Abstract: In one embodiment, a method includes rendering a first sequence of image frames for displays of the extended reality (XR) display device in XR environment, wherein the first sequence of images portrays a virtual content organizer with multiple user-interactable elements corresponding to a first respective multiple operations, wherein the virtual content organizer is in a first pose, wherein a first subset of user-interactable elements of multiple user-interactable elements is selectable from the first pose, receiving one or more first gesture inputs associated with a first manipulation of the virtual content organizer along six degrees of freedom from the first pose to a second pose, rendering a second sequence of image frames, wherein the second sequence of images portrays the virtual content organizer in the second pose, receiving a selection of a particular user-interactable element from a second subset of user-interactable elements in a second pose, and executing the particular operation.

Abstract: In one embodiment, an apparatus includes a multi-view display that includes several pixels. The apparatus includes a parallax barrier that overlays the several pixels of the multi-view display. The parallax barrier includes several barrier rows that are arrayed in a first dimension, where each barrier row includes several barriers arrayed in a second dimension. Each of the barriers are separated from adjacent barriers in the barrier row by an aperture. Each barrier row is offset from adjacent barrier rows by a macro offset distance in the second dimension. A portion of each barrier is offset by a micro offset distance in the second dimension, where the micro offset distance is smaller than the macro offset distance.

Abstract: In particular embodiments, an apparatus comprises a non-transitory computer-readable storage media and a processor coupled to the media executes instructions to: access a plurality of text, generate, using one or more natural language understanding (NLU) models, one or more scores for at least a portion of the plurality of text. The apparatus determines, based on the scores, one or more prosodic values corresponding to the portion of the plurality of text. The apparatus determines, based on the one or more prosodic values, one or more speech synthesis markup language (SSML) tags. The apparatus then generates, based on the prosodic values, SSML-tagged data comprising each determined SSML tag and that tag's location in the plurality of text.

Abstract: In one embodiment, an apparatus includes one or more processors and a memory coupled to the processors include instructions executable by the processors. When executing the instructions, the processors present on a display of the apparatus a first screen that corresponds to a first mode of the apparatus. The first screen is in a first level of a graphical user interface (GUI) hierarchy and occupies a substantial portion of the display when presented. In response to a transition event at the first screen, the processors present a second screen that corresponds to a second mode of the apparatus. The second screen is in the first level of the GUI hierarchy and occupies the substantial portion of the display when presented. In response to a selection event at the first screen, the processors present a third screen that corresponds to a first function of the first mode of the apparatus.

Abstract: In one embodiment, a method may include receiving a user input at an electronic device, the user input comprising a gesture associated with setting a screen orientation of the electronic device, wherein the electronic device is configured to recognize orientation-specific user input when entered from any one of a plurality of orientations. The method may include transitioning the electronic device from a first state to a second state, the second state being an active state. The method may then include changing the screen orientation based at least in part on an assessment of the user input, and displaying content on the electronic device based on the screen orientation.

Abstract: A method implemented by an extended reality (XR) display device capturing, by an optical sensor, an image portraying a number of objects within an environment and analyzing the image to identify a tracking pattern corresponding to a first object. The first object is an external electronic device associated with the XR display device. The method further includes generating a first map of the environment based on the image, in which a relative location of the external electronic device within the environment with respect to the XR display device is determined for the first map based on the tracking pattern. The method further includes accessing a final map of the environment based on the first map of the environment and a second map of the environment generated with respect to the relative location.

Abstract: A method includes capturing, by a camera disposed behind a display panel of an electronic device, a plurality of point spread functions (PSFs) through a semi-transparent pixel region of the display panel. Each of the plurality of PSFs is captured at a different exposure time. The method further includes determining, for each of the PSFs, pixel intensity data for each of a plurality of pixel locations of the PSF. The pixel intensity data is associated with the exposure time of the respective PSF. The method further includes calculating, for each pixel location, a weighted average pixel intensity value based on the pixel intensity data and the exposure time for the respective pixel location over the plurality of PSFs, and generating a high dynamic range (HDR) PSF utilizing the weighted average pixel intensity values.

Abstract: A method implemented by a client device includes accessing a plurality of image frames captured by one or more cameras of the client device and generating a working image frame based at least in part on one or more of the plurality of image frames. The method further includes classifying one or more first objects detected in the working image frame based at least in part on a determined desirability of the one or more first objects. The one or more first objects are determined to be undesirable. The method further includes applying a pixel filtering process to the working image frame to replace one or more first pixel sets associated with the first objects with pixels from one or more image frames of the plurality of image frames to generate a final image frame, and displaying the final image frame on a display of the client device.

Abstract: An artificial intelligence (AI) method includes generating a first musical interaction behavioral model. The first musical interaction behavioral model causes an interactive electronic device to perform a first set of musical operations and a first set of motional operations. The AI method further includes receiving user inputs received in response to the performance of the first set of musical operations and the first set of motional operations and determining a user learning progression level based on the user inputs. In response to determining that the user learning progression level is above a threshold, the AI method includes generating a second musical interaction behavioral model. The second musical interaction behavioral model causes the interactive electronic device to perform a second set of musical operations and a second set of motional operations. The AI method further includes performing the second set of musical operations and the second set of motional operations.

Abstract: In one embodiment, a method includes processing user interactions with an electronic device based on different processing modules. The electronic device includes one or more radar-based transmitters and receivers. The method transmits radio waves into an area in the vicinity of the electronic device from the transmitters and receives at the receivers the radio waves reflected off one or more objects in the vicinity of the electronic device. The method selects either trilateration processing or imaging process to process the received radio waves based on different requirements for processing user interactions.

Abstract: In one embodiment, a device includes a device body that includes a touch-sensitive display and a processor. The device also includes a band coupled to the device body and an optical sensor in or on the band. The optical sensor faces outward from the band and captures images. The processor communicates with the optical sensor to process captured images.

Abstract: In one embodiment, an apparatus includes a wearable computing device that includes one or more processors and a memory. The memory is coupled to the processors and includes instructions executable by the processors. When executing the instructions, the processors determine whether an application is running on the wearable computing device. The application controls one or more functions of a remote computing device. The processors determine to delegate a task associated with the application; delegate the task to be processed by a local computing device; and receive from the local computing device results from processing the delegated task.

Abstract: In one embodiment, a method includes presenting to a user, on a display of a head-worn client computing device, a three-dimensional video including images of a real-life scene that is remote from the user's physical environment. The method also includes presenting to the user, on the display of the head-worn client computing device, a graphical object including an image of the user's physical environment or a virtual graphical object.

Abstract: In one embodiment, the system receives unlabeled data from one or more sensors. The one or more sensors are associated with a computing device of a user. The system clusters the unlabeled data into one or more unlabeled clusters. The system determines, based on one or more rules, at least one label for at least one unlabeled cluster of the one or more unlabeled clusters. The system expands, by a natural language processing algorithm, the at least one label for the at least one unlabeled cluster to produce one or more semantic terms associated with the at least one unlabeled cluster. The system generates, based on the one or more semantic terms, a personalized graph associated with one or more behavioral patterns of the user.

Abstract: A method includes receiving temporal-based user profile data including a first set of user profile data and a second set of user profile data. The method further includes determining an aggregated profile covariance (APC) and an aggregated profile variance (APV), and then deriving a regression coefficient based on the APC and the APV. In response to receiving an observation of desirable media content for one or more particular timeslots, the method further includes determining an updated APC based on a covariance of the first set of user profile data and the observation of desirable media content, determining an updated APV based on a variance of the first set of user profile data, and generating a prediction of desirable media content based on the updated APC, the updated APV, and the regression coefficient. The prediction of desirable media content corresponds to the one or more particular timeslots.

Abstract: A wearable computing device includes a device body, a band coupled to the device body, and one or more sensors. The device body includes one or more processors, a memory, and a touch-sensitive display. The processors are operable to authenticate, using the one or more sensors, a user of the device, and communicate with one or more target devices in response to successful authentication of the user. The processors can also authenticate the target devices, and control the target devices in response to successful authentication of the target devices. The sensors may include a camera, and to authenticate the user of the device, the processors may send a request to one or more remote devices requesting display of a pairing visual, receive an image from the camera, determine whether the image comprises valid pairing information, and if so, establish a pairing between the device and the remote devices.

Abstract: In one embodiment, a method may include outputting one or more sensor signals from an electronic device into a portion of a user's body, and detecting one or more deflected signals from the one or more sensor signals. The method may include detecting a bone structure of the user's body based on the one or more deflected signals. Then, the method may include determining a user measurement based on the one or more deflected signals, the health measurement being adjusted by the detected bone structure.

Abstract: A method includes rendering, on displays of an extended reality (XR) display device, a first sequence of image frames based on image data received from an external electronic device associated with the XR display device. The method further includes detecting an interruption to the image data received from the external electronic device, and accessing a plurality of feature points from a depth map corresponding to the first sequence of image frames. The plurality of feature points includes movement and position information of one or more objects within the first sequence of image frames. The method further includes performing a re-warping to at least partially re-render the one or more objects based at least in part on the plurality of feature points and spatiotemporal data, and rendering a second sequence of image frames corresponding to the partial re-rendering of the one or more objects.

Abstract: A method implemented by an extended reality (XR) display device includes rendering a current image frame received from an external electronic device associated with the XR display device. The current image frame is associated with a current pose of the XR display device. The method further includes receiving an updated image frame from the external electronic device, calculating an updated pose based on one or more characteristics of the updated image frame, and determining whether the updated pose is within a pose range with respect to the current pose. The method thus further includes re-rendering, on one or more displays of the XR display device, a previous image frame based on whether the current pose is determined to be within the pose range.

Abstract: In one embodiment, an electrical device may inject one or more first electrical signals into a resistive layer of a touch sensor. The device may receive one or more second electrical signals each corresponding to a first electrical signal injected by a first electrode. The device may determine, based on the one or more second electrical signals, a vector with each element of the vector corresponding to a value associated with a particular second electrical signal. Each element may depend at least on: a relative location between the first electrode injecting the first electrical signal and a second electrode receiving the second electrical signal, the signal frequency, and a user touch location on the touch sensor. The device may determine the user touch location based on the vector using at least one of a lookup table, a curve-fitting coefficient set, or a machine-learning model.