PATENT DOCUMENT

Publication Number: US-11955099-B2
Application Number: US-202318099436-A
Country: US
Kind Code: B2

Title: Color correction based on perceptual criteria and ambient light chromaticity

Abstract:
Various implementations disclosed herein include methods, electronic devices, and systems for performing perceptual-based color correction based on chromaticity values. To that end, in some implementations, a method is performed at an electronic device with one or more processors, a non-transitory memory, and a see-through display. The method includes determining a chromaticity value associated with ambient light from a physical environment. The chromaticity value quantifies the ambient light. The method includes determining a set of color correction values based on a function of the chromaticity value and image data. The set of color correction values and the chromaticity value together satisfy one or more perceptual criteria. The method includes modifying the image data in order to generate display data based on a function of the set of color correction values. The method includes displaying the display data on the see-through display.

Claims:
What is claimed: 
     
       1. A method comprising:
 at an electronic device including one or more processors, a non-transitory memory, and a see-through display:
 determining a chromaticity value associated with ambient light from a physical environment, wherein the chromaticity value quantifies the ambient light; 
 determining a set of color correction values based on a function of the chromaticity value and image data, wherein the set of color correction values and the chromaticity value together satisfy one or more perceptual criteria; 
 obtaining a plurality of semantic values respectively associated with a plurality of portions of the image data, wherein the plurality of portions includes a first portion of the image data and a second portion of the image data; 
 identifying a first one of the plurality of semantic values that satisfies a criterion, wherein the first one of the plurality of semantic values is associated with the first portion of the image data; 
 modifying the image data in order to generate display data based on a function of the set of color correction values, wherein modifying the image data includes modifying the first portion of the image data; and 
 displaying the display data on the see-through display. 
 
 
     
     
       2. The method of  claim 1 , wherein modifying the image data includes color mapping a portion of the image data in order to match a corresponding portion of the set of color correction values within a performance threshold. 
     
     
       3. The method of  claim 1 , wherein modifying the image data includes performing a tone mapping operation with respect to a portion of the image data. 
     
     
       4. The method of  claim 3 , wherein the tone mapping operation corresponds to a high-dynamic range (HDR) tone mapping operation. 
     
     
       5. The method of  claim 1 , wherein the one or more perceptual criteria include a color contrast criterion, and wherein the set of color correction values and the chromaticity value satisfy the color contrast criterion with respect to each other. 
     
     
       6. The method of  claim 1 , further comprising determining a plurality of luminance values associated with the ambient light, wherein the plurality of luminance values quantifies the ambient light, wherein the one or more perceptual criteria include a luminance contrast criterion, and wherein the set of color correction values and the plurality of luminance values satisfy the luminance contrast criterion with respect to each other. 
     
     
       7. The method of  claim 1 , further comprising determining the one or more perceptual criteria based on a function of a color appearance model. 
     
     
       8. The method of  claim 1 , wherein the electronic device includes an environmental sensor that senses the ambient light and outputs corresponding sensor data, and wherein determining the chromaticity value is based on a function of the sensor data. 
     
     
       9. The method of  claim 1 , further comprising:
 identifying a second one of the plurality of semantic values that does not satisfy the criterion, wherein the second one of the plurality of semantic values is associated with the second portion of the image data; and 
 foregoing modifying the second portion of the image data. 
 
     
     
       10. The method of  claim 1 , wherein the first portion of the image data represents an object, and wherein the second portion of the image data represents a background relative to the object. 
     
     
       11. The method of  claim 1 , further comprising:
 determining a first chromaticity value and a second chromaticity value; 
 determining a first color correction value based on a function of the first chromaticity value and the image data, wherein the first color correction value and the first chromaticity value together satisfy the one or more perceptual criteria; 
 determining a second color correction value based on a function of the second chromaticity value and the image data, wherein the second color correction value and the second chromaticity value together satisfy the one or more perceptual criteria; and 
 modifying the first portion of the image data based on a function of the first color correction value, and modifying the second portion of the image data based on a function of the second color correction value. 
 
     
     
       12. A system comprising:
 a chromaticity values generator to determine a first chromaticity value and a second chromaticity value associated with ambient light from a physical environment, wherein the first chromaticity value and the second chromaticity value quantifies the ambient light; 
 a color correction value generator to determine a first color correction value based on a function of the first chromaticity value and image data and a second color correction value based on a function of the second chromaticity value and the image data, wherein the first color correction value and the first chromaticity value together satisfy one or more perceptual criteria and the second color correction value and the second chromaticity value together satisfy the one or more perceptual criteria; 
 an image data modifier to modify a first portion of the image data based on a function of the first color correction value and a second portion of the image data based on a function of the second color correction value in order to generate display data; and 
 a see-through display to display the display data. 
 
     
     
       13. The system of  claim 12 , wherein the image data modifier modifies the image data by color mapping a portion of the image data in order to match a corresponding portion of the set of color correction values within a performance threshold. 
     
     
       14. The system of  claim 12 , wherein the image data modifier includes a tone mapper to perform a tone mapping operation with respect to a portion of the image data. 
     
     
       15. The system of  claim 14 , wherein the tone mapping operation corresponds to a high-dynamic range (HDR) tone mapping operation. 
     
     
       16. The system of  claim 12 , further comprising an environmental sensor that senses the ambient light and outputs corresponding sensor data, wherein the chromaticity values generator determines the first chromaticity value and the second chromaticity value based on a function of the sensor data. 
     
     
       17. The system of  claim 12 , wherein the first chromaticity value quantifies the ambient light from a first region of the physical environment and the second chromaticity value quantifies the ambient light from a second region of the physical environment. 
     
     
       18. The system of  claim 12 , wherein modifying the first portion of the image data is further based on a function of the second color correction value. 
     
     
       19. The system of  claim 18 , wherein modifying the second portion of the image data is further based on a function of the first color correction value. 
     
     
       20. 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 with one or processors and a see-through display, cause the electronic device to:
 determine a first chromaticity value and a second chromaticity value associated with ambient light from a physical environment, wherein the first chromaticity value and the second chromaticity value quantifies the ambient light; 
 determine a first color correction value based on a function of the first chromaticity value and image data and a second color correction value based on a function of the second chromaticity value and the image data, wherein the first color correction value and the first chromaticity value together satisfy one or more perceptual criteria and the second color correction value and the second chromaticity value together satisfy the one or more perceptual criteria; 
 modify a first portion of the image data based on a function of the first color correction value and a second portion of the image data based on a function of the second color correction value in order to generate display data; and 
 display the display data on the see-through display.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a continuation of Intl. Patent App. No. PCT/US2021/038099, filed on Jun. 18, 2021, which claims priority to U.S. Provisional Patent App. No. 63/054,738, filed on Jul. 21, 2020, which are both hereby incorporated by reference in their entirety. 
    
    
     TECHNICAL FIELD 
     The present disclosure relates to color correction, and in particular, performing color correction with respect to a see-through display. 
     BACKGROUND 
     In some augmented reality (AR) environments, computer-generated content is added to light from a physical environment in order to enable display of the computer-generated content and a representation of the physical environment on a see-through display. A user may experience AR by wearing a head-mountable device (HMD) that includes the see-through display, which, in turn, allows the light from the physical environment to pass to eyes of the user. 
     In some circumstances, light from the physical environment has a luminance or a chromaticity that interferes with computer-generated content in a manner that degrades the AR experience. However, previously available color correction techniques do not effectively account for light from the physical environment. 
     SUMMARY 
     In accordance with some implementations, a method is performed at an electronic device with one or more processors, a non-transitory memory, and a see-through display. The method includes determining a chromaticity value associated with ambient light from a physical environment. The chromaticity value quantifies the ambient light. The method includes determining a set of color correction values based on a function of the chromaticity value and image data. The set of color correction values and the chromaticity value together satisfy one or more perceptual criteria. The method includes modifying the image data in order to generate display data based on a function of the set of color correction values. The method includes displaying the display data on the see-through display. 
     In accordance with some implementations, an electronic device includes one or more processors, a non-transitory memory, and a see-through display. 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 an electronic device in accordance with some implementations. 
         FIGS.  2 A- 2 J  are an example of an electronic device performing color correction based on perceptual criteria and chromaticity values associated with ambient light from a physical environment in accordance with some implementations. 
         FIG.  3    is an example of a block diagram of a system that performs color correction based on perceptual criteria and chromaticity values associated with ambient light from a physical environment in accordance with some implementations. 
         FIG.  4    is an example of a flow diagram of a method of performing color correction based on perceptual criteria and chromaticity values associated with ambient light from a physical environment in accordance with some implementations. 
     
    
    
     SUMMARY 
     A user may experience augmented reality (AR) by wearing a head-mountable device (HMD) that includes a see-through display, which, in turn, allows light from a physical environment to pass to eyes of the user. For example, the see-through display projects computer-generated content to be reflected off of the see-through display to the user&#39;s eyes. As another example, the see-through display projects computer-generated content directly at retinas of the user, and the light from the physical environment and the projected light of the computer-generated content concurrently reach the retinas. However, the HMD cannot effectively perform color correction because the HMD does not account for light from the physical environment. For example, light from the physical environment may have a chromaticity that interferes with computer-generated content in a manner that degrades the AR experience. The chromaticity of the light, such as the presence of predominantly one color, may provide dominant hues that are difficult to mask. The dominant hues associated with the light from the physical environment may interfere with the color characteristics of displayed computer-generated content. Moreover, certain color correction methods that are used in pass-through video display systems, such as spatially varying backlight tinting, are not readily applicable to the see-through display. Additionally, applying previously available tone mapping is not effective because it does not account for luminance or chromaticity features associated with the light. 
     By contrast, various implementations disclosed herein include methods, electronic devices, and systems for performing perceptual-based color correction based on chromaticity values that quantify ambient light from a physical environment. To that end, an electronic device, including a see-through display, determines the chromaticity values. For example, in some implementations, the electronic device includes one or more environment sensors (e.g., an ambient light sensor or image sensor) that sense the ambient light and output corresponding sensor data, and the electronic device determines the chromaticity values based on the corresponding sensor data. 
     The electronic device determines a set of color correction values based on a function of the chromaticity values and image data (e.g., computer-generated content to be displayed, such as AR content). The set of color correction values and the chromaticity value together satisfy one or more perceptual criteria. For example, the one or more perceptual criteria are a function of a range of colors or luminance values that is perceptible by a user, which may be affected by factors such as the user&#39;s state of adaptation of the eye, size and contour sharpness, location on the retina, etc. 
     Based on the set of color correction values, the electronic device modifies image data in order to generate corresponding display data for display on the see-through display. Thus, in contrast to other systems, the electronic device accounts for characteristics of the ambient light in order to perform effective color correction with respect to image data. For example, when the chromaticity values indicate a green background (e.g., the electronic device is pointing at trees in a real-world forest) and the image data is characterized by a predominately green hue, the set of color correction values modifies the image data in order to generate display data that is a different color than green. 
     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 person can interact with and/or sense a physical environment or physical world without the aid of an electronic device. A physical environment can include physical features, such as a physical object or surface. An example of a physical environment is physical forest that includes physical plants and animals. A person can directly sense and/or interact with a physical environment through various means, such as hearing, sight, taste, touch, and smell. In contrast, a person can use an electronic device to interact with and/or sense an extended reality (XR) environment that is wholly or partially simulated. The XR environment can include mixed reality (MR) content, augmented reality (AR) content, virtual reality (VR) content, and/or the like. With an XR system, some of a person&#39;s physical motions, or representations thereof, can be tracked and, in response, characteristics of virtual objects simulated in the XR environment can be adjusted in a manner that complies with at least one law of physics. For instance, the XR system can detect the movement of a user&#39;s head and adjust graphical content and auditory content presented to the user similar to how such views and sounds would change in a physical environment. In another example, the XR system can detect movement of an electronic device that presents the XR environment (e.g., a mobile phone, tablet, laptop, or the like) and adjust graphical content and auditory content presented to the user similar to how such views and sounds would change in a physical environment. In some situations, the XR system can adjust characteristic(s) of graphical content in response to other inputs, such as a representation of a physical motion (e.g., a vocal command). 
     Many different types of electronic systems can enable a user to interact with and/or sense an XR environment. A non-exclusive list of examples include heads-up displays (HUDs), head mountable systems, projection-based systems, windows or vehicle windshields having integrated display capability, displays formed as lenses to be placed on users&#39; eyes (e.g., contact lenses), headphones/earphones, input systems with or without haptic feedback (e.g., wearable or handheld controllers), speaker arrays, smartphones, tablets, and desktop/laptop computers. A head mountable system can have one or more speaker(s) and an opaque display. Other head mountable systems can be configured to accept an opaque external display (e.g., a smartphone). The head mountable system can include one or more image sensors to capture images/video of the physical environment and/or one or more microphones to capture audio of the physical environment. A head mountable system may have a transparent or translucent display, rather than an opaque display. The transparent or translucent display can have a medium through which light is directed to a user&#39;s eyes. The display may utilize various display technologies, such as uLEDs, OLEDs, LEDs, liquid crystal on silicon, laser scanning light source, digital light projection, or combinations thereof. An optical waveguide, an optical reflector, a hologram medium, an optical combiner, combinations thereof, or other similar technologies can be used for the medium. In some implementations, the transparent or translucent display can be selectively controlled to become opaque. Projection-based systems can utilize retinal projection technology that projects images onto users&#39; retinas. Projection systems can also project virtual objects into the physical environment (e.g., as a hologram or onto a physical surface). 
       FIG.  1    is a block diagram of an example of an electronic device  100  in accordance with some implementations. The electronic device  100  includes memory  102  (which optionally includes one or more computer readable storage mediums), a memory controller  122 , one or more processing units (CPUs)  120 , an interface  118 , an input/output (I/O) subsystem  106 , an inertial measurement unit (IMU)  130 , image sensor(s)  143  (e.g., a camera), a depth sensor  150 , eye tracking sensor(s)  164  (e.g., included within a head-mountable device (HMD)), an ambient light sensor  190 , 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 interface  118 , the one or more CPUs  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  and the other input or control devices  116  with the interface  118 . The I/O subsystem  106  optionally includes an image sensor controller  158 , an eye tracking controller  162 , and one or more input controllers  160  for other input or control devices, and a privacy engine  170 . The one or more input controllers  160  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  160  are, optionally, coupled with any (or none) of the following: a keyboard, infrared port, Universal Serial Bus (USB) port, stylus, and/or a pointer device such as a mouse. The one or more buttons optionally include an up/down button for volume control of a speaker and/or audio sensor(s). 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 physical environment. 
     The I/O subsystem  106  optionally includes a speaker and audio sensor(s) that provide an audio interface between a user and the electronic device  100 . Audio circuitry receives audio data from the interface  118 , converts the audio data to an electrical signal, and transmits the electrical signal to the speaker. The speaker converts the electrical signal to human-audible sound waves. Audio circuitry also receives electrical signals converted by an audio sensor (e.g., a microphone) from sound waves. Audio circuitry converts the electrical signal to audio data and transmits the audio data to the interface  118  for processing. Audio data is, optionally, retrieved from and/or transmitted to the memory  102  and/or RF circuitry by the 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 I/O subsystem  106  optionally includes a touch-sensitive display system that provides an input interface and an output interface between the electronic device  100  and a user. A display controller may receive and/or send electrical signals from/to the touch-sensitive display system. The touch-sensitive display system displays visual output to the user. The visual output optionally includes graphics, text, icons, video, and any combination thereof (collectively termed “graphics”). 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 touch-sensitive display system has a touch-sensitive surface, sensor, or set of sensors that accepts input from the user based on haptic and/or tactile contact. The touch-sensitive display system and the display controller (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 touch-sensitive display system 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 touch-sensitive display system. In an example implementation, a point of contact between the touch-sensitive display system and the user corresponds to a finger of the user or a stylus. 
     The touch-sensitive display system 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 touch-sensitive display system and the display controller 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 touch-sensitive display system. 
     The user optionally makes contact with the touch-sensitive display system using any suitable object or appendage, such as a stylus, 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. 
     The I/O subsystem  106  includes an inertial measurement unit (IMU) controller  132  that controls (e.g., manages operations of) the inertial measurement unit (IMU)  130 . The IMU  130  may include 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 IMU  130  may include 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)  143  corresponds to one or more HMD cameras. In some implementations, the image sensor(s)  143  includes one or more depth sensors. In some implementations, the image sensor(s)  143  includes a monochrome or color camera. In some implementations, the image sensor(s)  143  includes an RGB depth (RGB-D) sensor. 
     The I/O subsystem  106  optionally includes contact intensity sensors that 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 may be coupled with an intensity sensor controller in the I/O subsystem  106 . The contact intensity sensor(s) 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) 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 is collocated with, or proximate to, a touch-sensitive surface of the electronic device  100 . In some implementations, at least one contact intensity sensor is located on the back of the electronic device  100 . 
     The electronic device  100  includes a depth sensing controller  180  that controls (e.g., manages operations of) the depth sensor  150 . In some implementations, the depth sensor  150  is configured to obtain depth data, such as depth information characterizing an object within an obtained input image. For example, the depth sensor  150  corresponds to one of a structured light device, a time-of-flight device, and/or the like. 
     The eye tracking sensor(s)  164  detect eye gaze of a user of the electronic device  100  and generate eye tracking data indicative of the eye gaze 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 electronic device  100  includes an ambient light sensor controller  195  that controls (e.g., manages operations of) the ambient light sensor (ALS)  190 . The ALS  190  detects ambient light from a physical environment. In some implementations, the ambient light sensor  190  is a color light sensor. In some implementations, the ambient light sensor  190  is a two-dimensional (2D) or a three-dimensional (3D) light sensor. 
     In various implementations, the electronic device  100  includes a privacy engine  170  that includes one or more privacy setting filters associated with user information, such as user information included in the eye gaze data and/or body position data associated with a user. In some implementations, the privacy engine  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 engine  170  receives user preferences and/or selections from the user in response to prompting the user for the same. In some implementations, the privacy engine  170  prevents the electronic device  100  from obtaining and/or transmitting the user information unless and until the privacy engine  170  obtains informed consent from the user. In some implementations, the privacy engine  170  anonymizes (e.g., scrambles or obscures) certain types of user information. For example, the privacy engine  170  receives user inputs designating which types of user information the privacy engine  170  anonymizes. As another example, the privacy engine  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 J  are an example of an electronic device  212  performing color correction based on perceptual criteria and chromaticity values associated with ambient light from a physical environment  200  in accordance with some implementations. In various implementations, the features described with reference to  FIGS.  2 A- 2 J  are performed by the electronic device  100  illustrated in  FIG.  1   . 
     The electronic device  212  includes a see-through display  214 . In some implementations, the electronic device  212  corresponds to a mobile device, such as a smartphone, wearable device, tablet, head-mountable device (HMD), etc. In some implementations, the see-through display  214  corresponds to an additive display that enables optical see-through of the physical environment  200 , such as an optical HMD (OHMD). For example, in contrast to pure compositing using a video stream, the additive display is capable of reflecting projected images off of the display while enabling a user to see through the display. 
     As illustrated in  FIG.  2 A , the electronic device  212 , being held by a user  210 , includes the see-through display  214 . The see-through display  214  is associated with a field-of-view  216  that includes a portion of a physical environment  200 . The portion of the physical environment  200  includes a portion of a physical wall  204 . Accordingly, as illustrated in  FIG.  2 B , the see-through display  214  includes a representation of the portion of the physical wall  204  (sometimes herein referred to as “the physical wall  204 ” for the sake of brevity). 
     As illustrated in  FIG.  2 C , the electronic device  212  determines a first chromaticity value  217  that is associated with the physical wall  204  and a second chromaticity value  218  that is associated with a region of the see-through display  214  outside of the physical wall  204 . For example, the first chromaticity value  217  indicates that the physical wall  204  has a green hue because green light reflects off of the physical wall  204  and enters the see-through display  214 . The green hue is indicated by a first pattern (e.g., hatch pattern) of the physical wall  204  in  FIG.  2 C . The second chromaticity value  218  indicates a neutral color because of an absence of physical objects, and the neutral color is indicated in  FIG.  2 C  by a white color (e.g., no pattern). 
     In some implementations, the electronic device  212  includes one or more environmental sensors that sense ambient light from the physical environment  200 . The one or more environmental sensors output corresponding sensor data, such as ambient light data. The electronic device  212  may determine the first chromaticity value  217  and the second chromaticity value  218  based on the corresponding sensor data. In some implementations, the one or more environmental sensors include a combination of an ambient light sensor (ALS) (e.g., a two-dimensional (2D) sensor), an image sensor, and/or an inertial measurement unit (IMU). For example, in some implementations, the one or more environmental sensors include a monochrome or color camera with a depth sensor (RGB-D) and determines camera pose to point-of-view projection based on data from the RGB-D. 
     As illustrated in  FIG.  2 D , image data  219  is added to the see-through display  214  in order to provide the user  210  an augmented-reality (AR) experience, as is indicated by the plus sign. The image data  219  is associated with a navigation application (e.g., a GPS-based application). Namely, the image data  219  represents a directional indicator  220  that indicates a direction the user  210  should move in order to reach a destination, and a distance indicator  222  indicates the distance (“0.5 Miles”) to the destination. For example, the directional indicator  220  is yellow, as is indicated by a second pattern that is different from the first pattern associated with the physical wall  204 . Moreover, the distance indicator  222  is black. One of ordinary skill in the art will appreciate that, in some implementations, the image data  219  is associated with different content, associated with different application types, such as a content editing application, measuring application, furniture placement application, etc. In some implementations, the image data  219  is characterized by a plurality of sequential images, such as a video stream. 
     As illustrated in  FIG.  2 E , the electronic device  212  renders the image data  219  for display on the see-through display  214 . Accordingly, the see-through display  214  includes the directional indicator  220  and the distance indicator  222 . The directional indicator  220  and the distance indicator  222  are displayed within a region of the see-through display  214  that is outside of the physical wall  204 . Accordingly, ambient light reflected off of the physical wall  204  (e.g., green light) does not adversely affect the appearance of the directional indicator  220  and the distance indicator  222 . Accordingly, as illustrated in  FIG.  2 E , the directional indicator  220  displayed on the see-through display  214  maintains the second pattern. Moreover, the distance indicator  222  displayed on the see-through display  214  maintains the black appearance. 
     As illustrated in  FIG.  2 F , the electronic device  212  detects (e.g., via the IMU  130 ) a positional change input  224 . For example, the positional change input  224  is initiated by the user  210  turning the electronic device  212  towards the physical wall  204 . One of ordinary skill in the art will appreciate that, in some implementations, a different type of positional change results in a positional change of the electronic device  212 . In response to detecting the positional change input  224  in  FIG.  2 F , the field-of-view  216  correspondingly orients (e.g., rotates) more towards the physical wall  204 , as illustrated in  FIG.  2 G . 
     As illustrated in  FIG.  2 H , in response to the positional change input  224 , a larger portion of the see-through display  214  includes the physical wall  204 , as compared with the see-through display  214  in  FIGS.  2 C- 2 E . Accordingly, the electronic device  212  determines that the first chromaticity value  217  in  FIG.  2 H  is associated with a larger portion (e.g., larger horizontal strip) of the see-through display  214  than the first chromaticity value  217  illustrated in  FIGS.  2 C- 2 E . Consequently, the electronic device  212  determines that the second chromaticity value  218  in  FIG.  2 H  is associated with a smaller portion of the see-through display  214  than the second chromaticity value  218  illustrated in  FIGS.  2 C- 2 E . 
     Moreover, as illustrated in  FIG.  2 H , the directional indicator  220  and the distance indicator  222  are spatially associated with (e.g., overlap with) the physical wall  204  on the see-through display  214 . Consequently, the ambient light from the physical wall  204  interferes with (e.g., mixes with) the appearance of the directional indicator  220  and the distance indicator  222 . Accordingly, the directional indicator  220  in  FIG.  2 H  has a third pattern that is different from the second pattern illustrated in  FIG.  2 E . For example, rather than having a yellow color, the directional indicator  220  in  FIG.  2 H  has a greenish-yellow color because green light reflecting off of the physical wall  204  mixes with the directional indicator  220 . Moreover, the distance indicator  222  appears faded in  FIG.  2 H , as compared with the distance indicator  222  illustrated in  FIG.  2 E . 
     Accordingly, the electronic device  212  performs perceptual-based color correction based on chromaticity values according to various implementations disclosed herein. To that end, as illustrated in  FIG.  2 I , the electronic device  212  includes a color correction value generator  230 . The color correction value generator  230  determines a set of color correction values based on a function of the first chromaticity value  217  and the image data  219 . The set of color correction values are based on the first chromaticity value  217  because it is associated with light from the physical wall  204 , and the light from the physical wall  204  adversely affects display of the directional indicator  220  and the distance indicator  222 . The set of color correction values includes a first color correction value  236  that is associated with the directional indicator  220 , and a second color correction value  238  that is associated with the distance indicator  222 . 
     The set of color correction values and the first chromaticity value  217  together satisfy one or more perceptual criteria  228 . In some implementations, the one or more perceptual criteria  228  are a function of a color appearance model, which provides perceptual aspects of human color vision. For example, in some implementations, the color appearance model is based on color theory. Color theory may provide an indication of colors that appear harmonious with other colors. For example, color theory may indicate harmonious colors, such as complementary colors (e.g., high contrast, opposite on the color wheel), analogous colors (e.g., close to each other on the color wheel), tetradic colors (e.g., colors spaced equally on the color wheel), and/or the like. 
     As one example, referring back to  FIG.  2 H , a yellow directional indicator  220  and a green physical wall  204  do not satisfy the one or more perceptual criteria  228  because the combination of yellow and green is not visually pleasing based on color theory. Thus, for example, the first color correction value  236  changes the directional indicator  220  from yellow to red, because red and green satisfy a color contrast criterion with respect to each other. Accordingly, the electronic device  212  modifies the directional indicator  220  in order to generate display data representing a color-corrected directional indicator  240 , based on a function of the first color correction value  236 . As illustrated in  FIG.  2 J , the see-through display  214  displays the color-corrected directional indicator  240 . The color-corrected directional indicator  240  has a fourth pattern that is different from the third pattern (yellowish-green) and the second pattern (yellow) of the directional indicator  220 , which are respectively illustrated in  FIGS.  2 H and  2 E . 
     As another example, the electronic device  212  modifies the distance indicator  222  in order to generate display data representing a color-corrected distance indicator  242 , based on a function of the second color correction value  238 . For example, the color-corrected distance indicator  242  includes white text, as is illustrated in  FIG.  2 J . The white text enables greater visibility against the green background of the physical wall  204 , as compared with the faded black text illustrated in  FIG.  2 H . 
     In some implementations, in response to a positional change input (e.g., the user  210  looks down), the directional indicator  220  partially overlaps with the physical wall  204  and partially overlaps with the ground. Accordingly, the electronic device  212  determines a respective chromaticity value associated with the physical wall  204  and a respective chromaticity value associated with the ground, and modifies the directional indicator  220  based on the two respective chromaticity values. 
     In some implementations, the electronic device  212  concurrently changes respective colors of the directional indicator  220  and the distance indicator  222 . For example, in response to the positional change input  224  illustrated in  FIG.  2 F , the directional indicator  220  and the distance indicator  222  both overlap with the physical wall  204 , and the electronic device  212  concurrently changes colors of the directional indicator  220  and the distance indicator  222  based on the overlap. 
     In some implementations, the electronic device  212  changes respective colors of the directional indicator  220  and the distance indicator  222  independently of each other, such as changing one color at a time but not the other. For example, in response to a positional change input, the directional indicator  220  overlaps with the physical wall  204 , but the distance indicator  222  does not overlap with the physical wall  204 . Accordingly, the electronic device  210  may modify the color of the directional indicator  220  in order to account for (e.g., mask out) reflected light from the physical wall  204 , but does not modify the color of the distance indicator  222 . 
       FIG.  3    is an example of a block diagram of a system  300  that performs color correction based on perceptual criteria and chromaticity values associated with ambient light  302  from a physical environment in accordance with some implementations. In various implementations, the system  300 , or portions thereof, is integrated in an electronic device with a see-through display, such as the electronic device  100  in  FIG.  1    or the electronic device  212  in  FIGS.  2 A- 2 J . In some implementations, the system  300 , or portions thereof, is integrated in an HMD with a see-through display. 
     In some implementations, the system  300  includes a sensor subsystem  304  to sense the ambient light  302  and output corresponding sensor data. In some implementations, the sensor subsystem  304  includes a combination of environmental sensors, such as an ambient light sensor (ALS) (e.g., a two-dimensional (2D) sensor), an image sensor, and/or an inertial measurement unit (IMU). For example, in some implementations, the sensor subsystem  304  includes a monochrome or color camera with a depth sensor (RGB-D) and determines camera pose to point-of-view projection based on data from the RGB-D. As another example, in some implementations, the sensor subsystem  304  captures a lower resolution scene image, such as via a dedicated low-resolution image sensor or a dedicated high-resolution image sensor. In some implementations, the sensor subsystem  304  is implemented as a hardened IP block. In some implementations, the sensor subsystem  304  is implemented by using software and hardware accelerators. 
     The system  300  includes a chromaticity values generator  306  that determines one or more chromaticity values  308  associated with the ambient light  302 . The one or more chromaticity values  308  quantify the ambient light  302 . In some implementations, the chromaticity values generator  306  determines the one or more chromaticity values  308  based on the corresponding sensor data from the sensor subsystem  304 . For example, with reference to  FIGS.  2 E and  2 H , the chromaticity values generator  306  determines the first chromaticity value  217  and the second chromaticity value  218 . 
     The system  300  includes a color correction value generator  320  that generates a set of color correction values  322 . In some implementations, the color correction value generator  320  is similar to and adapted from the color correction value generator  230  in  FIG.  2 I . The color correction value generator  320  generates the set of color correction values  322  based on a function of the one or more chromaticity values  308  and image data  330 . The set of color correction values  322  and the one or more chromaticity values  308  together satisfy one or more perceptual criteria  312 . For example, in some implementations, the one or more perceptual criteria  312  are a function of a color appearance model  310 . In some implementations, the color appearance model  310  indicates certain moods or emotions that may result from a user viewing certain colors. For example, with reference to  FIGS.  2 I and  2 J , the first color correction value  236  changes the yellow directional indicator  220  to a red directional indicator  240  because red content overlaid onto a green physical wall  204  is visually pleasing according to the color appearance model  310 . 
     In some implementations, the system  300  includes a semantic values generator  350  that obtains or generates a plurality of semantic values respectively associated with a plurality of portions of the image data  330 . For example, in some implementations, the semantic values generator  350  obtains the plurality of semantic values from another system, such as from the internet. As another example, in some implementations, the semantic values generator  350  generates the plurality of semantic values by performing semantic segmentation with respect to the image data  330 . In some implementations, the semantic values generator  350  generates the plurality of semantic values with the aid of a neural network that is integrated within the system  300 . 
     Moreover, the system  300  may include a semantic value identifier  352  that obtains the plurality of semantic values from the semantic values generator  350 . In some implementations, the system  300  identifies, from the plurality of semantic values, one or more semantic values that satisfy a criterion. For example, a particular identified semantic value is associated with a portion of the image data  330  that represents an object of interest. As another example, a particular identified semantic value corresponds to a particular object type, such as a living object (e.g., a person, animal, tree, etc.). As one example, with reference to  FIG.  2 D , the semantic value identifier  352  identifies, within the image data  219 , a first semantic value associated with the directional indicator  220 , and a second semantic value associated with the distance indicator  222 . 
     The system  300  includes an image data modifier  340 . The image data modifier  340  modifies the image data  330  in order to generate display data  360  based on a function of the set of color correction values  322 . In some implementations, the image data modifier  340  color maps a portion of the image data  330  in order to match a corresponding portion of the set of color correction values  322  within a performance threshold. For example, the performance threshold is a function of distortion level (e.g., minimal distortion in color or contrast), quality of color reproduction, user experience, etc. 
     In some implementations, the image data modifier  340  modifies a portion (e.g., a subset of pixels of a particular image) of the image data  330  based on the one or more semantic values from the semantic value identifier  352 . Accordingly, by modifying less than the entirety of the image data  330 , the system  300  reduces resource utilization in some circumstances. 
     In some implementations, the image data modifier  340  includes a tone mapper  342  that performs a tone mapping operation with respect to the image data  330 . The tone mapper  342  may recover contrast that is lost in a physical environment with a non-zero luminance value. For example, the tone mapper  342  applies a tone mapping operation to a face in order to achieve a substantially uniform skin tone. In some implementations, the tone mapper  342  performs a high-dynamic range (HDR) tone mapping operation. For example, the tone mapper  342  maps colors represented within the image data  330  to the corresponding portion of the set of color correction values  322  in order to approximate the appearance of high-dynamic-range images in a medium that has a more limited dynamic range. Accordingly, the mapped image data has an improved chromaticity reproduction. 
     The image data modifier  340  provides the display data  360  for display on a see-through display  370 . In some implementations, the see-through display  370  corresponds to the see-through display  214  described with reference to  FIGS.  2 A- 2 J . 
       FIG.  4    is an example of a flow diagram of a method  400  of performing color correction based on perceptual criteria and chromaticity values associated with ambient light from a physical environment in accordance with some implementations. In various implementations, the method  400  or portions thereof are performed by an electronic device including a see-through display (e.g., the electronic device  100  in  FIG.  1    or the electronic device  212  in  FIGS.  2 A- 2 J ). In various implementations, the method  400  or portions thereof are performed by the system  300 . In various implementations, the method  400  or portions thereof are performed by a head-mountable device (HMD) including a see-through 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 determining a chromaticity value associated with ambient light from a physical environment. The chromaticity value quantifies the ambient light. In some implementations, the method  400  includes sensing (e.g., via the sensor subsystem  304  in  FIG.  3   ) the ambient light, outputting corresponding sensor data, and using the sensor data in order to determine the chromaticity value. As one example, with reference to  FIGS.  2 E,  2 H, and  3   , the chromaticity values generator  306  determines the first chromaticity value  217  and the second chromaticity value  218 . The chromaticity value may indicate a combination of hue value, chroma value, saturation value, etc. associated with the ambient light. 
     In some implementations, the method  400  includes determining a plurality of chromaticity values associated with the ambient light. For example, with reference to  FIG.  2 D , the electronic device  212  determines a first chromaticity value  217  associated with ambient light reflecting off of the physical wall  204 , and a second chromaticity value  218  associated with ambient light outside of the physical wall  204 . For example, each of the plurality of chromaticity values provides an objective specification of the quality of a color of a corresponding portion of ambient light entering a see-through display, irrespective of the luminance (e.g., intensity or brightness) of the ambient light. 
     As represented by block  404 , the method  400  includes determining a set of color correction values based on a function of the chromaticity value and image data (e.g., the image data  219  in  FIG.  2 D ). The set of color correction values and the chromaticity value together satisfy one or more perceptual criteria. For example, the one or more perceptual criteria is a function of a range of colors or lightness values that is perceptible by a particular user, which may be affected by factors such as the user&#39;s state of adaptation of the eye, size and contour sharpness, location on the retina, etc. In some implementations, the method  400  includes determining the one or more perceptual criteria based on a function of a color appearance model, such as the color appearance model  310  illustrated in  FIG.  3   . A color appearance model provides perceptual aspects of human color vision, such as the extent to which viewing conditions of a color diverge from the corresponding physical measurement of the stimulus source. In some implementations, the color appearance model is associated with a CIELAB color space. In some implementations, the color appearance model indicates certain moods or emotions that may result from the viewing of certain colors. For example, with reference to  FIGS.  2 I and  2 J , the first color correction value  236  changes the yellow directional indicator  220  to a red directional indicator  240  because red content overlaid onto a green physical wall  204  is visually pleasing according to the color appearance model. 
     As represented by block  408 , in some implementations, the one or more perceptual criteria include a color contrast criterion. The set of color correction values and the chromaticity value satisfy the color contrast criterion with respect to each other. For example, a portion of image data, corresponding to navigational AR content, has a greenish hue. Moreover, a particular chromaticity value, which is spatially associated with the portion of the image data, indicates a green hue because the electronic device is pointed at green grass on the ground. Thus, the method  400  includes determining a color correction value that changes the navigational AR content from green to red, because red and green have a relatively high color contrast with respect to each other. 
     As represented by block  410 , in some implementations, the method  400  includes determining a plurality of luminance values associated with the ambient light, based on ambient light sensor data from an integrated ambient light sensor. The plurality of luminance values quantifies the ambient light. The one or more perceptual criteria include a luminance contrast criterion, and the set of color correction values and the plurality of luminance values satisfy the luminance contrast criterion with respect to each other. For example, with reference to  FIG.  2 J , the color-corrected distance indicator  242  includes bright white text because, as compared with the green background of the physical wall  204 , the bright white text has a relatively high luminance contrast. Accordingly, the relatively high luminance contrast of the color-corrected distance indicator  242  is more easily perceptible by the user  210  than is the faded distance indicator  222  illustrated in  FIG.  2 H . 
     As represented by block  412 , in some implementations, the method  400  includes obtaining a plurality of semantic values respectively associated with a plurality of portions of the image data. The plurality of portions of the image data includes a first portion of the image data and a second portion of the image data. Moreover, the method  400  includes identifying a first one of the plurality of semantic values that satisfies a criterion, wherein the first one of the plurality of semantic values is associated with the first portion of the image data. For example, with reference to  FIG.  3   , the semantic value identifier  352  identifies a particular one of a plurality of semantic values that is associated with an object of interest (e.g., a face, text, etc.) within the image data  330 . Moreover, in some implementations, the method  400  includes identifying a second one of the plurality of semantic values (associated with the second portion of the image data) that does not satisfy the criterion. In some implementations, the first portion of the image data represents an object, and the second portion of the image data represents a background relative to the object. For example, with reference to  FIG.  2 D , the electronic device  212  determines that the directional indicator  220  represents an object, as compared with the white background surrounding the directional indicator  220 . 
     As represented by block  414 , the method  400  includes modifying (e.g., rendering) the image data in order to generate display data based on a function of the set of color correction values. For example, with reference to  FIGS.  2 H- 2 J , the electronic device  212  modifies the image data in order to generate display data, which is displayed on the see-through display  214  in  FIG.  2 J . In some implementations, the electronic device  212  applies the first color correction value  236  to the directional indicator  220  in order to generate the color-corrected directional indicator  240 , and applies the second color correction value  238  to the distance indicator  222  in order to generate the color-corrected distance indicator  242 . As one example, when the image data represents a map with three colors (e.g., green background, blue arrow, black text), the method  400  includes changing some or all of the three colors based on a corresponding set of color correction values. As another example, in some implementations, the method  400  includes modifying the image data in order to preserve a level of color contrast between the three colors of the map. In some implementations, a physical environment includes multiple colors (e.g., a blue sky and a green tree are in the field-of-view of a display), and the method  400  includes modifying an object represented by the image data based on the multiple colors. For example, the method  400  includes modifying a yellow object represented within the image data to a different color that appears harmonious in view of the multiple colors. As represented by block  416 , in some implementations, modifying the image data includes modifying the first portion of the image data, as described with reference to block  412 . Moreover, in some implementations, the method  400  includes foregoing modifying the second portion of the image data. Accordingly, by selectively modifying portions of the image data, an electronic device implementing the method  400  utilizes fewer resources in some circumstances. 
     As represented by block  418 , the method  400  includes displaying, on a see-through display, the display data. In some implementations, the see-through display corresponds to the see-through display  214  described with reference to  FIGS.  2 A- 2 J . In some implementations, the see-through display corresponds to the see-through display  370  described with reference to  FIG.  3   . 
     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: 20230120
Publication Date: 20240409
Grant Date: 20240409
Priority Date: 20200721
Inventors: RANGAPRASAD, ARUN SRIVATSAN
GRUNDHOEFER, ANSELM
Assignee: APPLE INC
CPC Classifications: [{"code": "G09G5/02", "inventive": true, "first": true, "tree": "[]"}, {"code": "G06V10/60", "inventive": true, "first": false, "tree": "[]"}, {"code": "G09G2360/144", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04N1/6088", "inventive": true, "first": true, "tree": "[]"}, {"code": "G09G5/02", "inventive": true, "first": true, "tree": "[]"}, {"code": "G09G2360/144", "inventive": false, "first": false, "tree": "[]"}, {"code": "G09G5/10", "inventive": true, "first": false, "tree": "[]"}, {"code": "G09G5/393", "inventive": true, "first": false, "tree": "[]"}, {"code": "G09G2320/0242", "inventive": false, "first": false, "tree": "[]"}, {"code": "G09G5/02", "inventive": true, "first": false, "tree": "[]"}, {"code": "G02B2027/0118", "inventive": false, "first": false, "tree": "[]"}, {"code": "G02B2027/0112", "inventive": false, "first": false, "tree": "[]"}, {"code": "G06V10/60", "inventive": true, "first": false, "tree": "[]"}, {"code": "G09G2360/144", "inventive": false, "first": false, "tree": "[]"}]
Family ID: 76959068