PATENT DOCUMENT

Publication Number: US-12198267-B1
Application Number: US-202217702011-A
Country: US
Kind Code: B1

Title: Generating a shadow based on a spherical gaussian lobe

Abstract:
A method is performed at an electronic device including one or more processors and a non-transitory memory. The method includes obtaining a first spherical Gaussian (SG) lobe that characterizes ambient light from a physical environment. The method may include determining the first SG lobe based on a 360 degree image of the physical environment. The first SG lobe indicates a first directional characteristic associated with the ambient light. The method includes determining a first plurality of sampling rays based on the first directional characteristic. The method includes obtaining a depth value that is associated with a computer-generated object. The depth value may be from a depth buffer, which is populated with the depth value during rendering of the computer-generated object. The method includes generating a shadow that is associated with the computer-generated object, based on the depth value and a first sampling ray of the first plurality of sampling rays.

Claims:
What is claimed: 
     
       1. A method comprising:
 at an electronic device including one or more processors and a non-transitory memory: 
 obtaining a first spherical Gaussian (SG) lobe that characterizes ambient light from a physical environment, wherein the first SG lobe indicates a first directional characteristic associated with the ambient light; 
 determining a first plurality of sampling rays based on the first directional characteristic; 
 obtaining a depth value that is associated with a computer-generated object; and 
 generating a first shadow that is associated with the computer-generated object, based on the depth value and a first sampling ray of the first plurality of sampling rays. 
 
     
     
       2. The method of  claim 1 , wherein the first SG lobe is characterized by an SG function corresponding to G (v; μ; λ; a)=ae λ(μ·v−1) . 
     
     
       3. The method of  claim 1 , further comprising:
 obtaining image data that represents the physical environment; and 
 determining the first SG lobe based on the image data. 
 
     
     
       4. The method of  claim 3 , wherein the image data includes a plurality of images associated with a plurality of poses. 
     
     
       5. The method of  claim 3 , wherein the image data includes a 360 degree image of the physical environment. 
     
     
       6. The method of  claim 1 , wherein each of the first plurality of sampling rays is associated with a distinct position within the first SG lobe. 
     
     
       7. The method of  claim 1 , wherein each of the first plurality of sampling rays is substantially parallel to the first SG lobe. 
     
     
       8. The method of  claim 1 , wherein the number of the first plurality of sampling rays is proportional to an intensity characteristic indicated by the first SG lobe. 
     
     
       9. The method of  claim 1 , wherein the number of the first plurality of sampling rays is based on a sharpness characteristic indicated by the first SG lobe. 
     
     
       10. The method of  claim 1 , wherein generating the first shadow includes tracing the first sampling ray against the depth value. 
     
     
       11. The method of  claim 1 , wherein the electronic device includes a rendering system and a depth buffer, the method further comprising:
 rendering, via the rendering system, the computer-generated object in order to generate an object render, wherein the rendering includes determining the depth value; and 
 storing the depth value in the depth buffer. 
 
     
     
       12. The method of  claim 11 , wherein generating the first shadow includes retrieving the depth value from the depth buffer. 
     
     
       13. The method of  claim 11 , further comprising selecting the first sampling ray according to a determination that the first sampling ray and the object render together satisfy an occlusion criterion. 
     
     
       14. The method of  claim 11 , further comprising:
 combining the object render with the first shadow in order to generate a combined render; 
 compositing the combined render with image data of the physical environment, in order to generate display data; and 
 displaying the display data on a display. 
 
     
     
       15. The method of  claim 1 , wherein generating the first shadow is further based on a second sampling ray of the first plurality of sampling rays. 
     
     
       16. The method of  claim 1 , further comprising:
 obtaining a second SG lobe that characterizes the ambient light from the physical environment, wherein the second SG lobe indicates a second directional characteristic associated with the ambient light, and wherein the first directional characteristic is different from the second directional characteristic; and 
 determining a second plurality of sampling rays based on the second directional characteristic; 
 wherein generating the first shadow is further based on a first sampling ray of the second plurality of sampling rays. 
 
     
     
       17. The method of  claim 1 , wherein the first directional characteristic is associated with a first portion of the ambient light from a first physical light source, the method further comprising:
 obtaining a second SG lobe that characterizes the ambient light from the physical environment, wherein the second SG lobe indicates a second directional characteristic associated with the ambient light, and wherein the second directional characteristic is associated with a second portion of the ambient light from a second physical light source that is different from the first physical light source; 
 determining a second plurality of sampling rays based on the second directional characteristic; and 
 generating a second shadow that is associated with the computer-generated object, based on the depth value and a first sampling ray of the second plurality of sampling rays. 
 
     
     
       18. An electronic device comprising:
 a sampling ray generator to:
 obtain a first SG lobe that characterizes ambient light from a physical environment, wherein the first SG lobe indicates a first directional characteristic associated with the ambient light; and 
 determine a first plurality of sampling rays based on the first directional characteristic; and 
 
 a shadow drawer to:
 obtain a depth value that is associated with a computer-generated object; and 
 determine a first shadow that is associated with the computer-generated object, based on the depth value and a first sampling ray, of the first plurality of sampling rays, from the sampling ray generator. 
 
 
     
     
       19. The electronic device of  claim 18 , wherein the electronic device further comprises:
 a rendering system to render the computer-generated object in order to determine the depth value; and 
 a depth buffer to store the depth value. 
 
     
     
       20. The electronic device of  claim 19 , wherein the shadow drawer obtains the depth value from the depth buffer. 
     
     
       21. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which, when executed by an electronic device, cause the electronic device to:
 obtain a first SG lobe that characterizes ambient light from a physical environment, wherein the first SG lobe indicates a first directional characteristic associated with the ambient light; 
 determine a first plurality of sampling rays based on the first directional characteristic; 
 obtain a depth value that is associated with a computer-generated object; and 
 generate a first shadow that is associated with the computer-generated object, based on the depth value and a first sampling ray of the first plurality of sampling rays.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application claims priority to U.S. Provisional Patent App. No. 63/188,260 filed on May 13, 2021, and hereby incorporated by reference in its entirety. 
    
    
     TECHNICAL FIELD 
     The present disclosure relates to generating shadows, and in particular generating a shadow associated with a computer-generated object. 
     BACKGROUND 
     Previously available techniques for generating shadows are often inaccurate and computationally expensive. For example, some techniques include generating a three-dimensional (3D) mesh for a computer-generated object, and tracing light rays against the mesh in order to determine a shadow for the computer-generated object. However, determining the shadow based on the 3D mesh is computationally expensive. As another example, some techniques include arbitrarily sampling across a plurality of directions, and tracing a light ray across the plurality of directions in order to determine a shadow, resulting in shadow inaccuracies and high system resource utilization. 
     SUMMARY 
     In accordance with some implementations, a method is performed at an electronic device with one or more processors and a non-transitory memory. The method includes obtaining a first spherical Gaussian (SG) lobe that characterizes ambient light from a physical environment. The first SG lobe indicates a first directional characteristic associated with the ambient light. The method includes determining a first plurality of sampling rays based on the first directional characteristic. The method includes obtaining a depth value that is associated with a computer-generated object. The method includes generating a shadow that is associated with the computer-generated object, based on the depth value and a first sampling ray of the first plurality of sampling rays. 
     In accordance with some implementations, an electronic device includes one or more processors and a non-transitory memory. The one or more programs are stored in the non-transitory memory and configured to be executed by the one or more processors and the one or more programs include instructions for performing or causing performance of the operations 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 an electronic device, cause the device to perform or cause performance of the operations of any of the methods described herein. In accordance with some implementations, an electronic device includes means for performing or causing performance of the operations of any of the methods described herein. In accordance with some implementations, an information processing apparatus, for use in an electronic device, includes means for performing or causing performance of the operations of any of the methods described herein. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       For a better understanding of the various described implementations, reference should be made to the Description, below, in conjunction with the following drawings in which like reference numerals refer to corresponding parts throughout the figures. 
         FIG.  1    is a block diagram of an example of a portable multifunction device in accordance with some implementations. 
         FIGS.  2 A- 2 I  are an example of generating shadows based on respective depth values and an SG lobe in accordance with some implementations. 
         FIGS.  3 A- 3 D  are an example of utilizing a plurality of SG lobes for generating different shadows in accordance with some implementations. 
         FIG.  4    is an example of a flow diagram of a method of generating a shadow based on an SG lobe and a depth value in accordance with some implementations. 
         FIG.  5    is an example of a flow diagram of a method of generating a shadow based on a plurality of SG lobes and a depth value in accordance with some implementations. 
     
    
    
     DESCRIPTION OF IMPLEMENTATIONS 
     Techniques for generating shadows are often inaccurate and computationally expensive. For example, one technique includes generating a three-dimensional (3D) mesh indicating a depth value, and tracing a light ray against the 3D mesh in order to determine a shadow based on the depth value. However, determining the shadow based on the 3D mesh is computationally expensive. For example, it is computationally expensive to test shadow rays against potentially thousands or millions of triangles in the 3D mesh. As another example, one technique includes arbitrarily sampling across a plurality of directions, and tracing a light ray across the plurality of directions in order to determine a shadow. Accordingly, determining the shadow based on the particular light ray includes a relatively large number of calculations, resulting in a high level of processor utilization. 
     By contrast, various implementations include methods, systems, and electronic devices that generate a shadow for a computer-generated object based on a depth value and a spherical Gaussian (SG) lobe. The SG lobe characterizes ambient light from a physical environment, such as light generated by a physical desk lamp or by the Sun. As used herein, “ambient light” may refer to light produced by direct or indirect light sources. The SG indicates a directional characteristic associated with the ambient light. In some implementations, a method includes determining the SG lobe based on a 360 degree image of the physical environment. For example, a neural network receives the 360 degree image and outputs a corresponding SG lobe. The method includes determining a plurality of sampling rays based on the directional characteristic. For example, each of the plurality of sampling rays is substantially parallel to the SG lobe. In some implementations, the method includes obtaining a plurality of SG lobes, and determines a plurality of sampling rays for each of the plurality of SG lobes. For example, in some implementations, ambient light from a physical environment includes light from multiple physical light sources (e.g., a street lamp, the Sun, etc.), and each of the multiple physical light sources is characterized by one or more SG lobes. Moreover, the method includes obtaining a depth value that is associated with a computer-generated object. To that end, in some implementations, the method includes generating the depth value during rendering the computer-generated object, and storing the depth value in a depth buffer for subsequent retrieval. For example, a rendering system, which may be integrated in a graphics processing unit (GPU), renders the computer-generated object. Thus, in contrast to other techniques, the method foregoes generating a 3D mesh of the environment, instead utilizing the depth value that is determined during rendering of the computer-generated object, thereby reducing resource utilization. Based on the depth value and at least one of the plurality of sampling rays, the method includes generating a shadow that is associated with the computer-generated object. In some implementations, generating the shadow includes tracing a sampling ray against the depth value. Accordingly, in contrast to other techniques that include tracing light rays in arbitrary directions, the method includes tracing the sampling ray based on a directional characteristic associated with the ambient light. Accordingly, the method includes generating a more accurate shadow for a computer-generated object, while using less system resources. 
     DESCRIPTION 
     Reference will now be made in detail to implementations, examples of which are illustrated in the accompanying drawings. In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the various described implementations. However, it will be apparent to one of ordinary skill in the art that the various described implementations may be practiced without these specific details. In other instances, well-known methods, procedures, components, circuits, and networks have not been described in detail so as not to unnecessarily obscure aspects of the implementations. 
     It will also be understood that, although the terms first, second, etc. are, in some instances, 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 contact could be termed a second contact, and, similarly, a second contact could be termed a first contact, without departing from the scope of the various described implementations. The first contact and the second contact are both contacts, but they are not the same contact, unless the context clearly indicates otherwise. 
     The terminology used in the description of the various described implementations herein is for the purpose of describing particular implementations only and is not intended to be limiting. As used in the description of the various described 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 “includes,” “including”, “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” is, optionally, construed to mean “when” or “upon” or “in response to determining” or “in response to detecting”, depending on the context. Similarly, the phrase “if it is determined” or “if [a stated condition or event] is detected” is, optionally, construed to mean “upon determining” or “in response to determining” or “upon detecting [the stated condition or event]” or “in response to detecting [the stated condition or event]”, depending on the context. 
     A physical environment refers to a physical world 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 one example, the XR system may detect head movement and, in response, adjust graphical content and an acoustic field presented to the person in a manner similar to how such views and sounds would change in a physical environment. As another example, the XR system may detect movement of the electronic device presenting the XR environment (e.g., a mobile phone, a tablet, a laptop, or the like) and, in response, adjust graphical content and an acoustic field presented 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 source, 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. 
       FIG.  1    is a block diagram of an example of a portable multifunction device  100  (sometimes also referred to herein as the “electronic device  100 ” for the sake of brevity) in accordance with some implementations. The electronic device  100  includes memory  102  (e.g., one or more non-transitory computer readable storage mediums), a memory controller  122 , one or more processing units (CPUs)  120 , a peripherals interface  118 , an input/output (I/O) subsystem  106 , a display system  112 , an inertial measurement unit (IMU)  130 , image sensor(s)  143  (e.g., camera), contact intensity sensor(s)  165 , audio sensor(s)  113  (e.g., microphone), eye tracking sensor(s)  164  (e.g., included within a head-mountable device (HMD)), an extremity tracking sensor  150 , and other input or control device(s)  116 . In some implementations, the electronic device  100  corresponds to one of a mobile phone, tablet, laptop, wearable computing device, head-mountable device (HMD), head-mountable enclosure (e.g., the electronic device  100  slides into or otherwise attaches to a head-mountable enclosure), or the like. In some implementations, the head-mountable enclosure is shaped to form a receptacle for receiving the electronic device  100  with a display. 
     In some implementations, the peripherals interface  118 , the one or more processing units  120 , and the memory controller  122  are, optionally, implemented on a single chip, such as a chip  103 . In some other implementations, they are, optionally, implemented on separate chips. 
     The I/O subsystem  106  couples input/output peripherals on the electronic device  100 , such as the display system  112  and the other input or control devices  116 , with the peripherals interface  118 . The I/O subsystem  106  optionally includes a display controller  156 , an image sensor controller  158 , an intensity sensor controller  159 , an audio controller  157 , an eye tracking controller  160 , one or more input controllers  152  for other input or control devices, an IMU controller  132 , an extremity tracking controller  180 , and a privacy subsystem  170 . The one or more input controllers  152  receive/send electrical signals from/to the other input or control devices  116 . The other input or control devices  116  optionally include physical buttons (e.g., push buttons, rocker buttons, etc.), dials, slider switches, joysticks, click wheels, and so forth. In some alternate implementations, the one or more input controllers  152  are, optionally, coupled with any (or none) of the following: a keyboard, infrared port, Universal Serial Bus (USB) port, stylus, finger-wearable device, and/or a pointer device such as a mouse. The one or more buttons optionally include a push button. In some implementations, the other input or control devices  116  includes a positional system (e.g., GPS) that obtains information concerning the location and/or orientation of the electronic device  100  relative to a particular object. In some implementations, the other input or control devices  116  include a depth sensor and/or a time-of-flight sensor that obtains depth information characterizing a physical object within a physical environment. In some implementations, the other input or control devices  116  include an ambient light sensor that senses ambient light from a physical environment and outputs corresponding ambient light data. 
     The display system  112  provides an input interface and an output interface between the electronic device  100  and a user. The display controller  156  receives and/or sends electrical signals from/to the display system  112 . The display system  112  displays visual output to the user. The visual output optionally includes graphics, text, icons, video, and any combination thereof (sometimes referred to herein as “computer-generated content”). In some implementations, some or all of the visual output corresponds to user interface objects. As used herein, the term “affordance” refers to a user-interactive graphical user interface object (e.g., a graphical user interface object that is configured to respond to inputs directed toward the graphical user interface object). Examples of user-interactive graphical user interface objects include, without limitation, a button, slider, icon, selectable menu item, switch, hyperlink, or other user interface control. 
     The display system  112  may have a touch-sensitive surface, sensor, or set of sensors that accepts input from the user based on haptic and/or tactile contact. The display system  112  and the display controller  156  (along with any associated modules and/or sets of instructions in the memory  102 ) detect contact (and any movement or breaking of the contact) on the display system  112  and converts the detected contact into interaction with user-interface objects (e.g., one or more soft keys, icons, web pages or images) that are displayed on the display system  112 . In an example implementation, a point of contact between the display system  112  and the user corresponds to a finger of the user or a finger-wearable device. 
     The display system  112  optionally uses LCD (liquid crystal display) technology, LPD (light emitting polymer display) technology, or LED (light emitting diode) technology, although other display technologies are used in other implementations. The display system  112  and the display controller  156  optionally detect contact and any movement or breaking thereof using any of a plurality of touch sensing technologies now known or later developed, including but not limited to capacitive, resistive, infrared, and surface acoustic wave technologies, as well as other proximity sensor arrays or other elements for determining one or more points of contact with the display system  112 . 
     The user optionally makes contact with the display system  112  using any suitable object or appendage, such as a stylus, a finger-wearable device, a finger, and so forth. In some implementations, the user interface is designed to work with finger-based contacts and gestures, which can be less precise than stylus-based input due to the larger area of contact of a finger on the touch screen. In some implementations, the electronic device  100  translates the rough finger-based input into a precise pointer/cursor position or command for performing the actions desired by the user. 
     Audio circuitry also receives electrical signals converted by the audio sensors  113  (e.g., a microphone) from sound waves. Audio circuitry converts the electrical signal to audio data and transmits the audio data to the peripherals interface  118  for processing. Audio data is, optionally, retrieved from and/or transmitted to the memory  102  and/or RF circuitry by the peripherals interface  118 . In some implementations, audio circuitry also includes a headset jack. The headset jack provides an interface between audio circuitry and removable audio input/output peripherals, such as output-only headphones or a headset with both output (e.g., a headphone for one or both ears) and input (e.g., a microphone). 
     The inertial measurement unit (IMU)  130  includes accelerometers, gyroscopes, and/or magnetometers in order measure various forces, angular rates, and/or magnetic field information with respect to the electronic device  100 . Accordingly, according to various implementations, the IMU  130  detects one or more positional change inputs of the electronic device  100 , such as the electronic device  100  being shaken, rotated, moved in a particular direction, and/or the like. 
     The image sensor(s)  143  capture still images and/or video. In some implementations, an image sensor  143  is located on the back of the electronic device  100 , opposite a touch screen on the front of the electronic device  100 , so that the touch screen is enabled for use as a viewfinder for still and/or video image acquisition. In some implementations, another image sensor  143  is located on the front of the electronic device  100  so that the user&#39;s image is obtained (e.g., for selfies, for videoconferencing while the user views the other video conference participants on the touch screen, etc.). In some implementations, the image sensor(s) are integrated within an HMD. For example, the image sensor(s)  143  output image data that represents a physical object (e.g., a physical agent) within a physical environment. 
     The contact intensity sensors  165  detect intensity of contacts on the electronic device  100  (e.g., a touch input on a touch-sensitive surface of the electronic device  100 ). The contact intensity sensors  165  are coupled with the intensity sensor controller  159  in the I/O subsystem  106 . The contact intensity sensor(s)  165  optionally include one or more piezoresistive strain gauges, capacitive force sensors, electric force sensors, piezoelectric force sensors, optical force sensors, capacitive touch-sensitive surfaces, or other intensity sensors (e.g., sensors used to measure the force (or pressure) of a contact on a touch-sensitive surface). The contact intensity sensor(s)  165  receive contact intensity information (e.g., pressure information or a proxy for pressure information) from the physical environment. In some implementations, at least one contact intensity sensor  165  is collocated with, or proximate to, a touch-sensitive surface of the electronic device  100 . In some implementations, at least one contact intensity sensor  165  is located on the side of the electronic device  100 . 
     The eye tracking sensor(s)  164  detect an eye gaze of a user of the electronic device  100  and generate eye tracking data indicative of a gaze position of the user. In various implementations, the eye tracking data includes data indicative of a fixation point (e.g., point of regard) of the user on a display panel, such as a display panel within a head-mountable device (HMD), a head-mountable enclosure, or within a heads-up display. 
     The extremity tracking sensor  150  obtains extremity tracking data indicative of a position of an extremity of a user. For example, in some implementations, the extremity tracking sensor  150  corresponds to a hand tracking sensor that obtains hand tracking data indicative of a position of a hand or a finger of a user within a particular object. In some implementations, the extremity tracking sensor  150  utilizes computer vision techniques to estimate the pose of the extremity based on camera images. 
     In various implementations, the electronic device  100  includes a privacy subsystem  170  that includes one or more privacy setting filters associated with user information, such as user information included in extremity tracking data, eye gaze data, and/or body position data associated with a user. In some implementations, the privacy subsystem  170  selectively prevents and/or limits the electronic device  100  or portions thereof from obtaining and/or transmitting the user information. To this end, the privacy subsystem  170  receives user preferences and/or selections from the user in response to prompting the user for the same. In some implementations, the privacy subsystem  170  prevents the electronic device  100  from obtaining and/or transmitting the user information unless and until the privacy subsystem  170  obtains informed consent from the user. In some implementations, the privacy subsystem  170  anonymizes (e.g., scrambles or obscures) certain types of user information. For example, the privacy subsystem  170  receives user inputs designating which types of user information the privacy subsystem  170  anonymizes. As another example, the privacy subsystem  170  anonymizes certain types of user information likely to include sensitive and/or identifying information, independent of user designation (e.g., automatically). 
       FIGS.  2 A- 2 I  are an example of generating shadows based on respective depth values and an SG lobe in accordance with some implementations. As illustrated in  FIG.  2 A , a physical environment  200  includes a first wall  202 , a second wall  204 , a physical lamp  230 , and a user  50  holding an electronic device  210 . The physical lamp  230  emits ambient light  232  within the physical environment  200 . The electronic device  210  includes a display  212  that is associated with a viewable region  214  of the physical environment  200 . The viewable region  214  includes a portion of the first wall  202  and a portion of the second wall  204 . 
     In some implementations, the electronic device  210  corresponds to a head-mountable device (HMD) that includes an integrated display (e.g., a built-in display) that displays a representation of the physical environment  200 . For example, the electronic device  210  displays, on the display  212 , a computer-generated object that is overlaid on a portion of the physical environment  200 . To that end, in some implementations, the electronic device  210  displays an XR environment. In some implementations, the electronic device  210  includes a head-mountable enclosure. In various implementations, the head-mountable enclosure includes an attachment region to which another device with a display can be attached. In various implementations, the head-mountable enclosure is shaped to form a receptacle for receiving another device that includes a display (e.g., the electronic device  210 ). For example, in some implementations, the electronic device  210  slides/snaps into or otherwise attaches to the head-mountable enclosure. In some implementations, the display of the device attached to the head-mountable enclosure presents (e.g., displays) the representation of the physical environment  200 . For example, in some implementations, the electronic device  210  corresponds to a mobile phone that can be attached to the head-mountable enclosure. 
     In some implementations, the electronic device  210  includes an image sensor, such as a scene camera. For example, with references to  FIGS.  2 B and  2 C , the electronic device  210  includes an image sensor  233 . The image sensor  233  senses (e.g., captures) the ambient light  232  from the physical environment  200 , and outputs image data  234  of the physical environment  200 . The image data  234  may correspond to an image or a sequence of images (e.g., a video stream). According to various implementations, the electronic device  210  composites, via a compositing system  219 , the image data  234  with various object renders in order to generate display data to be displayed on the display  212 . 
     In some implementations, the electronic device  210  includes a see-through display. The see-through display permits ambient light from the physical environment  200  through the see-through display, and the representation of the physical environment is a function of the ambient light. In some implementations, the see-through display is an additive display that enables optical see-through of the physical surface, such as an optical HMD (OHMD). For example, unlike purely compositing using the image data  234 , the see-through display is capable of reflecting projected images off of the display while enabling a user to see through the display. 
     Referring to  FIG.  2 B , the electronic device  210  renders, via a rendering system  216 , a first computer-generated cube  240  (e.g., XR content) in order to generate a first cube render  242 . For example, the rendering system  216  is integrated in a GPU. The rendering system  216  includes a depth value generator  217 . While rendering the first-computer generated cube  240 , the depth value generator  217  determines a first depth value  244  associated with the first-computer generated cube  240 . For example, the first depth value  244  indicates a depth of the first-computer generated cube  240  within a scene, such that a higher depth value indicates that the first-computer generated cube  240  is positioned nearer to the background of the scene, and vice versa for a lower depth value. In some implementations, the electronic device  210  includes a depth buffer  218 , and the electronic device  210  stores the first depth value  244  in the depth buffer  218 . Utilization of the depth buffer  218  for generating shadows will be described with reference to  FIGS.  2 E and  2 F . Moreover, in some implementations, the electronic device  210  includes a compositing system  219  that composites the image data  234  with the first cube render  242 , in order to generate display data that is displayed on the display  212 , as illustrated in  FIG.  2 D . 
     Referring to  FIG.  2 C , the electronic device  210  renders, via the rendering system  216 , a second computer-generated cube  250  (e.g., XR content) in order to generate a second cube render  252 . Rendering the second computer-generated cube  250  includes determining a second depth value  254  associated with the second computer-generated cube  250 . The second depth value  254  is greater than the first depth value  244 , as is illustrated in  FIG.  2 D . Moreover, the electronic device  210  stores the second depth value  254  in the depth buffer  218 . The rendering system  216  may render the first computer-generated cube  240  and the second computer-generated cube  250  during a common rendering cycle, or during separate rendering cycles. Moreover, the compositing system  219  composites the image data  234  with the second cube render  252  in order to generate display data that is displayed on the display  212 , as illustrated in  FIG.  2 D . 
     As illustrated in  FIG.  2 D , the electronic device  210  displays the display data on the display  212 . The display data includes the first cube render  242  and the second cube render  252 , composited with the image data  234 . The image data  234  represents a portion of the physical environment  200 . The portion of the physical environment  200  includes a portion of the first wall  202  and a portion of the second wall  204 , based on the current viewable region  214 . Accordingly, the first cube render  242  and the second cube render  252  appear as displayed overlaid respective portions of the physical environment  200 . 
     The first depth value  244  and the second depth value  254  are illustrated in  FIG.  2 D  for purely explanatory purposes. The first depth value  244  is less than the second depth value  254 , and thus the first cube render  242  appears closer to the display  212  than does the second cube render  252 . Accordingly, the first cube render  242  appears farther from the first wall  202  than does the second cube render  252 . 
     As illustrated in  FIG.  2 E , according to various implementations, the electronic device  210  includes components for generating and displaying a first shadow  246  and a second shadow  256 . The first shadow  246  and the second shadow  256  are respectively associated with the first computer-generated cube  240  and the second computer-generated cube  250 . Each of the first shadow  246  and the second shadow  256  is based on the ambient light  232 , which is characterized by a Spherical Gaussian (SG) lobe  264 . To that end, in some implementations, the electronic device  210  includes a shadow generator  260 , an SG lobe generator  263 , and a combiner  266 . 
     The shadow generator  260  determines the first shadow  246  and the second shadow  256 , based on the SG lobe  264  and respective depth values  244 / 254 . The SG lobe  264  indicates a directional characteristic associated with the ambient light  232 . Details regarding the shadow generator  260  determining the first shadow  246  and the second shadow  256  are described with reference to  FIGS.  2 F- 2 H . The SG lobe  264  is associated with a Spherical Gaussian (SG) function, which may be a standard Gaussian function defined on a surface of a sphere. For example, an SG function, denoted G (v; μ; λ; a), corresponds to: G (v; μ; λ; a)=ae λ(μ·v−1)    
     The SG function characterizes the ambient light  232 , and the parameters (v; μ; λ; a) of the SG function affect the shape and location of the SG lobe  264 . The parameter ‘μ’ corresponds to a unit vector that indicates the axis or direction associated with the SG lobe  264 , such as a location of the SG lobe  264  on a surface of a sphere. For example, the parameter ‘μ’ indicates the directional characteristic associated with the ambient light  232 . The parameter ‘μ’ may effectively point to the center of the SG lobe  264 . In some implementations, the parameter ‘μ’ is represented by a three dimensional (3D) XYZ directional value. The parameter ‘a’ corresponds to the amplitude or intensity associated with the SG lobe  264 . In some implementations, the amplitude is represented by a scalar value. In some implementations, the amplitude is represented by an RGB color value. The parameter ‘λ’ corresponds to the sharpness associated with the SG lobe  264 . For example, a larger ‘λ’ value corresponds to a narrower SG lobe, resulting in a faster decrease from the axis associated with the SG lobe  264  (as compared with a smaller ‘λ’ value). 
     In various implementations, the SG lobe generator  263  generates the SG lobe  264  based on the image data  234 . For example, in some implementations, the image data  234  corresponds to a 360 degree image of the physical environment  200 , and the SG lobe generator  263  includes a neural network that determines the SG lobe  264  based on the 360 degree image. 
     The combiner  266  combines an object render with a corresponding shadow in order to generate a combined render  268 . Namely, the combiner  266  combines the first cube render  242  with the first shadow  246 , and combines the second cube render  252  with the second shadow  256 , in order to generate the combined render  268 . The compositing system  219  composites the combined render  268  with the image data  234  in order to generate display data  269 . The display data  269  is displayed on the display  212 , as illustrated in  FIG.  2 I . 
     As illustrated in  FIG.  2 F , the shadow generator  260  determines the first shadow  246  and the second shadow  256 , based on the SG lobe  264  and respective depth values  244 / 254 . To that end, in some implementations, the shadow generator  260  includes a sampling ray generator  270 , a ray selector  274 , and a shadow drawer  280 . 
     The sampling ray generator  270  obtains the SG lobe  264 . A graphical representation of the SG lobe  264 , on a corresponding SG  262 , is illustrated in  FIG.  2 G . Referring back to  FIG.  2 A , the physical lamp  230  is positioned behind and to the right of the electronic device  210  within the physical environment  200 . Accordingly, the directional characteristic associated with the SG lobe  264  (e.g., the position of the SG lobe  264 ) is also towards the bottom right of the SG  262 , as illustrated in  FIG.  2 G . The sampling ray generator  270  determines a plurality of sampling rays  272 - 1 , . . . ,  272 -N based on the directional characteristic. For example, as illustrated in  FIG.  2 G , each of the plurality of sampling rays  272 - 1 , . . . ,  272 -N is substantially parallel to the SG lobe  264 . One of ordinary skill in the art will appreciate that the number of the plurality of sampling rays  272 - 1 , . . . ,  272 -N may vary according to different implementations. For example, the number of the plurality of sampling rays  272 - 1 , . . . ,  272 -N is between 16 and 64. 
     The ray selector  274  selects at least a portion of plurality of sampling rays  272 - 1 , . . . ,  272 -N. For example, with reference to  FIG.  2 F , the ray selector  274  selects a first sampling ray  272 - 1  based on the first depth value  244 , and selects a second sampling ray  272 - 2  based on the second depth value  254 . As described with reference to  FIGS.  2 B and  2 C , the electronic device  210  determines the first depth value  244  and the second depth value  254  during rendering of the first computer-generated cube  240  and the second computer-generated cube  250 , respectively. Moreover, the electronic device  210  stores the first depth value  244  and the second depth value  254  in the depth buffer  218 . During ray selection, the ray selector  274  obtains the first depth value  244  and the second depth value  254  from the depth buffer  218 , and selects appropriate sampling rays based on the depth values. In some implementations, the selected portion of the plurality of sampling rays  272 - 1 , . . . ,  272 -N and a corresponding object render together satisfy an occlusion criterion. For example, as illustrated in  FIG.  2 H  and with reference back to  FIG.  2 D , the first sampling ray  272 - 1  and the first cube render  242  satisfy the occlusion criterion based on intersection between the first sampling ray  272 - 1  and the first cube render  242 . Moreover, the second sampling ray  272 - 2  and the second cube render  252  satisfy the occlusion criterion based on intersection between the second sampling ray  272 - 2  and the second cube render  252 . 
     The shadow drawer  280  generates the first shadow  246  (associated with the first computer-generated cube  240 ) based on the first sampling ray  272 - 1  and the first depth value  244 . Moreover, the shadow drawer  280  generates the second shadow  256  (associated with the second computer-generated cube  250 ) based on the second sampling ray  272 - 2  and the second depth value  254 . To that end, in some implementations, generating a shadow includes tracing one or more sampling ray(s) against a corresponding depth value. For example, the shadow drawer  280  traces the first sampling ray  272 - 1  against the first depth value  244  in order to generate the first shadow  246 . As another example, the shadow drawer  280  traces the second sampling ray  272 - 2  against the second depth value  254  in order to generate the second shadow  256 . Accordingly, in contrast to other systems that arbitrarily sample light rays (e.g., guess direction of the ambient light), the electronic device  210  uses the directional characteristic associated with the SG lobe  264  in order to efficiently trace sampling rays. The electronic device  210 , therefore, performs fewer tracing operations in order to generate a photorealistic shadow. 
     As illustrated in  FIG.  2 I , the display  212  displays the first shadow  246  for the first cube render  242 , and displays the second shadow  256  for the second cube render  252 . The respective positions of the first shadow  246  and the second shadow  256  are based on the first sampling ray  272 - 1  and the second sampling ray  272 - 2 . Because the second cube render  252  is nearer to the first wall  202 , the second shadow  256  is smaller and has a sharper appearance, as compared with the first shadow  246 . The difference in sharpness is indicated by different respective hatch patterns for the first shadow  246  and the second shadow  256 . 
       FIGS.  3 A- 3 D  are an example of utilizing a plurality of SG lobes for generating different shadows in accordance with some implementations. As illustrated in  FIG.  3 A , a physical environment  300  includes the user  50  holding the electronic device  210 . The electronic device  210  is outside at daytime, and thus the physical environment  300  includes the Sun  302 . The Sun  302  emits a first portion of ambient light  340   a  towards the electronic device  210 . The physical environment  300  also includes a physical street lamp  304  that emits a second portion of ambient light  340   b  towards the electronic device  210 . Because of the relative proximity of the physical street lamp  304  to the electronic device  210 , the second portion of ambient light  340   b  is brighter (e.g., has a higher luminance) than the first portion of ambient light  340   a  from the Sun  302 . Moreover, the electronic device  210  has rendered, via a rendering system, a computer-generated cube in order to generate a cube render  320 , including determining a depth value  322  associated with the computer-generated cube. The display  212  displays the cube render  320 , as shown in  FIG.  3 A . 
     As illustrated in  FIGS.  3 B and  3 C , the electronic device  210  obtains a first SG lobe  332  of an SG  330 , and obtains a second SG lobe  336  of the SG  330 . The first SG lobe  332  characterizes the first portion of ambient light  340   a  from the Sun  302 , and the second SG lobe  336  characterizes the second portion of ambient light  340   b  from the physical street lamp  304 . The electronic device  210  determines, via the sampling ray generator  270 , a first plurality of sampling rays associated with the first SG lobe  332 , based on a first directional characteristic associated with the first SG lobe  332 . Moreover, the electronic device  210  determines, via the sampling ray generator  270 , a second plurality of sampling rays associated with the second SG lobe  336 , based on a second directional characteristic associated with the second SG lobe  336 . 
     In some implementations, the electronic device  210  selects, via the ray selector  274 , a first portion  334  of the first plurality of sampling rays and a second portion  338  of the second plurality of sampling rays. In some implementations, the number of selected sampling rays is based on a corresponding intensity of the SG lobe, as indicated by a corresponding SG function. For example, as illustrated in  FIGS.  3 B and  3 C , the second portion  338  of the second plurality of sampling rays includes more sampling rays than the first portion  334  of the first plurality of sampling rays, because the second portion of ambient light  340   b  from the physical street lamp  304  is more intense (e.g., brighter) than the first portion of ambient light  340   a  from the Sun  302 . 
     The electronic device  210  generates, via the shadow drawer  280 , a first shadow  350  associated with the first portion of ambient light  340   a , and a second shadow  352  associated with the second portion of ambient light  340   b . The first shadow  350  is generated based on the depth value  322  and the first portion  334  of the first plurality of sampling rays. The second shadow  352  is generated based on the depth value  322  and the second portion  338  of the second plurality of sampling rays. For example, generating a particular shadow includes tracing respective sampling rays towards the cube render  320 , based on a function of the depth value  322 . As illustrated in  FIG.  3 D , the display  212  displays the cube render  320 , the first shadow  350 , and the second shadow  352 . Because of the relatively high intensity of the second portion of ambient light  340   b , the corresponding second shadow  352  is sharper than the first shadow  350 , which is associated with the first portion of ambient light  340   a . Additionally, the first shadow  350  is longer than the second shadow  352  because the Sun  302  is farther from the electronic device  210  than the physical street lamp  304  is from the electronic device  210 . 
       FIG.  4    is an example of a flow diagram of a method  400  of generating a shadow based on an SG lobe and a depth value in accordance with some implementations. In various implementations, the method  400  or portions thereof are performed by an electronic device (e.g., the electronic device  210 ). In various implementations, the method  400  or portions thereof are performed by a mobile device, such as a smartphone, tablet, or wearable device. In various implementations, the method  400  or portions thereof are performed by a head-mountable device (HMD) including a display. In some implementations, the method  400  is performed by processing logic, including hardware, firmware, software, or a combination thereof. In some implementations, the method  400  is performed by a processor executing code stored in a non-transitory computer-readable medium (e.g., a memory). 
     As represented by block  402 , the method  400  includes obtaining a first SG lobe that characterizes ambient light from a physical environment. The first SG lobe indicates a first directional characteristic associated with the ambient light. For example, with reference to  FIGS.  2 A and  2 G , the electronic device  210  obtains the SG lobe  264 , which is associated with the ambient light  232  produced by the physical lamp  230 . In some implementations, the first SG lobe further indicates an intensity characteristic and/or a sharpness characteristic associated with the ambient light. In some implementations, the first SG lobe is characterized by an SG function G (v; μ; λ; a)=ae λ(μ·v−1) . 
     As represented by block  404 , in some implementations, obtaining the first SG lobe includes determining the first SG lobe based on image data that represents the physical environment. For example, with reference to  FIGS.  2 E , the image sensor  233  captures ambient light  232  from the physical environment  200 , and outputs the image data  234  to the SG lobe generator  264 , which determines the SG lobe  264  based on the image data  234 . In some implementations, the image data includes a plurality of images associated with a plurality of poses. In some implementations, the image data includes a 360 degree image of the physical environment. For example, with reference to  FIG.  2 A , while the image sensor  233  is activated, the user  50  rotates the electronic device  210  in order to capture a 360 degree image of the physical environment  200 . 
     As represented by block  406 , the method  400  includes determining a first plurality of sampling rays based on the first directional characteristic. As represented by block  408 , in some implementations, each of the plurality of sampling rays is substantially parallel to the first SG lobe. For example, with reference to  FIGS.  2 F and  2 G , the sampling ray generator  270  determines a plurality of sampling rays  272 - 1 , . . . ,  272 -N, based on a directional characteristic indicated by the SG lobe  264 . Continuing with this example, the directional characteristic indicates a position of the SG lobe  264  on the SG  262 . In some implementations, each of the first plurality of sampling rays is associated with a distinct position on the first SG lobe. 
     As represented by block  410 , in some implementations, the method  400  includes rendering, via the rendering system, the computer-generated object in order to generate an object render. The rendering system may be integrated in a GPU. The computer-generated object may correspond to a 2D or a 3D object, such as an object model. Rendering the computer-generated object includes determining a depth value that is associated with the computer-generated object. Moreover, the method  400  may include storing the depth value in a depth buffer. For example, with reference to  FIG.  2 B , the rendering system  216 , while rendering the first computer-generated cube  240 , determines the first depth value  244 . Moreover, the electronic device  210  stores the first depth value  244  in the depth buffer  218 . 
     As represented by block  412 , the method  400  includes obtaining the depth value that is associated with the computer-generated object. As represented by block  414 , in some implementations, obtaining the depth value includes retrieving the depth value from the depth buffer. For example, with reference to  FIG.  2 E , the shadow generator  260  obtains the first depth value  244  from the depth buffer  218 . Accordingly, an electronic device retrieves the depth value that is determined as part of the standard rendering process. Retrieving the depth value from the depth buffer enables an electronic device to avoid performing additional depth information calculations, such as a determination of a 3D mesh performed by other systems. 
     As represented by block  416 , in some implementations, the method  400  includes selecting a first sampling ray of the first plurality of sampling rays according to a determination that the first sampling ray and the object render together satisfy an occlusion criterion. For example, with reference to  FIGS.  2 D and  2 H , the first sampling ray  272 - 1  and the first cube render  242  satisfy the occlusion criterion based on intersection between the first sampling ray  272 - 1  and the first cube render  242 . 
     As represented by block  418 , the method  400  includes generating a first shadow that is associated with the computer-generated object, based on the depth value and a first sampling ray of the first plurality of sampling rays. To that end, in some implementations, the method  400  includes tracing the first sampling ray against the depth value, as represented by block  420 . In other words, the depth value may be used as a proxy for tracing the first sampling ray. For example, with reference to  FIGS.  2 H and  2 I , the electronic device  210  uses the first sampling ray  272 - 1  and the first depth value  244  in order to generate and display display data that includes a first shadow  246 . The first shadow  246  represents a real-world shadow that would be cast by a physical approximation of the first computer-generated cube  240 , such as a physical cube. Details regarding generation of the display data are described with reference to blocks  424  and  426 . As represented by block  422 , in some implementations, generating the first shadow is further based on a second sampling ray of the first plurality of sampling rays. 
     As represented by block  424 , in some implementations, the method  400  includes combining the object render with the first shadow in order to generate a combined render, and compositing the combined render with image data of the physical environment in order to generate the display data. For example, with reference to  FIG.  2 E , the combiner  266  combines first and second cube renders  242  and  252  with respective first and second shadows  246  and  256 , in order to generate the combined render  268 . Moreover, the compositing system  219  composites the combined render  268  with the image data  234  in order to generate the display data  269 . As represented by block  426 , in some implementations, the method  400  includes displaying the display data on a display, such as on the display  212  illustrated in  FIG.  2 I . 
       FIG.  5    is an example of a flow diagram of a method  500  of generating a shadow based on a plurality of SG lobes and a depth value in accordance with some implementations. In various implementations, the method  500  or portions thereof are performed by an electronic device (e.g., the electronic device  210 ). In various implementations, the method  500  or portions thereof are performed by a mobile device, such as a smartphone, tablet, or wearable device. In various implementations, the method  500  or portions thereof are performed by an HMD including a display. In some implementations, the method  500  is performed by processing logic, including hardware, firmware, software, or a combination thereof. In some implementations, the method  500  is performed by a processor executing code stored in a non-transitory computer-readable medium (e.g., a memory). 
     As represented by block  502 , in some implementations, the method  500  includes obtaining a plurality of SG lobes. In some implementations, as represented by block  504 , each of the plurality of SG lobes indicates a respective directional characteristic associated with ambient light from a physical environment. 
     As represented by block  506 , in some implementations, the plurality of SGlobes may be associated with a particular physical light source. For example, the method  500  includes obtaining a first SG lobe that characterizes a first portion of ambient light produced by a particular physical light source, and obtaining a second SG lobe that characterizes a second portion of the ambient light produced by the particular physical light source. Continuing with this example, the first SG lobe indicates a first directional characteristic, and the second SG lobe indicates a second directional characteristic that is different from the first directional characteristic. The number of SG lobes associated with a particular physical light source may be proportional to the complexity of the particular physical light source. 
     As another example, as represented by block  508 , the plurality of SG lobes may be associated with different physical light sources. Because each of the plurality of SG lobes is localized, each SG lobe may quantify a different physical light source. Moreover, the amplitude (e.g., RGB value) and sharpness value associated with a particular SG lobe can be independently adjusted. For example, with reference to  FIGS.  3 A- 3 C , the first SG lobe  332  characterizes the first portion of the ambient light  340   a  from the Sun  302 , and the second SG lobe  336  characterizes the second portion of the ambient light  340   b  from the physical street lamp  304 . Accordingly, in some implementations, each of the plurality of SG lobes characterizes a distinct physical light source. In some implementations, each of a plurality of physical light sources is characterized by multiple SG lobes. In some implementations, the method  500  includes obtaining a single SG lobe for a less complex light source, and multiple SG lobes for a more complex light source. 
     As represented by block  510 , in some implementations, the method  500  includes determining a respective plurality of sampling rays for each of the plurality of SG lobes. In some implementations, the number of a plurality of sampling rays for a particular SG lobe is proportional to an intensity characteristic indicated by the particular SG lobe. In other words, more sampling rays may be used for a brighter physical light source. For example, an electronic device determines  16  sampling rays based on a first SG lobe associated with the Sun, and determines  64  sampling rays based on a second SG lobe associated with a physical fluorescent lamp. In some implementations, the number of a plurality of sampling rays for a particular SG lobe is based on a sharpness or softness characteristic indicated by a particular SG lobe. For example, the method  500  utilizes fewer sampling rays for a narrower (e.g., sharper) SG lobe than for a wider SG lobe, because the narrower SG lobe is associated with a sharper shadow boundary. The width of a penumbra associated with a particular SG lobe is based on geometry involved in the light transport. For example, the width of a penumbra is based on the size of a physical light source, and the distances between the light, the occluder, and physical surface on which a shadow is cast. In some implementations, the number of a plurality of sampling rays for a particular SG lobe is based on a combination of an intensity characteristic indicated by a particular SG lobe, and a sharpness/softness characteristic indicated by the particular SG lobe. 
     As represented by block  512 , the method  500  includes obtaining the depth value that is associated with a computer-generated object, such as is described with reference to block  412 . As represented by block  514 , the method  500  includes generating a shadow that is associated with the computer-generated object, based on a portion of the respective plurality of sampling rays. For example, with reference to  FIGS.  3 B and  3 C , the electronic device  210  selects three sampling rays based on the first SG lobe  332 , and selects six sampling rays based on the second SG lobe  336 . Accordingly, with reference to  FIG.  3 D , the electronic device  210  generates the first shadow  350  based on the three sampling rays, and generates the second shadow  352  based on the six sampling rays. 
     The present disclosure describes various features, no single one of which is solely responsible for the benefits described herein. It will be understood that various features described herein may be combined, modified, or omitted, as would be apparent to one of ordinary skill. Other combinations and sub-combinations than those specifically described herein will be apparent to one of ordinary skill, and are intended to form a part of this disclosure. Various methods are described herein in connection with various flowchart steps and/or phases. It will be understood that in many cases, certain steps and/or phases may be combined together such that multiple steps and/or phases shown in the flowcharts can be performed as a single step and/or phase. Also, certain steps and/or phases can be broken into additional sub-components to be performed separately. In some instances, the order of the steps and/or phases can be rearranged and certain steps and/or phases may be omitted entirely. Also, the methods described herein are to be understood to be open-ended, such that additional steps and/or phases to those shown and described herein can also be performed. 
     Some or all of the methods and tasks described herein may be performed and fully automated by a computer system. The computer system may, in some cases, include multiple distinct computers or computing devices (e.g., physical servers, workstations, storage arrays, etc.) that communicate and interoperate over a network to perform the described functions. Each such computing device typically includes a processor (or multiple processors) that executes program instructions or modules stored in a memory or other non-transitory computer-readable storage medium or device. The various functions disclosed herein may be implemented in such program instructions, although some or all of the disclosed functions may alternatively be implemented in application-specific circuitry (e.g., ASICs or FPGAs or GP-GPUs) of the computer system. Where the computer system includes multiple computing devices, these devices may be co-located or not co-located. The results of the disclosed methods and tasks may be persistently stored by transforming physical storage devices, such as solid-state memory chips and/or magnetic disks, into a different state. 
     Various processes defined herein consider the option of obtaining and utilizing a user&#39;s personal information. For example, such personal information may be utilized in order to provide an improved privacy screen on an electronic device. However, to the extent such personal information is collected, such information should be obtained with the user&#39;s informed consent. As described herein, the user should have knowledge of and control over the use of their personal information. 
     Personal information will be utilized by appropriate parties only for legitimate and reasonable purposes. Those parties utilizing such information will adhere to privacy policies and practices that are at least in accordance with appropriate laws and regulations. In addition, such policies are to be well-established, user-accessible, and recognized as in compliance with or above governmental/industry standards. Moreover, these parties will not distribute, sell, or otherwise share such information outside of any reasonable and legitimate purposes. 
     Users may, however, limit the degree to which such parties may access or otherwise obtain personal information. For instance, settings or other preferences may be adjusted such that users can decide whether their personal information can be accessed by various entities. Furthermore, while some features defined herein are described in the context of using personal information, various aspects of these features can be implemented without the need to use such information. As an example, if user preferences, account names, and/or location history are gathered, this information can be obscured or otherwise generalized such that the information does not identify the respective user. 
     The disclosure is not intended to be limited to the implementations shown herein. Various modifications to the implementations described in this disclosure may be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other implementations without departing from the spirit or scope of this disclosure. The teachings of the invention provided herein can be applied to other methods and systems, and are not limited to the methods and systems described above, and elements and acts of the various implementations described above can be combined to provide further implementations. Accordingly, the novel methods and systems described herein may be implemented in a variety of other forms; furthermore, various omissions, substitutions and changes in the form of the methods and systems described herein may be made without departing from the spirit of the disclosure. The accompanying claims and their equivalents are intended to cover such forms or modifications as would fall within the scope and spirit of the disclosure.

Metadata:
Filing Date: 20220323
Publication Date: 20250114
Grant Date: 20250114
Priority Date: 20210513
Inventors: NAGY, GABOR
Assignee: APPLE INC
CPC Classifications: [{"code": "G06T2215/12", "inventive": false, "first": false, "tree": "[]"}, {"code": "G06T15/60", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06T15/06", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06T15/506", "inventive": true, "first": true, "tree": "[]"}, {"code": "G06T15/06", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06T15/60", "inventive": true, "first": true, "tree": "[]"}, {"code": "G06T15/06", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06T15/60", "inventive": true, "first": true, "tree": "[]"}]
Family ID: 94212648