via the image sensor, a first performance of the first hand gesture. The method includes extracting, from the first performance of the first hand gesture, a first set of features. The method includes defining, based on the first set of features, one or more gesture matching criteria for the first hand gesture. 
     In accordance with some implementations, a device includes one or more processors, a non-transitory memory, and one or more programs; the one or more programs are stored in the non-transitory memory and configured to be executed by the one or more processors. The one or more programs include instructions for performing or causing performance of any of the methods described herein. In accordance with some implementations, a non-transitory computer readable storage medium has stored therein instructions, which, when executed by one or more processors of a device, cause the device to perform or cause performance of any of the methods described herein. In accordance with some implementations, a device includes: one or more processors, a non-transitory memory, and means for performing or causing performance of any of the methods described herein. 
     DESCRIPTION 
     A physical environment refers to a physical place that people can sense and/or interact with without aid of electronic devices. The physical environment may include physical features such as a physical surface or a physical object. For example, the physical environment corresponds to a physical park that includes physical trees, physical buildings, and physical people. People can directly sense and/or interact with the physical environment such as through sight, touch, hearing, taste, and smell. In contrast, an extended reality (XR) environment refers to a wholly or partially simulated environment that people sense and/or interact with via an electronic device. For example, the XR environment may include augmented reality (AR) content, mixed reality (MR) content, virtual reality (VR) content, and/or the like. With an XR system, a subset of a person&#39;s physical motions, or representations thereof, are tracked, and, in response, one or more characteristics of one or more virtual objects simulated in the XR environment are adjusted in a manner that comports with at least one law of physics. As an example, the XR system may detect movement of the electronic device presenting the XR environment (e.g., a mobile phone, a tablet, a laptop, a head-mounted device, and/or the like) and, in response, adjust graphical content and an acoustic field presented by the electronic device to the person in a manner similar to how such views and sounds would change in a physical environment. In some situations (e.g., for accessibility reasons), the XR system may adjust characteristic(s) of graphical content in the XR environment in response to representations of physical motions (e.g., vocal commands). 
     There are many different types of electronic systems that enable a person to sense and/or interact with various XR environments. Examples include head-mountable systems, projection-based systems, heads-up displays (HUDs), vehicle windshields having integrated display capability, windows having integrated display capability, displays formed as lenses designed to be placed on a person&#39;s eyes (e.g., similar to contact lenses), headphones/earphones, speaker arrays, input systems (e.g., wearable or handheld controllers with or without haptic feedback), smartphones, tablets, and desktop/laptop computers. A head-mountable system may have one or more speaker(s) and an integrated opaque display. Alternatively, a head-mountable system may be configured to accept an external opaque display (e.g., a smartphone). The head-mountable system may incorporate one or more imaging sensors to capture images or video of the physical environment, and/or one or more microphones to capture audio of the physical environment. Rather than an opaque display, a head-mountable system may have a transparent or translucent display. The transparent or translucent display may have a medium through which light representative of images is directed to a person&#39;s eyes. The display may utilize digital light projection, OLEDs, LEDs, uLEDs, liquid crystal on silicon, laser scanning light sources, or any combination of these technologies. The medium may be an optical waveguide, a hologram medium, an optical combiner, an optical reflector, or any combination thereof. In some implementations, the transparent or translucent display may be configured to become opaque selectively. Projection-based systems may employ retinal projection technology that projects graphical images onto a person&#39;s retina. Projection systems also may be configured to project virtual objects into the physical environment, for example, as a hologram or on a physical surface. 
     Numerous details are described in order to provide a thorough understanding of the example implementations shown in the drawings. However, the drawings merely show some example aspects of the present disclosure and are therefore not to be considered limiting. Those of ordinary skill in the art will appreciate that other effective aspects and/or variants do not include all of the specific details described herein. Moreover, well-known systems, methods, components, devices, and circuits have not been described in exhaustive detail so as not to obscure more pertinent aspects of the example implementations described herein. 
     In various implementations, an electronic device detects pre-defined hand gestures performed by a user and, in response, performs a corresponding function. Disclosed herein is a graphical user interface for associating a hand gesture, which may be pre-defined or defined by a user, with a function. 
       FIG.  1    is a block diagram of an example operating environment  100  in accordance with some implementations. While pertinent features are shown, those of ordinary skill in the art will appreciate from the present disclosure that various other features have not been illustrated for the sake of brevity and so as not to obscure more pertinent aspects of the example implementations disclosed herein. To that end, as a non-limiting example, the operating environment  100  includes a controller  110  and an electronic device  120 . 
     In some implementations, the controller  110  is configured to manage and coordinate an XR experience for the user. In some implementations, the controller  110  includes a suitable combination of software, firmware, and/or hardware. The controller  110  is described in greater detail below with respect to  FIG.  2   . In some implementations, the controller  110  is a computing device that is local or remote relative to the physical environment  105 . For example, the controller  110  is a local server located within the physical environment  105 . In another example, the controller  110  is a remote server located outside of the physical environment  105  (e.g., a cloud server, central server, etc.). In some implementations, the controller  110  is communicatively coupled with the electronic device  120  via one or more wired or wireless communication channels  144  (e.g., BLUETOOTH, IEEE 802.11x, IEEE 802.16x, IEEE 802.3x, etc.). In another example, the controller  110  is included within the enclosure of the electronic device  120 . In some implementations, the functionalities of the controller  110  are provided by and/or combined with the electronic device  120 . 
     In some implementations, the electronic device  120  is configured to provide the XR experience to the user. In some implementations, the electronic device  120  includes a suitable combination of software, firmware, and/or hardware. According to some implementations, the electronic device  120  presents, via a display  122 , XR content to the user while the user is physically present within the physical environment  105  that includes a table  107  within the field-of-view  111  of the electronic device  120 . As such, in some implementations, the user holds the electronic device  120  in his/her hand(s). In some implementations, while providing XR content, the electronic device  120  is configured to display an XR object (e.g., an XR cylinder  109 ) and to enable video pass-through of the physical environment  105  (e.g., including a representation  117  of the table  107 ) on a display  122 . The electronic device  120  is described in greater detail below with respect to  FIG.  3   . 
     According to some implementations, the electronic device  120  provides an XR experience to the user while the user is virtually and/or physically present within the physical environment  105 . 
     In some implementations, the user wears the electronic device  120  on his/her head. For example, in some implementations, the electronic device includes a head-mounted system (HMS), head-mounted device (HMD), or head-mounted enclosure (HME). As such, the electronic device  120  includes one or more XR displays provided to display the XR content. For example, in various implementations, the electronic device  120  encloses the field-of-view of the user. In some implementations, the electronic device  120  is a handheld device (such as a smartphone or tablet) configured to present XR content, and rather than wearing the electronic device  120 , the user holds the device with a display directed towards the field-of-view of the user and a camera directed towards the physical environment  105 . In some implementations, the handheld device can be placed within an enclosure that can be worn on the head of the user. In some implementations, the electronic device  120  is replaced with an XR chamber, enclosure, or room configured to present XR content in which the user does not wear or hold the electronic device  120 . 
       FIG.  2    is a block diagram of an example of the controller  110  in accordance with some implementations. While certain specific features are illustrated, those skilled in the art will appreciate from the present disclosure that various other features have not been illustrated for the sake of brevity, and so as not to obscure more pertinent aspects of the implementations disclosed herein. To that end, as a non-limiting example, in some implementations the controller  110  includes one or more processing units  202  (e.g., microprocessors, application-specific integrated-circuits (ASICs), field-programmable gate arrays (FPGAs), graphics processing units (GPUs), central processing units (CPUs), processing cores, and/or the like), one or more input/output (I/O) devices  206 , one or more communication interfaces  208  (e.g., universal serial bus (USB), FIREWIRE, THUNDERBOLT, IEEE 802.3x, IEEE 802.11x, IEEE 802.16x, global system for mobile communications (GSM), code division multiple access (CDMA), time division multiple access (TDMA), global positioning system (GPS), infrared (IR), BLUETOOTH, ZIGBEE, and/or the like type interface), one or more programming (e.g., I/O) interfaces  210 , a memory  220 , and one or more communication buses  204  for interconnecting these and various other components. 
     In some implementations, the one or more communication buses  204  include circuitry that interconnects and controls communications between system components. In some implementations, the one or more I/O devices  206  include at least one of a keyboard, a mouse, a touchpad, a joystick, one or more microphones, one or more speakers, one or more image sensors, one or more displays, and/or the like. 
     The memory  220  includes high-speed random-access memory, such as dynamic random-access memory (DRAM), static random-access memory (SRAM), double-data-rate random-access memory (DDR RAM), or other random-access solid-state memory devices. In some implementations, the memory  220  includes non-volatile memory, such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid-state storage devices. The memory  220  optionally includes one or more storage devices remotely located from the one or more processing units  202 . The memory  220  comprises a non-transitory computer readable storage medium. In some implementations, the memory  220  or the non-transitory computer readable storage medium of the memory  220  stores the following programs, modules and data structures, or a subset thereof including an optional operating system  230  and an XR experience module  240 . 
     The operating system  230  includes procedures for handling various basic system services and for performing hardware dependent tasks. In some implementations, the XR experience module  240  is configured to manage and coordinate one or more XR experiences for one or more users (e.g., a single XR experience for one or more users, or multiple XR experiences for respective groups of one or more users). To that end, in various implementations, the XR experience module  240  includes a data obtaining unit  242 , a tracking unit  244 , a coordination unit  246 , and a data transmitting unit  248 . 
     In some implementations, the data obtaining unit  242  is configured to obtain data (e.g., presentation data, interaction data, sensor data, location data, etc.) from at least the electronic device  120  of  FIG.  1   . To that end, in various implementations, the data obtaining unit  242  includes instructions and/or logic therefor, and heuristics and metadata therefor. 
     In some implementations, the tracking unit  244  is configured to map the physical environment  105  and to track the position/location of at least the electronic device  120  with respect to the physical environment  105  of  FIG.  1   . To that end, in various implementations, the tracking unit  244  includes instructions and/or logic therefor, and heuristics and metadata therefor. 
     In some implementations, the coordination unit  246  is configured to manage and coordinate the XR experience presented to the user by the electronic device  120 . To that end, in various implementations, the coordination unit  246  includes instructions and/or logic therefor, and heuristics and metadata therefor. 
     In some implementations, the data transmitting unit  248  is configured to transmit data (e.g., presentation data, location data, etc.) to at least the electronic device  120 . To that end, in various implementations, the data transmitting unit  248  includes instructions and/or logic therefor, and heuristics and metadata therefor. 
     Although the data obtaining unit  242 , the tracking unit  244 , the coordination unit  246 , and the data transmitting unit  248  are shown as residing on a single device (e.g., the controller  110 ), it should be understood that in other implementations, any combination of the data obtaining unit  242 , the tracking unit  244 , the coordination unit  246 , and the data transmitting unit  248  may be located in separate computing devices. 
     Moreover,  FIG.  2    is intended more as functional description of the various features that may be present in a particular implementation as opposed to a structural schematic of the implementations described herein. As recognized by those of ordinary skill in the art, items shown separately could be combined and some items could be separated. For example, some functional modules shown separately in  FIG.  2    could be implemented in a single module and the various functions of single functional blocks could be implemented by one or more functional blocks in various implementations. The actual number of modules and the division of particular functions and how features are allocated among them will vary from one implementation to another and, in some implementations, depends in part on the particular combination of hardware, software, and/or firmware chosen for a particular implementation. 
       FIG.  3    is a block diagram of an example of the electronic device  120  in accordance with some implementations. While certain specific features are illustrated, those skilled in the art will appreciate from the present disclosure that various other features have not been illustrated for the sake of brevity, and so as not to obscure more pertinent aspects of the implementations disclosed herein. To that end, as a non-limiting example, in some implementations the electronic device  120  includes one or more processing units  302  (e.g., microprocessors, ASICs, FPGAs, GPUs, CPUs, processing cores, and/or the like), one or more input/output (I/O) devices and sensors  306 , one or more communication interfaces  308  (e.g., USB, FIREWIRE, THUNDERBOLT, IEEE 802.3x, IEEE 802.11x, IEEE 802.16x, GSM, CDMA, TDMA, GPS, IR, BLUETOOTH, ZIGBEE, and/or the like type interface), one or more programming (e.g., I/O) interfaces  310 , one or more XR displays  312 , one or more optional interior- and/or exterior-facing image sensors  314 , a memory  320 , and one or more communication buses  304  for interconnecting these and various other components. 
     In some implementations, the one or more communication buses  304  include circuitry that interconnects and controls communications between system components. In some implementations, the one or more I/O devices and sensors  306  include at least one of an inertial measurement unit (IMU), an accelerometer, a gyroscope, a thermometer, one or more physiological sensors (e.g., blood pressure monitor, heart rate monitor, blood oxygen sensor, blood glucose sensor, etc.), one or more microphones, one or more speakers, a haptics engine, one or more depth sensors (e.g., a structured light, a time-of-flight, or the like), and/or the like. 
     In some implementations, the one or more XR displays  312  are configured to provide the XR experience to the user. In some implementations, the one or more XR displays  312  correspond to holographic, digital light processing (DLP), liquid-crystal display (LCD), liquid-crystal on silicon (LCoS), organic light-emitting field-effect transitory (OLET), organic light-emitting diode (OLED), surface-conduction electron-emitter display (SED), field-emission display (FED), quantum-dot light-emitting diode (QD-LED), micro-electro-mechanical system (MEMS), and/or the like display types. In some implementations, the one or more XR displays  312  correspond to diffractive, reflective, polarized, holographic, etc. waveguide displays. For example, the electronic device  120  includes a single XR display. In another example, the electronic device includes an XR display for each eye of the user. In some implementations, the one or more XR displays  312  are capable of presenting MR and VR content. 
     In some implementations, the one or more image sensors  314  are configured to obtain image data that corresponds to at least a portion of the face of the user that includes the eyes of the user (any may be referred to as an eye-tracking camera). In some implementations, the one or more image sensors  314  are configured to be forward-facing so as to obtain image data that corresponds to the physical environment as would be viewed by the user if the electronic device  120  was not present (and may be referred to as a scene camera). The one or more optional image sensors  314  can include one or more RGB cameras (e.g., with a complimentary metal-oxide-semiconductor (CMOS) image sensor or a charge-coupled device (CCD) image sensor), one or more infrared (IR) cameras, one or more event-based cameras, and/or the like. 
     The memory  320  includes high-speed random-access memory, such as DRAM, SRAM, DDR RAM, or other random-access solid-state memory devices. In some implementations, the memory  320  includes non-volatile memory, such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid-state storage devices. The memory  320  optionally includes one or more storage devices remotely located from the one or more processing units  302 . The memory  320  comprises a non-transitory computer readable storage medium. In some implementations, the memory  320  or the non-transitory computer readable storage medium of the memory  320  stores the following programs, modules and data structures, or a subset thereof including an optional operating system  330  and an XR presentation module  340 . 
     The operating system  330  includes procedures for handling various basic system services and for performing hardware dependent tasks. In some implementations, the XR presentation module  340  is configured to present XR content to the user via the one or more XR displays  312 . To that end, in various implementations, the XR presentation module  340  includes a data obtaining unit  342 , a gesture control unit  344 , an XR presenting unit  346 , and a data transmitting unit  348 . 
     In some implementations, the data obtaining unit  342  is configured to obtain data (e.g., presentation data, interaction data, sensor data, location data, etc.) from at least the controller  110  of  FIG.  1   . To that end, in various implementations, the data obtaining unit  342  includes instructions and/or logic therefor, and heuristics and metadata therefor. 
     In some implementations, the gesture control unit  344  is configured to detect hand gestures and perform corresponding functions. To that end, in various implementations, the gesture control unit  344  includes instructions and/or logic therefor, and heuristics and metadata therefor. 
     In some implementations, the XR presenting unit  346  is configured to present XR content via the one or more XR displays  312 . To that end, in various implementations, the XR presenting unit  346  includes instructions and/or logic therefor, and heuristics and metadata therefor. 
     In some implementations, the data transmitting unit  348  is configured to transmit data (e.g., presentation data, location data, etc.) to at least the controller  110 . In some implementations, the data transmitting unit  348  is configured to transmit authentication credentials to the electronic device. To that end, in various implementations, the data transmitting unit  348  includes instructions and/or logic therefor, and heuristics and metadata therefor. 
     Although the data obtaining unit  342 , the gesture control unit  344 , the XR presenting unit  346 , and the data transmitting unit  348  are shown as residing on a single device (e.g., the electronic device  120 ), it should be understood that in other implementations, any combination of the data obtaining unit  342 , the gesture control unit  344 , the XR presenting unit  346 , and the data transmitting unit  348  may be located in separate computing devices. 
     Moreover,  FIG.  3    is intended more as a functional description of the various features that could be present in a particular implementation as opposed to a structural schematic of the implementations described herein. As recognized by those of ordinary skill in the art, items shown separately could be combined and some items could be separated. For example, some functional modules shown separately in  FIG.  3    could be implemented in a single module and the various functions of single functional blocks could be implemented by one or more functional blocks in various implementations. The actual number of modules and the division of particular functions and how features are allocated among them will vary from one implementation to another and, in some implementations, depends in part on the particular combination of hardware, software, and/or firmware chosen for a particular implementation. 
       FIGS.  4 A- 4 F  illustrate an XR environment  400 , based on a physical environment, including a graphical user interface for selecting a function and selecting a hand gesture to associate with the function.  FIGS.  4 A- 4 F  illustrate the XR environment  400  from the perspective of a user of an electronic device. In various implementations, the perspective of the user is from a location of an image sensor of the electronic device. For example, in various implementations, the electronic device is a handheld electronic device and the perspective of the user is from a location of the image sensor of the handheld electronic device directed towards the physical environment. In various implementations, the perspective of the user is from the location of a user of the electronic device. For example, in various implementations, the electronic device is a head-mounted electronic device and the perspective of the user is from a location of the user directed towards the physical environment, generally approximating the field-of-view of the user were the head-mounted electronic device not present. In various implementations, the perspective of the user is from the location of an avatar of the user. For example, in various implementations, the XR environment  400  is a virtual environment and the perspective of the user is from the location of an avatar or other representation of the user directed towards the virtual environment. 
       FIG.  4 A  illustrates the XR environment  400  during a first time period. In various implementations, the first time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the first time period, the XR environment  400  includes a plurality of objects, including one or more real objects (e.g., a table  411 , a speaker  412 , a lamp  413 , and a door  414 ) and one or more virtual objects (e.g., a playback indicator  422  and a lock indicator  424 ). In various implementations, certain objects (such as the real objects  411 - 414  and the lock indicator  424 ) are displayed at a location in the XR environment  400 , e.g., at a location defined by three coordinates in a three-dimensional (3D) XR coordinate system. Accordingly, when the user moves in the XR environment  400  (e.g., changes either position and/or orientation), the objects are moved on the display of the device, but retain their location in the XR environment  400 . In various implementations, certain virtual objects (such as the playback indicator  422 ) are displayed at locations on the display such that when the user moves in the XR environment  400 , the objects are stationary on the display on the device. 
     The state of audio being played by the speaker  412  is indicated by the playback indicator  422 . During the first time period, the playback indicator  422  indicates that a first song (entitled “SongName1” by an artist named “ArtistName1”) is queued for playback as indicated by the playback indicator  422  including a pause/play affordance  425  in a first state. 
     The state of the lamp  413  is indicated by the presence or absence of light  423  emanating from the lamp  413 . During the first time period, the light  423  is present, indicating that the lamp  413  is on. 
     The state of the door  414  is indicated by the lock indicator  424 . During the first time period, the lock indicator  424  is displayed in a first state (e.g., a first color, such as red) to indicate that the door  414  is locked. At other times (e.g., in FIG.  5 H 2 ), the lock indicator  424  is displayed in a second state (e.g., a second color, such as green) to indicate that the door is unlocked. 
     During the first time period, the device detects a request to associate a hand gesture with a function. In various implementations, the request is detected based on a verbal command issued by a user. In various implementations, the request is detected based on user interaction with one or more affordances, such as menu items or buttons. 
       FIG.  4 B  illustrates the XR environment  400  during a second time period subsequent to the first time period. In various implementations, the second time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the second time period, in response to detecting the request to associate a hand gesture with a function, the XR environment  400  includes a gesture association window  430 . 
     During the second time period, the gesture association window  430  includes a prompt requesting that the user select a function to associate with the hand gesture. In various implementations, the user response is a verbal command. For example, during the second time period, the user responds to the prompt by saying “Open Yoga app.” In various implementations, the user response includes user interaction with one or more affordances, such as menu items or buttons to select a function from a list of available functions. 
       FIG.  4 C  illustrates the XR environment  400  during a third time period subsequent to the second time period. In various implementations, the third time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the third time period, the gesture association window  430  indicates that the hand gesture will launch a Yoga application and includes a prompt requesting that the user perform the hand gesture. 
       FIG.  4 D  illustrates the XR environment  400  during a fourth time period subsequent to the third time period. In various implementations, the fourth time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the fourth time period, the user performs a namaste gesture  441  in which the user&#39;s palms are pressed against one another with the user&#39;s thumbs facing the user. 
     The device detects the user&#39;s hands in the XR environment  400  and extracts a set of features from the performance of the namaste gesture  441 . In various implementations, the set of features includes features based on the position and/or orientation of various hand elements (e.g., the relative position in three-dimensional space of fingertips, knuckles, and/or palms) at various times during the fourth time period. 
     Based on the set of features, the device attempts to classify the namaste gesture  441  as a known hand gesture. In various implementations, the device accesses (either locally or remotely) a hand gesture database including data regarding a plurality of hand gestures. Each of the plurality of hand gestures are associated with a corresponding set of gesture matching criteria. If the set of features matches a set of gesture matching criteria for a particular gesture, the device recognizes the hand gesture as the particular gesture. For example, during the fourth time period, the device recognizes the namaste gesture  441  as a particular hand gesture named “Namaste”. 
       FIG.  4 E  illustrates the XR environment  400  during a fifth time period subsequent to the fourth time period. In various implementations, the fifth time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the fifth time period, in response to recognizing the namaste gesture  441 , the gesture association window  430  includes a prompt requesting that the user confirm that the gesture performed is the “Namaste” gesture. In various implementations, and as illustrated in  FIG.  4 E , the gesture association window  430  further includes a graphical representation of the recognized gesture. 
     During the fifth time period, the user confirms that the namaste gesture  441  performed by the user corresponds to the “Namaste” gesture. In various implementations, the user response is a verbal command. For example, during the second time period, the user responds to the prompt by saying “Yes.” In various implementations, the user response includes user interaction with one or more affordances, such as a “Yes” button or a “No” button, or performance of a confirmation hand gesture or a cancel hand gesture. 
       FIG.  4 F  illustrates the XR environment  400  during a sixth time period subsequent to the fifth time period. In various implementations, the sixth time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the sixth time period, in response to the user confirming that the namaste gesture  441  corresponds to the “Namaste” gesture, the gesture association window  430  includes a confirmation that performing the “Namaste” gesture will open the Yoga application. 
       FIGS.  5 A- 5 L  illustrate the XR environment  400  of  FIG.  4 A  including a graphical user interface for selecting a function and defining a hand gesture to associate with the function. Like  FIGS.  4 A- 4 F ,  FIGS.  5 A- 5 L  illustrate the XR environment  400  from the perspective of a user of an electronic device. 
       FIG.  5 A  illustrates the XR environment  400  during a first time period. In various implementations, the first time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the first time period, the device detects a request to associate a hand gesture with a function. In various implementations, the request is detected based on a verbal command issued by a user. In various implementations, the request is detected based on user interaction with one or more affordances, such as menu items or buttons. 
       FIG.  5 B  illustrates the XR environment  400  during a second time period subsequent to the first time period. In various implementations, the second time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the second time period, in response to detecting the request to associate a hand gesture with a function, the XR environment  400  includes the gesture association window  430 . 
     During the second time period, the gesture association window  430  includes a prompt requesting that the user input a function to associate with the hand gesture. In various implementations, the user response is a verbal command. For example, during the second time period, the user responds to the prompt by saying “Open Camera app.” In various implementations, the user response includes user interaction with one or more affordances, such as menu items or buttons to select a function from a list of available functions. 
       FIG.  5 C  illustrates the XR environment  400  during a third time period subsequent to the second time period. In various implementations, the third time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the third time period, the gesture association window  430  indicates that the hand gesture will launch a Camera application and includes a prompt requesting that the user perform the hand gesture. 
       FIG.  5 D  illustrates the XR environment  400  during a fourth time period subsequent to the third time period. In various implementations, the fourth time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the fourth time period, the user performs a framing gesture  442  in which each of the user&#39;s thumbs are pressed against the index finger of the opposite hand with the other fingers curled in towards the palms. 
     The device detects the user&#39;s hands in the XR environment  400  and extracts a set of features from the performance of the framing gesture  442 . In various implementations, the set of features includes features based on the position and/or orientation of various hand elements (e.g., the relative position in three-dimensional space of fingertips, knuckles, and/or palms) at various times during the fourth time period. 
     Based on the set of features, the device attempts to classify the framing gesture  442  as a known hand gesture. In various implementations, the device accesses (either locally or remotely) a hand gesture database including data regarding a plurality of hand gestures. Each of the plurality of hand gestures are associated with a corresponding set of gesture matching criteria. If the set of features matches a set of gesture matching criteria for a particular gesture, the device recognizes the hand gesture as the particular gesture. For example, during the fourth time period, the device recognizes the namaste gesture  441  as a particular hand gesture named “Diamond”. 
       FIG.  5 E  illustrates the XR environment  400  during a fifth time period subsequent to the fourth time period. In various implementations, the fifth time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the fifth time period, in response to recognizing the framing gesture  442 , the gesture association window  430  includes a prompt requesting that the user confirm that the gesture performed is the “Diamond” gesture. In various implementations, and as illustrated in  FIG.  5 E , the gesture association window  430  further includes a graphical representation of the recognized gesture. 
     During the fifth time period, the user denies that the framing gesture  442  performed by the user corresponds to the “Diamond” gesture. In various implementations, the user response is a verbal command. For example, during the second time period, the user responds to the prompt by saying “No.” In various implementations, the user response includes user interaction with one or more affordances, such as a “Yes” button or a “No” button. 
       FIG.  5 F  illustrates the XR environment  400  during a sixth time period subsequent to the fifth time period. In various implementations, the sixth time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the sixth time period, in response to the user denying that the framing gesture  442  corresponds to the “Diamond” gesture, the gesture association window  430  includes a prompt requesting that the user provide a name for the framing gesture  442 . In various implementations, the user response is a verbal command. For example, during the sixth time period, the user responds to the prompt by saying “Framing.” In various implementations, the user response includes user interaction with one or more affordances, such as a virtual keyboard. 
       FIG.  5 G  illustrates the XR environment  400  during a seventh time period subsequent to the sixth time period. In various implementations, the seventh time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the seventh time period, in response to the user providing a name for the framing gesture  442  of “Framing”, the gesture association window  430  includes a prompt requesting that the user perform the framing gesture  442 . 
       FIG.  5 H  illustrates the XR environment  400  during an eighth time period subsequent to the seventh time period. In various implementations, the eighth time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the eighth time period, the user performs the framing gesture  442 . 
     The device detects the user&#39;s hands in the XR environment  400  and extracts a set of features from the performance of the framing gesture  442 . In various implementations, the set of features includes features based on the position and/or orientation of various hand elements (e.g., the relative position in three-dimensional space of fingertips, knuckles, and/or palms) at various times during the eighth time period. 
     Based on the set of features, the device defines one or more gesture matching criteria for the framing gesture  442 . In various implementations, the device stores the gesture matching criteria for the framing gesture  442  in the gesture database. In various implementations, the device defines the gesture matching criteria for the framing gesture  442  further based on the set of features extracted during the fourth time period as another positive example of the framing gesture  442 . In various implementations, the device defines the gesture matching criteria for the framing gesture  442  further based on the gesture matching criteria for the “Diamond” gesture as a negative example of the framing gesture  442  (e.g., a gesture that is not the framing gesture  442 ). 
       FIG.  5 I  illustrates the XR environment  400  during a ninth time period subsequent to the eighth time period. In various implementations, the ninth time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the ninth time period, the gesture association window  430  includes a prompt requesting that the user perform a gesture that is similar to, but different from the framing gesture (e.g., a gesture that is not the framing gesture). 
       FIG.  5 J  illustrates the XR environment  400  during a tenth time period subsequent to the ninth time period. In various implementations, the tenth time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the tenth time period, the user performs a window gesture  443  in which each of the user&#39;s thumbs are pressed against the index finger of the opposite hand with the other fingers extended. 
     The device detects the user&#39;s hands in the XR environment  400  and extracts a set of features from the performance of the window gesture  442 . In various implementations, the set of features includes features based on the position and/or orientation of various hand elements (e.g., the relative position in three-dimensional space of fingertips, knuckles, and/or palms) at various times during the tenth time period. 
     Based on the set of features, the device refines the one or more gesture matching criteria for the framing gesture  442  based on the window gesture  443  as a negative example of the framing gesture  442  (e.g., a gesture that is not the framing gesture  442 ). In various implementations, the device refines the one or more gesture matching criteria for the framing gesture  442  based on other gestures in the gesture data that are similar to, but are different from the framing gesture  442 . 
     In various implementations, the device refines the one or more gesture matching criteria for the framing gesture  442  based on additional information provided by the user (which, in various implementations, is solicited by the device via one or more prompts). For example, in various implementations, the user provides information regarding the importance of timing, a motion path, finger pose, or left-right distinction. For example, in various implementations, the user provides information that timing is unimportant, relaxing the gesture matching criteria relating to timing. As another example, the user provides information that the motion path is important, narrowing the gesture matching criteria regarding motion of the hands through space while performing the gesture. As another example, in various implementations, the user provides information that left-right distinction is unimportant and the gesture matching criteria are met by performing the gesture with either hand. 
       FIG.  5 K  illustrates the XR environment  400  during an eleventh time period subsequent to the tenth time period. In various implementations, the eleventh time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the eleventh time period, the gesture association window  430  includes a prompt requesting that the user confirm the “Framing” gesture. In various implementations, and as illustrated in  FIG.  5 K , the gesture association window  430  includes a graphical representation of the defined gesture. In various implementations, the graphical representation of the defined gesture is based on a representative set of features that satisfy the gesture matching criteria for the “Framing” gesture, e.g., an animation of a skeletal model using the representative set of features. 
     During the eleventh time period, the user confirms that the framing gesture  442  performed by the user corresponds to the “Framing” gesture. In various implementations, the user response is a verbal command. For example, during the eleventh time period, the user responds to the prompt by saying “Yes.” In various implementations, the user response includes user interaction with one or more affordances, such as a “Yes” button or a “No” button, or performance of a confirmation hand gesture or a cancel hand gesture. 
       FIG.  5 L  illustrates the XR environment  400  during a twelfth time period subsequent to the eleventh time period. In various implementations, the twelfth time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the twelfth time period, in response to the user confirming that the framing gesture  442  corresponds to the “Framing” gesture, the gesture association window  430  includes a confirmation that performing the “Framing” gesture will open the Camera application. 
       FIGS.  6 A- 6 I  illustrate the XR environment  400  of  FIG.  4 A  including a graphical user interface for selecting a function associated with a target and defining a hand gesture to associate with the function. Like  FIGS.  4 A- 4 F  and  FIGS.  5 A- 5 S ,  FIGS.  6 A- 6 I  illustrate the XR environment  400  from the perspective of a user of an electronic device. 
       FIG.  6 A  illustrates the XR environment  400  during a first time period. In various implementations, the first time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the first time period, the device detects a request to associate a hand gesture with a function. In various implementations, the request is detected based on a verbal command issued by a user. In various implementations, the request is detected based on user interaction with one or more affordances, such as menu items or buttons. 
       FIG.  6 B  illustrates the XR environment  400  during a second time period subsequent to the first time period. In various implementations, the second time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the second time period, in response to detecting the request to associate a hand gesture with a function, the XR environment  400  includes the gesture association window  430 . 
     During the second time period, the gesture association window  430  includes a prompt requesting that the user input a function to associate with the hand gesture. In various implementations, the user response is a verbal command. For example, during the second time period, the user responds to the prompt by saying “Engage target.” In various implementations, the user response includes user interaction with one or more affordances, such as menu items or buttons to select a function from a list of available functions. 
       FIG.  6 C  illustrates the XR environment  400  during a third time period subsequent to the second time period. In various implementations, the third time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the third time period, the gesture association window  430  indicates that the hand gesture will launch an action to engage a target (e.g., turn a light on or off, play or pause music, lock or unlock a door, etc.) and includes a prompt requesting that the user perform the hand gesture at an example target (e.g., a bullseye). 
       FIG.  6 D  illustrates the XR environment  400  during a fourth time period subsequent to the third time period. In various implementations, the fourth time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the fourth time period, the XR environment  400  includes a virtual target  450  at a first location in the XR environment  400 . Further, during the fourth time period, the user performs a L-pointing gesture  444  directed at the virtual target  450  in which the user&#39;s index finger points at the virtual target, the thumb is extended, and the other fingers are curled in towards the palm. 
     The device detects the user&#39;s hand in the XR environment  400  and extracts a set of features from the performance of the L-pointing gesture  444 . In various implementations, the set of features includes features based on the position and/or orientation of various hand elements (e.g., fingertips, knuckles, and/or palms) at various times during the fourth time period. 
     Based on the set of features, the device attempts to classify the L-pointing gesture  444  as a known hand gesture. In various implementations, the device accesses (either locally or remotely) a hand gesture database including data regarding a plurality of hand gestures. Each of the plurality of hand gestures are associated with a corresponding set of gesture matching criteria. If the set of features matches a set of gesture matching criteria for a particular gesture, the device recognizes the hand gesture as the particular gesture. However, in various implementations, the set of features does not satisfy any known set of gesture matching criteria. 
       FIG.  6 E  illustrates the XR environment  400  during a fifth time period subsequent to the fourth time period. In various implementations, the fifth time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the fifth time period, in response to failing to recognize the L-pointing gesture  444 , the gesture association window  430  includes a prompt requesting that the user provide a name for the L-pointing gesture  444 . In various implementations, the user response is a verbal command. For example, during the sixth time period, the user responds to the prompt by saying “L-pointing.” In various implementations, the user response includes user interaction with one or more affordances, such as a virtual keyboard. 
       FIG.  6 F  illustrates the XR environment  400  during a sixth time period subsequent to the fifth time period. In various implementations, the sixth time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the sixth time period, in response to the user providing a name for the L-pointing gesture  444  of “L-pointing”, the gesture association window  430  includes a prompt requesting that the user perform the L-pointing gesture  444  at the virtual target  450 . 
       FIG.  6 G  illustrates the XR environment  400  during a seventh time period subsequent to the sixth time period. In various implementations, the seventh time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the seventh time period, the XR environment  400  includes the virtual target  450  at a second location in the XR environment  400 . Further, during the seventh time period, the user performs the L-pointing gesture  444  at the virtual target  450 . 
     The device detects the user&#39;s hands in the XR environment  400  and extracts a set of features from the performance of the L-pointing gesture  444 . In various implementations, the set of features includes features based on the position and/or orientation of various hand elements (e.g., the relative position in three-dimensional space of fingertips, knuckles, and/or palms) at various times during the eighth time period. 
     Based on the set of features, the device defines one or more gesture matching criteria for the L-pointing gesture  444 . In various implementations, the device stores the gesture matching criteria for the L-pointing gesture  444  in the gesture database. In various implementations, the device defines the gesture matching criteria for the L-pointing gesture  444  further based on the set of features extracted during the fourth time period as another positive example of the framing gesture  442 . 
     Based on the set of features and the location of the virtual target  450  in the XR environment, the device defines a direction associated with the L-pointing gesture  444  extending from a location of performance of the L-pointing gesture towards the virtual target  450 . 
       FIG.  6 H  illustrates the XR environment  400  during an eighth time period subsequent to the seventh time period. In various implementations, the eighth time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the eighth time period, the gesture association window  430  includes a prompt requesting that the user confirm the “L-pointing” gesture. In various implementations, and as illustrated in  FIG.  6 H , the gesture association window  430  includes a graphical representation of the defined gesture, including a representation of the direction associated with the gesture. 
     During the eighth time period, the user confirms that the L-pointing gesture  444  performed by the user corresponds to the “L-pointing” gesture. In various implementations, the user response is a verbal command. For example, during the eighth time period, the user responds to the prompt by saying “Yes.” In various implementations, the user response includes user interaction with one or more affordances, such as a “Yes” button or a “No” button, or performance of a confirmation hand gesture or a cancel hand gesture. 
       FIG.  6 I  illustrates the XR environment  400  during a ninth time period subsequent to the eighth time period. In various implementations, the ninth time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the ninth time period, in response to the user confirming that the L-pointing gesture  444  corresponds to the “L-pointing” gesture, the gesture association window  430  includes a confirmation that performing the “L-pointing” gesture will engage the target of the gesture. 
     FIGS.  7 A 1 - 7 H 2  illustrate the XR environment  400  of  FIG.  4 A  in response to detecting various hand gestures. Like  FIGS.  4 A- 4 F ,  FIGS.  5 A- 5 S , and  FIGS.  6 A- 6 I , FIGS.  7 A 1 - 7 H 2  illustrate the XR environment  400  from the perspective of a user of an electronic device. 
     FIG.  7 A 1  illustrates the XR environment  400  during a first time period. In various implementations, the first time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the first time period, the user performs the namaste gesture  441 . During the first time period, the device detects the user&#39;s hands in the XR environment  400  and extracts a set of features from the performance of the namaste gesture  441 . Further, the device determines that the set of features matches the one or more gesture matching criteria for the “Namaste” gesture stored in the gesture database. 
     FIG.  7 A 2  illustrates the XR environment  400  during a second time period subsequent to the first time period. In various implementations, the second time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. In response to determining that the set of features extracted from the namaste gesture  441  matches the one or more gesture matching criteria for the “Namaste” gesture, the device launches the Yoga application. Accordingly, during the second time period, the XR environment includes an application window of the Yoga application  461 . 
     FIG.  7 B 1  illustrates the XR environment  400  during a third time period subsequent to the second time period. In various implementations, the third time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the third time period, the user performs the framing gesture  442 . During the third time period, the device detects the user&#39;s hands in the XR environment  400  and extracts a set of features from the performance of the framing gesture  442 . Further, the device determines that the set of features matches the one or more gesture matching criteria for the “Framing” gesture stored in the gesture database. 
     FIG.  7 B 2  illustrates the XR environment  400  during a fourth time period subsequent to the third time period. In various implementations, the fourth time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. In response to determining that the set of features extracted from the framing gesture  442  matches the one or more gesture matching criteria for the “Framing” gesture, the device launches the Camera application. Accordingly, during the fourth time period, the XR environment  400  includes an application window of the Camera application  462 . 
     FIG.  7 C 1  illustrates the XR environment  400  during a fifth time period subsequent to the fourth time period. In various implementations, the fifth time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the fifth time period, the user performs the L-pointing gesture  444  at the speaker  412 . During the fifth time period, the device detects the user&#39;s hand in the XR environment  400  and extracts a set of features from the performance of the L-pointing gesture  444 . Further, the device determines that the set of features matches the one or more gesture matching criteria for the “Framing” gesture stored in the gesture database. Further, the device determines a direction of the L-pointing gesture  444  and determines that the speaker  412  is within a path extending from a location of the performance of the L-pointing gesture  444  in the determined direction. 
     FIG.  7 C 2  illustrates the XR environment  400  during a sixth time period subsequent to the fifth time period. In various implementations, the sixth time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. In response to determining that the set of features extracted from the L-pointing gesture  444  matches the one or more gesture matching criteria for the “L-pointing” gesture, the device engages the speaker  412 , resulting in a change of state from a paused state to a playing state. Accordingly, during the sixth time period, the playback indicator  422  indicates that the speaker  412  is playing the song entitled “SongName1” as indicated by the playback indicator  422  including the pause/play affordance  425  in a second state (rather than the pause/play affordance  425  in a first state as in FIG.  7 C 1 ). 
     FIG.  7 D 1  illustrates the XR environment  400  during a seventh time period subsequent to the sixth time period. In various implementations, the seventh time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the seventh time period, the user performs the L-pointing gesture  444  at the lamp  413 . During the seventh time period, the device detects the user&#39;s hand in the XR environment  400  and extracts a set of features from the performance of the L-pointing gesture  444 . Further, the device determines that the set of features matches the one or more gesture matching criteria for the “L-pointing” gesture stored in the gesture database. Further, the device determines a direction of the L-pointing gesture  444  and determines that the lamp  413  is within a path extending from a location of the performance of the L-pointing gesture  444  in the determined direction. 
     FIG.  7 D 2  illustrates the XR environment  400  during an eighth time period subsequent to the seventh time period. In various implementations, the eighth time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. In response to determining that the set of features extracted from the L-pointing gesture  444  matches the one or more gesture matching criteria for the “L-pointing” gesture, the device engages the lamp  413 , resulting in a change of state from an on state to an off state. Accordingly, during the eighth time period, the lamp  413  is off as indicated by the absence of light  423  emanating from the lamp  413 . 
     FIG.  7 E 1  illustrates the XR environment  400  during a ninth time period subsequent to the eighth time period. In various implementations, the ninth time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the ninth time period, the user performs a shaka gesture  445  (in which the thumb and the pinky are extended while the other fingers are curled in towards the palm) at the speaker  412 . During the ninth time period, the device detects the user&#39;s hand in the XR environment  400  and extracts a set of features from the performance of the shaka gesture  445 . Further, the device determines that the set of features matches the one or more gesture matching criteria for a “Shaka” or “Hang Loose” gesture stored in the gesture database. Further, the device determines a direction of the shaka gesture  445  and determines that the speaker  412  is within a path extending from a location of the performance of the shaka gesture  445  in the determined direction. 
     FIG.  7 E 2  illustrates the XR environment  400  during a tenth time period subsequent to the ninth time period. In various implementations, the tenth time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. In response to determining that the set of features extracted from the shaka gesture  445  matches the one or more gesture matching criteria for the “Shaka” gesture, the device performs an associated function with respect to the speaker  412 , e.g., changing the playing song to a Hawaiian song. Accordingly, during the tenth time period, the playback indicator  422  indicates that the speaker  412  is playing the song entitled “SongName2”. 
     FIG.  7 F 1  illustrates the XR environment  400  during an eleventh time period subsequent to the tenth time period. In various implementations, the eleventh time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the eleventh time period, the user performs a warding gesture  446  (in which the index finger and pinky are extended while the other fingers are held in towards the palm by the thumb) at the speaker  412 . During the eleventh time period, the device detects the user&#39;s hand in the XR environment  400  and extracts a set of features from the performance of the warding gesture  446 . Further, the device determines that the set of features matches the one or more gesture matching criteria for a “Warding” or “Sign of the Horns” gesture stored in the gesture database. Further, the device determines a direction of the warding gesture  446  and determines that the speaker  412  is within a path extending from a location of the performance of the warding gesture  446  in the determined direction. 
     FIG.  7 F 2  illustrates the XR environment  400  during a twelfth time period subsequent to the eleventh time period. In various implementations, the twelfth time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. In response to determining that the set of features extracted from the warding gesture  446  matches the one or more gesture matching criteria for the “Warding” gesture, the device performs an associated function with respect to the speaker  412 , e.g., changing the playing song to a heavy metal song. Accordingly, during the twelfth time period, the playback indicator  422  indicates that the speaker  412  is playing the song entitled “SongName3”. 
     FIG.  7 G 1  illustrates the XR environment  400  during a thirteenth time period subsequent to the twelfth time period. In various implementations, the thirteenth time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the thirteenth time period, the user performs a wand gesture  447  (in which the hand is held in a position in which the index finger is extended with the other fingers held in towards the palm by the thumb while moving the index finger in a circle) while speaking the term “abracadabra”. During the thirteenth time period, the device detects the user&#39;s hand in the XR environment  400  and extracts a set of hand features from the performance of the wand gesture  447 . During the thirteenth time period, the device detects the user&#39;s voice and extracts a set of voice features from the user speaking the term “abracadabra”. 
     Further, the device determines that the set of hand features and the set of voice features matches the one or more gesture matching criteria for a “Magic Lighting” gesture stored in the gesture database. 
     FIG.  7 G 2  illustrates the XR environment  400  during a fourteenth time period subsequent to the thirteenth time period. In various implementations, the fourteenth time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. In response to determining that the set of features extracted from the wand gesture  447  and the set of features extracted from the user speaking the term “abracadabra” matches the one or more gesture matching criteria for the “Magic Lighting” gesture, the device performs an associated function, e.g., turning the lamp  413  on. Accordingly, during the fourteenth time period, the lamp  413  is on as indicated by the presence of light  423  emanating from the lamp  413 . 
     FIG.  7 H 1  illustrates the XR environment  400  during a fifteenth time period subsequent to the fourteenth time period. In various implementations, the fourteenth time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. During the fifteenth time period, the user performs the wand gesture  447  while speaking the term “open sesame”. During the fifteenth time period, the device detects the user&#39;s hand in the XR environment  400  and extracts a set of hand features from the performance of the wand gesture  447 . During the fifteenth time period, the device detects the user&#39;s voice and extracts a set of voice features from the user speaking the term “open sesame”. 
     Further, the device determines that the set of hand features and the set of voice features matches the one or more gesture matching criteria for a “Magic Opening” gesture stored in the gesture database. 
     FIG.  7 H 2  illustrates the XR environment  400  during a sixteenth time period subsequent to the fifteenth time period. In various implementations, the sixteenth time period is an instant, a fraction of a second, a few seconds, a few hours, a few days, or any length of time. In response to determining that the set of features extracted from the wand gesture  447  and the set of features extracted from the user speaking the term “open sesame” matches the one or more gesture matching criteria for the “Magic Opening” gesture, the device performs an associated function, e.g., unlocking the door  414 . Accordingly, during the sixteenth time period, the door  414  is unlocked as indicated by the lock indicator  424 . 
       FIG.  8    is a flowchart representation of a method  800  of defining a hand gesture in accordance with some implementations. In various implementations, the method  800  is performed by a device with an image sensor, one or more processors, and non-transitory memory (e.g., the electronic device  120  of  FIG.  3   ). In some implementations, the method  800  is performed by processing logic, including hardware, firmware, software, or a combination thereof. In some implementations, the method  800  is performed by a processor executing instructions (e.g., code) stored in a non-transitory computer-readable medium (e.g., a memory). 
     The method  800  begins, in block  810 , with the device receiving a request to define a first hand gesture. For example, during the first time period of  FIG.  5 A , the device receives a request to associate a hand gesture with a function. 
     The method  800  continues, in block  820 , with the device capturing, via the image sensor, a first performance of the first hand gesture. For example, during the fourth time period of  FIG.  5 D , the device captures a first performance of the framing gesture  442 . 
     In various implementations, the method  800  includes, in response to receiving the request to define the hand gesture, providing a prompt to perform the first hand gesture. For example, in  FIG.  5 C , the gesture association window  430  includes a prompt to perform a gesture. In various implementations, capturing the first performance of the first hand gesture is performed in response to providing the prompt to perform the first hand gesture. 
     The method  800  continues, in block  830 , with the device extracting, from the first performance of the first hand gesture, a first set of features. In various implementations, the set of features includes features based on the position and/or orientation of various hand elements (e.g., the relative position in three-dimensional space of fingertips, knuckles, and/or palms) at various times. For example, during the fourth time period of  FIG.  5 D , the device extracts a first set of features from the first performance of the framing gesture  442 . 
     In various implementations, the set of features includes features based on the position and/or orientation of a single hand. For example, FIG.  7 E 1  illustrates performance of a shaka gesture  445  involving a single hand. In various implementations, the set of features includes features based on the position and/or orientation of two hands. For example, FIG.  7 B 1  illustrates performance of a framing gesture  442  involving two hands. In various implementations, the set of features includes features based on a change over time in position and/or orientation of one or two hands, e.g., how the hand or hands of a user move along a motion path. For example, FIG.  7 G 1  illustrates a wand gesture  447  involving the motion of a single hand. 
     The method  800  continues, in block  840 , with the device defining, based on the first set of features, one or more gesture matching criteria for the first hand gesture. For example, during the tenth time period of  FIG.  5 J , the device defines one or more gesture matching criteria for the “Framing” gesture based at least on the first set of features extracted from the first performance of the framing gesture  442  in  FIG.  5 D . 
     In various implementations, the device defines the one or more gesture matching criteria for the first hand gesture further based on a second set of features extracted from a second performance of the first hand gesture. For example, during the tenth time period of  FIG.  5 J , the device defines the one or more gesture matching criteria for the “Framing” gesture based on a second set of features extracted from the second performance of the framing gesture  442  in  FIG.  5 H . 
     In various implementations, the device defines the one or more gesture matching criteria for the first hand gesture further based on a second set of features extracted from a performance of the second hand gesture different than the first hand gesture. For example, during the tenth time period of  FIG.  5 J , the device defines the one or more gesture matching criteria for the “Framing” gesture based on a second set of features extracted from the performance of the window gesture  443  in  FIG.  5 J . 
     In various implementations, the method  800  further includes associating the first hand gesture with a first function. In various implementations, the first function includes launching an application, performing a function within an application (e.g., opening a window to compose a new message or changing a music playlist), or engaging a target (e.g., turning a light on or off, playing or pausing music, locking or unlocking a door, etc.). For example, in  FIG.  5 L , the framing gesture  442  is associated with a function of opening a Camera application. In various implementations, the method  800  further includes capturing, via the image sensor, a second performance of the first hand gesture. For example, in FIG.  7 B 1 , the device detects a performance of the framing gesture  442 . In various implementations, the method  800  further includes extracting, from the second performance of the first hand gesture, a second set of features. For example, in FIG.  7 B 1 , the device extracts a second set of features from the performance of the framing gesture  442 . In various implementations, the method  800  further includes, in response to the second set of features satisfying the one or more gesture matching criteria for the first hand gesture, performing the first function. For example, in FIG.  7 B 2 , in response to the features extracted from the performance of the framing gesture  442 , the device opens the Camera application, as indicated by the application window of the Camera application  462 . 
     In various implementations, extracting the first set of features (in block  830 ) includes applying a neural network to the first performance of the first hand gesture. In various implementations, the neural network includes an interconnected group of nodes. In various implementation, each node includes an artificial neuron that implements a mathematical function in which each input value is weighted according to a set of weights and the sum of the weighted inputs is passed through an activation function, typically a non-linear function such as a sigmoid, piecewise linear function, or step function, to produce an output value. In various implementations, the neural network is trained on training data to set the weights. 
     In various implementations, the neural network includes a deep learning neural network. Accordingly, in some implementations, the neural network includes a plurality of layers (of nodes) between an input layer (of nodes) and an output layer (of nodes). In various implementations, the neural network receives, as inputs, images of the performance of the first hand gesture. In various implementations, the neural network receives, as inputs, a preliminary set of features based on the position and/or orientation of various hand elements (e.g., fingertips, knuckles, and/or palms) at various times during performance of the first hand gesture. In various implementations, the neural network provides, as an output, the set of features. 
     In various implementations, defining the one or more gesture matching criteria for the first hand gesture (in block  840 ) includes training a neural network (e.g., a classifier) on the first set of features. In various implementations, the neural network includes an interconnected group of nodes. In various implementation, each node includes an artificial neuron that implements a mathematical function in which each input value is weighted according to a set of weights and the sum of the weighted inputs is passed through an activation function, typically a non-linear function such as a sigmoid, piecewise linear function, or step function, to produce an output value. In various implementations, the neural network is trained on training data to set the weights. 
     In various implementations, the training data includes the first set of features as a positive example of the first hand gesture. In various implementations, the training data includes a second set of features extracted from a second performance of the first hand gesture as a positive example of the first hand gesture. In various implementations, the second performance of the first hand gesture is performed in response to a prompt. For example, in  FIG.  5 H , a performance of the framing gesture  442  is performed in response to the prompt in the gesture association window  430  in  FIG.  5 G . In various implementations, the second performance of the first hand gesture is performed in order to cause the device to perform the first function. For example, in FIG.  7 B 1 , a performance of the framing gesture  442  is performed in order to cause the device to open the Camera application. 
     In various implementations, the training data includes a second set of features extracted from a performance of a second hand gesture as a negative example of the first hand gesture. In various implementations, the performance of the second hand gesture is performed in response to a prompt. For example, in  FIG.  5 J , a performance of the window gesture  443  is performed in response to the prompt in the gesture association window  430  in  FIG.  5 I . In various implementations, the performance of the second hand gesture is performed in order to cause the device to perform a second function. For example, if the user performs a gesture which opens the Camera application and the user quickly closes the Camera application, the device may determine that the gesture was not the framing gesture. In various implementations, the second set of features are obtained from a gesture database. For example, in various implementations, a second set of features from the “Diamond” gesture shown in  FIG.  5 E  is used as a negative example of the framing gesture  442 . 
     In various implementations, the neural network includes a deep learning neural network. Accordingly, in some implementations, the neural network includes a plurality of layers (of nodes) between an input layer (of nodes) and an output layer (of nodes). In various implementations, the neural network receives, as inputs, images of the performance of the first hand gesture. In various implementations, the neural network receives, as inputs, the first set of features. In various implementations, the neural network provides, as an output, an indication of the gesture performed. In various implementations, the neural network provides, as an output an indication that the first set of features satisfy (or do not satisfy) the one or more gesture matching criteria for the first hand gesture. 
     In various implementations, the first hand gesture is associated with a first direction and wherein performing the first function includes performing the first function with respect to an object within a path extending from a location of the second performance of the first hand gesture in the first direction. For example, in FIG.  7 C 1 , the L-pointing gesture  444  is associated with a first direction towards the speaker  412  and, in response to the L-pointing gesture  444  satisfying one or more gesture matching criteria, the device engages the speaker  412 , resulting in a change of state from a paused state to a playing state. 
     The first direction can be determined in a number of ways. For example, in FIG.  7 C 1  and in FIG.  7 D 1 , the direction of the L-pointing gesture  444  is determined as the direction of a ray extending along the index finger of the user. As another example, in FIG.  7 E 1 , the direction of the shaka gesture  445  is determined as the direction of a ray bisecting an angle defined by the thumb and the pinky finger. As another example, in FIG.  7 F 1 , the direction of the warding gesture  446  is determined as a direction of ray between two rays extending along the index finger and the ring finger. 
     In various implementations, a circling gesture is defined in which the hand is held and moved in a similar position and motion to the wand gesture  447  of FIG.  7 H 1 , but with the index finger tracing a circle around a target. In various implementations, the direction of the circling gesture is determined as the direction of a ray extending from the user&#39;s wrist through the center of the circle. 
     In various implementations, the method  800  includes capturing, via the image sensor, a performance of a second hand gesture, wherein the second hand gesture is associated with a second direction and the object is within a path extending from a location of the performance of the second hand gesture in the second direction. For example, in FIG.  7 E 1 , the device captures the performance of a shaka gesture  445  directed to the speaker  412 . The method  800  includes extracting, from the performance of the second hand gesture, a third set of features and, in response to the third set of features satisfying the one or more gesture matching criteria for the second hand gesture, performing a second function with respect to the object. For example, in FIG.  7 E 2 , in response to the features extracted from the shaka gesture  445  satisfying one or more gesture matching criteria for the corresponding gesture, the device changes the playing song to a Hawaiian song. 
     In various implementations, the one or more gesture matching criteria for the first hand gesture include one or more hand position matching criteria and one or more audio matching criteria for the first hand gesture. For example, in FIG.  7 G 1 , the device extracts a set of hand features from the wand gesture  447  and a set of voice features from the user speaking the term “abracadabra”. In response to determining that the set of hand features and the set of voice features satisfy the one or more gesture matching criteria for a “Magic Lighting” gesture stored in the gesture database, the device turns on the lamp  413  (shown in FIG.  7 G 2 ). 
     In various implementations, the method  800  includes capturing, via the image sensor, a performance of a second hand gesture associated with one or more gesture matching criteria for the second hand gesture including the one or more hand position matching criteria and one or more audio matching criteria for the second hand gesture different than the one or more audio matching criteria for the first hand gesture. The method  800  includes extracting, from the performance of the second hand gesture, a third set of features and, in response to the third set of features satisfying the one or more gesture matching criteria for the second hand gesture, performing a second function. For example, in FIG.  7 H 1 , the device extracts a set of hand features from the wand gesture  447  and a set of voice features from the user speaking the term “open sesame”. In response to determining that the set of hand features and the set of voice features satisfy the one or more gesture matching criteria for a “Magic Opening” gesture stored in the gesture database, the device unlocks the door  414  (shown in FIG.  7 H 2 ). In various implementations, hand position matching criteria for the “Magic Lighting” gesture and the “Magic Opening” gesture are the same. 
     While various aspects of implementations within the scope of the appended claims are described above, it should be apparent that the various features of implementations described above may be embodied in a wide variety of forms and that any specific structure and/or function described above is merely illustrative. Based on the present disclosure one skilled in the art should appreciate that an aspect described herein may be implemented independently of any other aspects and that two or more of these aspects may be combined in various ways. For example, an apparatus may be implemented and/or a method may be practiced using any number of the aspects set forth herein. In addition, such an apparatus may be implemented and/or such a method may be practiced using other structure and/or functionality in addition to or other than one or more of the aspects set forth herein. 
     It will also be understood that, although the terms “first,” “second,” etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first node could be termed a second node, and, similarly, a second node could be termed a first node, which changing the meaning of the description, so long as all occurrences of the “first node” are renamed consistently and all occurrences of the “second node” are renamed consistently. The first node and the second node are both nodes, but they are not the same node. 
     The terminology used herein is for the purpose of describing particular implementations only and is not intended to be limiting of the claims. As used in the description of the implementations and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that the term “and/or” as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items. It will be further understood that the terms “comprises” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. 
     As used herein, the term “if” may be construed to mean “when” or “upon” or “in response to determining” or “in accordance with a determination” or “in response to detecting,” that a stated condition precedent is true, depending on the context. Similarly, the phrase “if it is determined [that a stated condition precedent is true]” or “if [a stated condition precedent is true]” or “when [a stated condition precedent is true]” may be construed to mean “upon determining” or “in response to determining” or “in accordance with a determination” or “upon detecting” or “in response to detecting” that the stated condition precedent is true, depending on the context.

Metadata:
Filing Date: 20210719
Publication Date: 20240723
Grant Date: 20240723
Priority Date: 20200924
Inventors: SALTER, Thomas G.
Lozada, Richard Ignatius Pusal
Assignee: APPLE INC
CPC Classifications: [{"code": "G06V40/20", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06N3/08", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06F3/011", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06F3/017", "inventive": true, "first": true, "tree": "[]"}, {"code": "G06V40/20", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06N3/08", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06F3/011", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06F3/017", "inventive": true, "first": true, "tree": "[]"}, {"code": "G06V40/20", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06N3/08", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06F3/011", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06F3/017", "inventive": true, "first": true, "tree": "[]"}]
Family ID: 91953455