Abstract: In one embodiment, a computing system determines one or more depth measurements associated with a first physical object. The system captures an image including image data associated with the first physical object. The system identifies and associates a plurality of first pixels with a first representative depth value based on the one or more depth measurements. The system determines, for an output pixel of an output image, that (1) a portion of a virtual object is visible from a viewpoint and (2) the output pixel overlaps with a portion of the first physical object. The system determines that the portion of the first physical object is associated with the plurality of first pixels and renders the output image from the viewpoint. Occlusion at the output pixel is determined based on a comparison between the first representative depth value and a depth value associated with the portion of the virtual object.

Abstract: Systems and methods are disclosed for generating a scaled reconstruction for a consumer product. One method includes receiving digital input comprising a calibration target and an object; defining a three-dimensional coordinate system; positioning the calibration target in the three-dimensional coordinate system; based on the digital input, aligning the object to the calibration target in the three-dimensional coordinate system; and generating a scaled reconstruction of the object based on the alignment of the object to the calibration target in the three-dimensional coordinate system.

Abstract: A location-based augmented-reality system to generate and cause display of augmented-reality content that includes three-dimensional typography, based on a perspective, and location of a client device.

Abstract: A display apparatus includes an optical see-through display apparatus, and includes a light source that emits lights a combiner including a diffraction member that diffracts light incident from the light source and outputs the light, and a controller that controls light emission of the light source. The controller controls a light output of the light source on the basis of a wavelength of light outputted from the light source and diffraction efficiency of the combiner that is changed resulting from change in a wavelength of incident light.

Abstract: Apparatuses, components, devices, methods, and systems for generating dentures are provided. An example system includes a motion capture system that captures patient jaw motion and generates patient jaw motion data; and a denture design system that generates a denture design based on the patient jaw motion data. An example method includes acquiring a digital reference denture model of a reference denture; selecting a denture tooth library based on the digital reference denture model; selecting and aligning denture library teeth from the selected denture tooth library to the digital reference denture model; generating a denture base digital model based on the digital reference denture model and the aligned denture library teeth; and fabricating a physical denture based from the denture base digital model.

Abstract: An image coloring method includes: acquiring first color a priori information about an image-to-be-colored; transforming the first color a priori information to obtain second color a priori information aligned with the image-to-be-colored; downsampling the image-to-be-colored to obtain a first image feature; performing modulation coloring processing on the first image feature based on the second color a priori information to obtain a second image feature; and upsampling the second image feature based on the second color a priori information to obtain a first colored image, where the first colored image is aligned with the image-to-be-colored.

Abstract: A system automatically identifies objects in an environment based on a walkthrough video and an annotated floorplan of the environment. The annotated floorplan indicates locations and types of objects that are expected to be in the environment. The system receives the walkthrough video and generates a 3D model of the environment. The system applies a machine learning model to the walkthrough video to identify regions within frames where objects are captured. After identifying the regions within frames of the walkthrough video that include objects, the system modifies corresponding regions of the 3D model to include the identified objects. For each of the identified objects, the system determines a likelihood of the identified object being present at a location in the environment based on a comparison of the modified 3D model and the annotated floorplan.

Abstract: Systems and methods provided for presenting supplemental content in an augmented reality environment where an object within a field of view of an augmented reality device of a user is identified and processed to detect a reference related to a participant in an event. A user profile or user social network is searched to identify a message from the user about the participant. The message may be combined with the object in the augmented reality field of view.

Abstract: Disclosed are example embodiments of systems and methods for virtual try-on of articles of clothing. An example method of virtual try-on of articles of clothing includes selecting a garment from a pre-existing database. The method also includes loading a photo of a source model wearing the selected garment. Additionally, the method includes generating a semantic segmentation of the model image. The method also includes extracting the selected garment from the photo of the model. Additionally, the method includes determining a correspondence between a target model and the source model by performing a feature point detection and description of the target model and the source model, and performing feature matching and correspondence validation. The method also includes performing garment warping and alignment of the extracted garment. Additionally, the method includes overlaying and rendering the garment.

Abstract: A system for generating three-dimensional models of a physical environment such as a room. In some cases, the system may utilize a two-dimensional floor, room, or house plan to generate, close and/or orthogonalize wall segments. The system may then generate a three-dimensional model by projecting the wall segments into a three-dimensional space and inserting objects.

Abstract: Methods and systems are disclosed for performing operations for generating a photorealistic rendering of an object. The operations include: accessing a set of albedo textures and a machine learning model associated with a real-world object, the set of albedo textures and a machine learning model having been trained based on a plurality of viewpoints of the real-world object; obtaining a three-dimensional (3D) mesh of the real-world object; receiving input that selects a new viewpoint that differs from the plurality of viewpoints of the real-world object; and generating a photorealistic rendering of the real-world object from the new viewpoint based on the 3D mesh of the real-world object, the set of albedo textures, and the machine learning model associated with the real-world object.

Abstract: Systems, apparatuses (or devices), methods, and computer-readable media are provided for generating virtual content. For example, a device (e.g., an extended reality device) can obtain an image of a scene of a real-world environment, wherein the real-world environment is viewable through a display of the extended reality device as virtual content is displayed by the display. The device can detect at least a part of a physical hand of a user in the image. The device can generate a virtual keyboard based on detecting at least the part of the physical hand. The device can determine a position for the virtual keyboard on the display of the extended reality device relative to at least the part of the physical hand. The device can display the virtual keyboard at the position on the display.

Abstract: There is provided a method of discrete optimisation comprising: receiving an optimisation objective function; performing a continuous optimisation based upon the optimisation objective function to generate an initial continuous value; generating a plurality of candidate discrete values based upon the initial continuous value; evaluating the plurality of candidate discrete values based upon the optimisation objective function, wherein the evaluation of the plurality of candidate discrete values is carried out in parallel; and outputting a candidate discrete value based upon the evaluation.

Abstract: This specification describes systems and methods for refining point cloud data. Methods can include receiving point cloud data for a physical space, iteratively selecting points along an x, y, and z dimension, clustering the selected points into 2D histograms, determining a slope value for each 2D histogram, and removing, based on the slope value exceeding a predetermined value, points from the point cloud data. Methods can also include iteratively voxelizing each 2D histogram into predetermined mesh sizes, summating points in each voxelized 2D histogram, removing, based on determining the summation is below a predetermined sum value, points from the point cloud data, keeping, based on determining that a number of points in each voxelized 2D histogram exceeds a threshold value, a center point, selecting, for each histogram, a point, identifying, nearest neighbors in the point cloud data, removing the identified nearest neighbors from the data, and returning remaining points.

Abstract: The subject technology receives at least one signal from a computing device, the at least one signal comprising at least one of a current time, battery power, sensor information, or location information. The subject technology generates a digital sticker, the digital sticker including graphical content indicating information based at least in part based on the at least one signal and media content including an image of a target face, the image of the target face being modified based on at least one of sets of source pose parameters to mimic at least one of positions of a head of a source actor and at least one of facial expressions of the source actor. The subject technology provides augmented reality content for display on a computing device, the augmented reality content including the digital sticker as an overlay on at least a portion of the augmented reality content.

Abstract: Systems and methods for continuously updating emotional states of artificial intelligence (AI) characters using emotional state models are provided. An example method includes providing an emotional state model trained to predict an emotional state of an AI character generated by an AI character model in a virtual environment; continuously monitoring a context of an interaction involving the AI character; generating, based on the context, an input for the emotional state model; providing the input to the emotional state model; obtaining, from the emotional state model, the emotional state of the AI character based on the input; and adjusting, based on the emotional state, parameters of the AI character model, thereby causing the AI character to act according to the emotional state.

Abstract: An electronic device is provided. The electronic device includes a sensor module, a communication module, a display, a memory, and at least one processor configured to identify a plurality of states based on at least one of information obtained through the sensor module, information received from an external electronic device through the communication module, or information associated with a function of the electronic device, identify priorities of the plurality of states, identify a first state among the plurality of states based on the identified priorities, identify whether there is a second state mergeable with the first state, and control the display to display, a first character object corresponding to the first state or a third character object corresponding to merge of the first state and the second state, based on whether there is the second state mergeable with the first state.

Abstract: A technology is described for using a medical implement or a fluoroscopic image with reference to an image data set and a body of a person. A method may include detecting visual image data of a body of a patient and a medical implement. The optical codes on the body of the patient and on the medical implement may be identified. One operation is aligning the image data set with the body of the person using one or more optical codes on the body of the person and the fixed position of an image visible marker with respect to the optical code. A position of the medical implement with respect to the body of the person may be determined using one or more optical codes on the medical implement and the body of the person to reference the medical implement to the image data set and the body of the person.

Abstract: A prediction device f includes an acquisition unit and a prediction unit. The acquisition unit is configured to acquire attribute data pertaining to the plurality of exhibits and the number of visitors to each of the plurality of exhibits during a first period in the display area in which the plurality of exhibition articles are exhibited. The prediction unit is configured to predict a future flow of persons to the plurality of exhibits by a prediction model. The prediction model is generated using attribute data for a second period that is a period previous to the first period, graph time-series data pertaining to a change over time in a movement pattern for each of the plurality of visitors to the plurality of exhibits during the second period, the number of visitors to the exhibits, and the number of visitors to each of the plurality of exhibits.

Abstract: A method includes extracting, using a backbone of a machine learning model, a plurality of features from an image of a foot and predicting, using a first portion of the machine learning model and based on one or more features of the plurality of features, a first aspect of the foot. The method also includes predicting, using a second portion of the machine learning model and based on one or more features of the plurality of features, a second aspect of the foot different from the first aspect, generating, using at least the first aspect and the second aspect, a two-dimensional model of a shoe, and superimposing the two-dimensional model of the shoe onto the image of the foot.