Abstract:
Techniques and systems are provided for providing recommendations for extended reality systems. In some examples, a system determines one or more environmental features associated with a real-world environment of an extended reality system. The system determines one or more user features associated with a user of the extended reality system. The system also outputs, based on the one or more environmental features and the one or more user features, a notification associated with at least one application supported by the extended reality system.
Abstract:
Methods, systems, and devices for deep learning based head motion prediction for extended reality are described. The head pose prediction may involve training one or more layers of a machine learning network based on application data and an estimated head motion range associated with the extended reality system. The network may receive one or more bias corrected inertial measurement unit (IMU) measurements based on a sensor. The network may model a relative head pose of the user as a polynomial of time over a prediction interval based on the bias corrected IMU measurements and the trained one or more layers of the machine learning network. The network may determine a future relative head pose of the user based on the polynomial (e.g., which may be used for virtual object generation, display, etc. within an extended reality system).
Abstract:
A method of determining a reference coordinate system includes: obtaining information indicative of a direction of gravity relative to a device; and converting an orientation of a device coordinate system using the direction of gravity relative to the device to produce the reference coordinate system. The method may also include setting an origin of the reference coordinate system and/or determining a scale value of the reference coordinate system. The method may also include refining the reference coordinate system.
Abstract:
An example system includes a first computing device comprising a first graphics processing unit (GPU) implemented in circuitry, and a second computing device comprising a second GPU implemented in circuitry. The first GPU is configured to perform a first portion of an image rendering process to generate intermediate graphics data and send the intermediate graphics data to the second computing device. The second GPU is configured to perform a second portion of the image rendering process to render an image from the intermediate graphics data. The first computing device may be a video game console, and the second computing device may be a virtual reality (VR) headset that warps the rendered image to produce a stereoscopic image pair.
Abstract:
Techniques are presented for constructing a digital representation of a physical environment. In some embodiments, a method includes obtaining image data indicative of the physical environment; receiving gesture input data from a user corresponding to at least one location in the physical environment, based on the obtained image data; detecting at least one discontinuity in the physical environment near the at least one location corresponding to the received gesture input data; and generating a digital surface corresponding to a surface in the physical environment, based on the received gesture input data and the at least one discontinuity.
Abstract:
Methods, systems, computer-readable media, and apparatuses for constructing a representation of a planar object are presented. In some embodiments, techniques for constructing a representation of a planar object are disclosed. According to some embodiments, a method for constructing a representation of a planar object may include obtaining a depth image of a physical scene as captured from a viewing position. The depth image may comprise a plurality of depth values and corresponding to a plurality of points in the physical scene. The method may further include identifying a planar surface along which the planar object is estimated to be positioned. Furthermore, the method may include constructing a support map. Moreover, the method may include constructing an occlusion map, the occlusion map indicating portions of the planar surface where the planar object is missing. Subsequently, the method may include constructing a representation of at least one boundary of the planar object, using the occlusion map.
Abstract:
Methods, systems, computer-readable media, and apparatuses for constructing a representation of a planar object are presented. In some embodiments, techniques for constructing a representation of a planar object are disclosed. According to some embodiments, a method for constructing a representation of a planar object may include obtaining a depth image of a physical scene as captured from a viewing position. The depth image may comprise a plurality of depth values and corresponding to a plurality of points in the physical scene. The method may further include identifying a planar surface along which the planar object is estimated to be positioned. Furthermore, the method may include constructing a support map. Moreover, the method may include constructing an occlusion map, the occlusion map indicating portions of the planar surface where the planar object is missing. Subsequently, the method may include constructing a representation of at least one boundary of the planar object, using the occlusion map.
Abstract:
Systems, methods, and computer-readable media are provided for providing pose estimation in extended reality systems. An example method can include tracking, in a lower-power processing mode using a set of lower-power circuit elements on an integrated circuit, a position and orientation of a computing device during a lower-power processing period, the set of lower-power circuit elements including a static random-access memory (SRAM); suspending, based on a triggering event, the tracking in the lower-power processing mode; initiating a higher-power processing mode for tracking the position and orientation of the computing device during a higher-power processing period; and tracking, in the higher-power processing mode using a set of higher-power circuit elements on the integrated circuit and a dynamic random-access memory (DRAM), the position and orientation of the computing device during the higher-power processing period.
Abstract:
This disclosure provides systems, methods, and devices for wireless communication that support enhanced beam management using extended reality (XR) perception data. In a first aspect, a method of wireless communication includes establishing a communication connection between a user equipment (UE) and a serving base station using a current serving beam selected by the UE from a plurality of available beams paired with a serving base station beam. The method further includes obtaining, perception information from one or more extended reality sensors associated with the UE and determining, in response to detection of UE movement, a transpositional representation of the movement using the perception information. The UE may then select a new serving beam in accordance with the transpositional representation. Other aspects and features are also claimed and described.
Abstract:
Systems and techniques are provided for modeling three-dimensional (3D) meshes using multi-view image data. An example method can include determining, based on a first image of a target, first 3D mesh parameters for the target corresponding to a first coordinate frame; determining, based on a second image of the target, second 3D mesh parameters for the target corresponding to a second coordinate frame; determining third 3D mesh parameters for the target in a third coordinate frame, the third 3D mesh parameters being based on the first and second 3D mesh parameters and relative rotation and translation parameters of image sensors that captured the first and second images; determining a loss associated with the third 3D mesh parameters, the loss being based on the first and second 3D mesh parameters and the relative rotation and translation parameters; determining 3D mesh parameters based on the loss and third 3D mesh parameters.