Abstract: In one example, a method includes presenting an extended reality (XR) experience to a plurality of user devices, wherein the presenting includes presenting a time control along with an XR stream, receiving a first signal from a first user device of the plurality of user devices via the time control, wherein the first signal indicates that a user of the first user device wishes to shift the XR stream to a first point in time that is different from a time that is currently being rendered in the XR stream, and presenting a personal XR environment to the first user device in response to the first signal, wherein the personal XR environment presents the first point in time in the XR stream to the first user device without changing a time point of the XR stream that is currently being presented to other user devices of the plurality of user devices.

Abstract: A system for generation of training dataset is provided. The system controls a depth sensor to capture, from a first viewpoint, a first image a first depth value associated with the first object. The system receives tracking information from a handheld device associated with the depth sensor, based on a movement of the handheld device and the depth sensor in a 3D space. The system generates graphic information corresponding to the first object based on the received tracking information. The graphic information includes the first object from a second viewpoint. The system calculates a second depth value associated with the first object, based on the graphic information. The system generates, for a neural network model, a training dataset which includes a first combination of the first image and the first depth value, and a second combination of second images corresponding to the graphic information and the second depth value.

Abstract: Disclosed herein are implementations of a method and apparatus for stroke self-detection. The method and apparatus may include a mobile platform for stroke detection. The method may include receiving sensor data. The method may include comparing the sensor data with a baseline test result to determine a test score. The method may include determining a passing test result based on a threshold. The method may include transmitting the results or an alert to one or more of an emergency contact, emergency medical services, a physician, or a telemedicine provider.

Abstract: The present technology relates to artificial reality systems. Such systems provide projections a user can create to specify object interactions. For example, when a user wishes to interact with an object outside her immediate reach, she can use a projection to select, move, or otherwise interact with the distant object. The present technology also includes object selection techniques for identifying and disambiguating between objects, allowing a user to select objects both near and distant from the user. Yet further aspects of the present technology include techniques for interpreting various bimanual (two-handed) gestures for interacting with objects. The present technology further includes a model for differentiating between global and local modes for, e.g., providing different input modalities or interpretations of user gestures.

Abstract: Embodiments described herein provide a graphics processor that can perform a variety of mixed and multiple precision instructions and operations. One embodiment provides a streaming multiprocessor that can concurrently execute multiple thread groups, wherein the streaming multiprocessor includes a single instruction, multiple thread (SIMT) architecture and the streaming multiprocessor is to execute multiple threads for each of multiple instructions. The streaming multiprocessor can perform concurrent integer and floating-point operations and includes a mixed precision core to perform operations at multiple or mixed precisions and dynamic ranges.

Abstract: A method of generating a representation of a virtual environment includes obtaining a mesh of at least part of the virtual environment; detecting the continuous and non-overlapping portions of that mesh, hereafter ‘patches’; populating a texture map with representations of the patches by, for successive patches in order of large to small, identifying a position on the texture map where a current patch meets a non-overwrite criterion, wherein the a non-overwrite criterion requires that texels corresponding to the current patch do not overwrite texels of any previously positioned patch, and successive positions for each current patch are tested at intervals starting from a common origin position; and associating the current patch with the identified position; setting colour values for the texels of the texture map responsive to colour information corresponding to the obtained mesh; and outputting the obtained mesh and texture map for use by a third party.

Abstract: A method for of playing an animation image, the method including: obtaining a plurality of images; displaying a first image of the plurality of images; detecting a first event as a trigger to play the animation image for a first object of the first image; and playing the animation image for the first object using the plurality of images.

Abstract: A system and method are provided to generate blended video and graphics using a blending domain. The system converts video from a first domain to a blending domain. The system converts graphics from a second domain to the blending domain and blends the video and graphics in the blending domain to generate a blended output.

Abstract: A method for operating a comprehensive three-dimensional teaching field, including: collecting, by a sensor, a depth data of a real teaching space, point cloud data of a teacher and voice data of the teacher; performing calculation and caching of an architecture for data storage, transmission and rendering of a virtual teaching space based on edge cloud; building a database model of the virtual teaching space by using a R-tree spatial index structure to realize distributed data storage; generating a virtual avatar model updating in real time by positioning and tracking an action of a user; displaying an image of the virtual teaching space on terminals of the teacher and a student through encoding, uploading, 5G rendering and decoding by using a 5G link.

Abstract: A surgical position calibration method for getting the augmented and mixed reality of a surgical instrument includes the following steps: placing a calibration plate under a C-ARM to take C-ARM images, with the calibration plate provided with geometric patterns; inputting the C-ARM images into a computer to make 2D image maps; finding the center point of each geometric pattern on the calibration plate; defining a first reference calibration point; finding the distance between the center point of each other geometric pattern and the first reference calibration point to set up a translation matrix formula to form a 3D space image map; placing a surgical instrument at any position above the calibration plate; using the translation matrix formula generating a spatial variation image for the displacement of the surgical instrument; and forming a new spatial variation image.

Abstract: An apparatus such as a graphics processing unit (GPU) includes shader engines and front end (FE) circuits. Subsets of the FE circuits are configured to schedule commands for execution on corresponding subsets of the shader engines. The apparatus also includes a set of physical paths configured to convey information from the FE circuits to a memory via the shader engines. Subsets of the physical paths are allocated to the subsets of the FE circuits and the corresponding subsets of the shader engines. The apparatus further includes a scheduler configured to receive a reconfiguration request and modify the set of physical paths based on the reconfiguration request. In some cases, the reconfiguration request is provided by a central processing unit (CPU) that requests the modification based on characteristics of applications generating the commands.

Abstract: Herein is presented a light-weight, high-quality texture synthesis algorithm that generalizes to other applications. We utilize an optimal transport optimization process within a bottleneck layer of an auto-encoder, achieving quality and flexibility on par with expensive back-propagation based neural texture synthesis methods, but at interactive rates. In addition to superior synthesis quality, our statistically motivated approach generalizes better to other special case texture synthesis problems such as Style Transfer, Inverse-Texture Synthesis, Texture Mixing, Multi-Scale Texture Synthesis, Structured Image Hybrids and Texture Painting. We treat the texture synthesis problem as the optimal transport between Probably Density Function of the deep neural activation vectors of the image being synthesized and the exemplar texture.

Abstract: Implementations are described herein for automatically generating synthetic training images that are usable, for instance, as training data for training machine learning models to detect and/or classify various types of plant diseases at various stages in digital images. In various implementations, one or more environmental features associated with an agricultural area may be retrieved. One or more synthetic plant models may be generated to visually simulate one or more stages of a progressive plant disease, taking into account the one or more environmental features associated with the agricultural area. The one or more synthetic plant models may be graphically incorporated into a synthetic training image that depicts the agricultural area.

Abstract: An embodiment of the process state analysis device of the present invention is provided with an evaluation value calculation unit and a graph creation unit. The evaluation value calculation unit calculates, within an evaluation value calculation range indicating a target range for calculating evaluation values, an evaluation value for each cluster that is classified on the basis of multi-dimensional process data output from each measurement device. The graph creation unit determines a hue for a graph element for each cluster on the basis of the evaluation value for the cluster as calculated within the evaluation value calculation range, and on the basis of a color reference evaluation value corresponding to a reference hue for the graph element, and creates and outputs a graph representing, for each aggregation unit time interval in a specified display period, the number of nodes belonging to each cluster.

Abstract: Techniques for generating an insurance claim include receiving pupil data from an electronic device. The pupil data indicates a gaze direction of a user. Environment information is received from the electronic device, including point cloud data representing an environment in which the electronic device is currently disposed and a plurality of objects located within the environment. The techniques include determining an identity of an object of the plurality of objects based at least in part on the gaze direction and the environment information. The techniques include receiving, from the electronic device and via the network, information indicative of an input provided by the user, the input corresponding to the object, and comprising at least one of a first user utterance or a hand gesture. The techniques include generating an insurance claim based at least in part on the information and on the identity of the object.

Abstract: A method may include obtaining HD mapping data including multiple data topics with one or more distinct instances. The method may include creating multiple meshes from corresponding distinct instances. The method may include defining multiple textures for each data topic. The method may include selecting a first data topic and a first distinct instance of the first data topic. The method may include selecting a first texture for the first data topic and applying the first texture to a first mesh corresponding with the first distinct instance. The method may include selecting a second distinct instance of the first data topic. The method may include selecting a second texture and applying the second texture to a second mesh corresponding with the second distinct instance. The method may also include combining the first mesh and the first texture with the second mesh and the second texture to generate a combined mesh.

Abstract: A projection image generation unit 91 applies a plurality of projection schemes that use the radius of a visual field region of a fisheye-lens camera to an image that is imaged by the fisheye-lens camera to generate a plurality of projection images. A display unit 92 displays the plurality of projection images. A selection acceptance unit 93 accepts a projection image selected by a user from among the plurality of displayed projection images. A projection scheme determination unit 94 determines a projection scheme on the basis of the selected projection image. An output unit 95 outputs an internal parameter of the fisheye-lens camera that corresponds to the determined projection scheme.

Abstract: An immersive ecosystem is provided comprising a VR headset configured to display a 3D rendering to a user and sensor(s) configured to measure a user response to dynamic 3D asset(s) in the 3D rendering. The immersive ecosystem further comprises a processor, an AI engine, and a first non-transitory computer-readable storage medium encoded with program code executable for providing the 3D rendering to the VR headset. The AI engine is operably coupled to a second non-transitory computer-readable storage medium configured to store predetermined response values and time values for dynamic 3D assets. The AI engine comprises a third non-transitory computer-readable storage medium encoded with program code executable for receiving the measured user response, comparing the received user response to the predetermined response value at the predetermined time value, based on the comparison, modifying dynamic 3D asset(s), and communicating the modified dynamic 3D asset(s) to the processor for providing within 3D rendering.

Abstract: There is provided an information processing apparatus to bring a three-dimensional model generated in accordance with observation information, closer to a real object. The information processing apparatus includes: a control section configured to allocate, to a second three-dimensional model being at least a partial three-dimensional model included in a first three-dimensional model, a definite shaped model having a predetermined shape corresponding to a shape of the second three-dimensional model.

Abstract: A preferred method for dynamically displaying virtual and augmented reality scenes can include determining input parameters, calculating virtual photometric parameters, and rendering a VAR scene with a set of simulated photometric parameters.