Abstract: Systems and methods are described for capturing, using a forward-facing camera associated with a head-mounted augmented reality (AR) head-mounted display (HMD), images of portions of first and second display devices in an environment, the first and second display devices displaying first and second portions of content related to an AR presentation, and displaying a third portion of content related to the AR presentation on the AR HMD, the third portion determined based upon the images of portions of the first and second display devices captured using the forward-facing camera. Moreover, the first and second display devices may be active stereo display, and the AR HMD may simultaneously function as shutter glasses.

Abstract: A virtual fabrication environment for semiconductor device fabrication that includes an analytics module for performing key parameter identification, process model calibration and variability analysis is discussed.

Abstract: A visual lens system is described that identifies, automatically and without user intervention, digital tool parameters for achieving a visual appearance of an image region in raster image data. To do so, the visual lens system processes raster image data using a tool region detection network trained to output a mask indicating whether the digital tool is useable to achieve a visual appearance of each pixel in the raster image data. The mask is then processed by a tool parameter estimation network trained to generate a probability distribution indicating an estimation of discrete parameter configurations applicable to the digital tool to achieve the visual appearance. The visual lens system generates an image tool description for the parameter configuration and incorporates the image tool description into an interactive image for the raster image data. The image tool description enables transfer of the digital tool parameter configuration to different image data.

Abstract: A system and method are disclosed to generate one or more mixed-reality visualizations and objects to facilitate efficient interaction with large volumes of data. Embodiments include a computer comprising a processor and memory and a mixed-reality display device comprising a display and one or more sensors. Embodiments generate a mixed-reality object comprising a first cuboid, the first cuboid comprising one or more adjustable display dimensions corresponding to one or more key process indicators (KPIs) and one or more cubelets divided along at least one of the one or more adjustable display dimensions. Embodiments display the mixed-reality object on the display, and adjust at least one of the one or more adjustable display dimensions in response to receiving a first input to the one or more sensors. In response to a second input, embodiments transform the one or more cubelets of the first cuboid.

Abstract: This application is directed to matching edges of polygons representing neighboring regions in a map user application. A computer system obtains a first polygon and a second polygon, and the second polygon is connected to the first polygon via polygon edges that are at least partially mismatched. Automatically and without user intervention, the computer system combines the first polygon and the second polygon to form a joined polygon defined by an outline of the first polygon and the second polygon. A region defined by the second polygon is subtracted from a region defined by the joined polygon to form a new region. The computer system defines an updated first polygon as an outline of the new region and renders, on a screen, the updated first polygon and the second polygon with matching edges.

Abstract: Methods, apparatuses, systems, and computer program products are disclosed for managing a feature emphasis interface element in association with a card-based collaborative workflow management system. In an example embodiment, an apparatus receives a feature status request, retrieves feature release data and user data, and determines a feature emphasis value based at least in part on the retrieved feature release data and user data. For each circumstance wherein the feature emphasis value satisfies a display feature threshold, the apparatus causes rendering of a feature emphasis interface element to a card-based collaborative workflow management user interface in association with a feature interface representation and for each circumstance wherein the feature emphasis value fails to satisfy the display feature threshold, cause rendering of the feature interface representation to the card-based collaborative workflow management user interface.

Abstract: Techniques to improve operation of an augmented reality device and/or system utilizing fiducial markers and/or colorspace conversions are provided. In various embodiments, one or more fiducial markers in an environment associated with the augmented reality device are updated and optimized in relation to environmental changes utilizing one or more color-space conversion techniques. Other embodiments are described and claimed.

Abstract: Augmented reality systems and methods for automatically repositioning a virtual object with respect to a destination object in a three-dimensional (3D) environment of a user are disclosed. The systems and methods can automatically attach the target virtual object to the destination object and re-orient the target virtual object based on the affordances of the virtual object or the destination object. The systems and methods can also track the movement of a user and detach the virtual object from the destination object when the user's movement passes a threshold condition.

Abstract: A computing system configured to: (1) render, via a graphical user interface (GUI) displayed by a client station, a three-dimensional view of a construction project using a three-dimensional model file that defines a set of meshes representing physical objects of the construction project, wherein each mesh comprises a set of triangular faces, and wherein the GUI includes a measurement tool for obtaining a shortest distance between a first mesh and a second mesh; (2) receive a request to obtain the shortest distance between the first mesh and the second mesh; (3) calculate a set of distances potentially comprising the shortest distance between the first mesh and the second mesh by first reducing one or both of: (i) the number of faces between which distances are calculated and (ii) the number of distances that are calculated; and (4) determine the shortest distance between the first mesh and the second mesh.

Abstract: A system and method for processing data wherein one or more user selections of source data and an input defining one or more operations to be performed on the selected source data are received to generate processed data for display as a chart; the source data is retrieved from at least one data source, the source data is processed according to the defined one or more operations to generate processed data for output for display as a chart, the chart is stored as data defining the one or more operations and data identifying the source data operated on, a further user selection is received to redisplay the chart; retrieving the source data from the at least one data source; and the source data is processed according to the defined one or more operations to generate the processed data for output for redisplay as the chart.

Abstract: A virtual representation of an operating room is generated based on robot information and sensing of the OR with depth cameras. One of the depth cameras is integrated with a portable electronic device, operated by a local user in the operating room. The virtual representation of the OR is communicated to the virtual reality headset, with three-dimensional point cloud data. A virtual reality environment is rendered to a display of the virtual reality headset, operated by a remote user. A virtual representation of the remote user is rendered in augmented reality to a display of the portable electronic device.

Abstract: Vector object transformation techniques are described that support generation of a transformed vector object based on a first vector object and a second vector object. A plurality of paths for a first and second vector object, for instance, are generated. Corresponding paths are determined by detecting which of the plurality of paths from the first vector object correspond to which of the plurality of paths from the second vector object. A mapping of control points between the first and second vector objects is generated. Using the mapping, a transformation of the first vector object is generated by adjusting one or more control points of the first vector object. As a result, the transformed vector object includes visual characteristics based on both the first vector object and the second vector object.

Abstract: Methods, systems, and media for generating compressed images are provided. In some embodiments, the method comprises: identifying a multi-plane image, MPI, that represents a three-dimensional image, wherein the MPI comprises a plurality of fronto-parallel planes; splitting the MPI into a plurality of sub-volumes, wherein each sub-volume in the plurality of sub-volumes includes a subset of the plurality of fronto-parallel planes; calculating, for each sub-volume of the MPI, a depthmap; converting each depthmap to a mesh, wherein each mesh corresponds to a layer of a plurality of layers associated with a multi-depth image, MDI, to be rendered; calculating, for each layer of the plurality of layers, an image; and storing the meshes corresponding to the plurality of layers of the MDI and the images corresponding to the plurality of layers of the MDI as the MDI.

Abstract: A device receives an image including image data of a scale model of a vehicle, and processes the image data, with a model, to identify a make, a model, and a year represented by the scale model. The device determines augmented reality (AR) vehicle information based on the make, the model, and the year represented by the scale model of the vehicle, and provides the AR vehicle information to enable a user device to associate the AR vehicle information with the image of the scale model of the vehicle. The device receives an input associated with the AR vehicle information, and determines updated AR vehicle information based on the input associated with the AR vehicle information. The device provides the updated AR vehicle information to enable the user device to associate the updated augmented reality vehicle information with the image of the scale model of the vehicle.

Abstract: A surgical hub may be configured to receive an image from a laparoscopic scope and surgical information from at least one surgical instrument. The surgical hub may be operatively connected to multiple displays such as a primary display and a secondary display. The surgical hub may generate visualization data for the primary display. The surgical hub may obtain a visualization control mode based on a visualization control parameter and may determine whether to generate a different set of visualization data for a secondary display based on the visualization control mode. When the visualization control mode supports multiple display capabilities, the surgical hub may generate the visualization data specifically for the secondary display. When the visualization control mode does not support multiple display capabilities, the surgical hub may send the same the visualization data for display at the secondary display as the primary display.

Abstract: An image processing apparatus includes a processor configured to display boundaries each of which encloses a respective one of multiple candidate regions that correspond to foreground objects in an image, detect a single selecting operation, and extract a target region corresponding to one of the foreground objects from one or more candidate regions of the multiple candidate regions. The one or more candidate regions are selected by the single selecting operation.

Abstract: In some embodiments, a model training system obtains a set of animation models. For each of the animation models, the model training system renders the animation model to generate a sequence of video frames containing a character using a set of rendering parameters and extracts joint points of the character from each frame of the sequence of video frames. The model training system further determines, for each frame of the sequence of video frames, whether a subset of the joint points are in contact with a ground plane in a three-dimensional space and generates contact labels for the subset of the joint points. The model training system trains a contact estimation model using training data containing the joint points extracted from the sequences of video frames and the generated contact labels. The contact estimation model can be used to refine a motion model for a character.

Abstract: Two-dimensional objects are displayed upon a user interface; user input selects an area and selects a machine learning model for execution. The results are displayed as an overlay over the objects in the user interface. User input selects a second model for execution; the result of this execution is displayed as a second overlay over the objects. A first overlay from a model is displayed over a set of objects in a user interface and a ground truth corresponding to the objects is displayed as a second overlay on the user interface. User input selects the ground truth overlay as a reference and causes a comparison of the first overlay with the ground truth overlay; the visual data from the comparison is displayed on the user interface. A comparison of M inference overlays with N reference overlays is performed and visual data from the comparison is displayed on the interface.

Abstract: Aspects include a multistage collector to receive outputs from plural processing elements. Processing elements may comprise (each or collectively) a plurality of clusters, with one or more ALUs that may perform SIMD operations on a data vector and produce outputs according to the instruction stream being used to configure the ALU(s). The multistage collector includes substituent components each with at least one input queue, a memory, a packing unit, and an output queue; these components can be sized to process groups of input elements of a given size, and can have multiple input queues and a single output queue. Some components couple to receive outputs from the ALUs and others receive outputs from other components. Ultimately, the multistage collector can output groupings of input elements. Each grouping of elements (e.g., at input queues, or stored in the memories of component) can be formed based on matching of index elements.

Abstract: Systems and methods of generating a three-dimensional (3D) reconstruction of a scene or environment surrounding a user of a spatial computing system, such as a virtual reality, augmented reality or mixed reality system, using only multiview images comprising RGB images, and without the need for depth sensors or depth data from sensors. Features are extracted from a sequence of frames of RGB images and back-projected using known camera intrinsics and extrinsic s into a 3D voxel volume wherein each pixel of the voxel volume is mapped to a ray in the voxel volume. The back-projected features are fused into the 3D voxel volume. The 3D voxel volume is passed through a 3D convolutional neural network to refine the and regress truncated signed distance function values at each voxel of the 3D voxel volume.