AUGMENTED REALITY SYSTEM
    1.
    发明申请

    公开(公告)号:US20210390777A1

    公开(公告)日:2021-12-16

    申请号:US16897596

    申请日:2020-06-10

    Applicant: Arm Limited

    Abstract: An AR system is provided, the AR system including one or more sensors, storage, one or more communications modules, and one or more processors. The one or more sensors generate sensed data representing at least part of an environment in which the AR system is located. The one or more communications modules transmit localization data to be used in determining the location and orientation of the AR system. The one or more processors are arranged to obtain sensed data representing an environment in which the AR system is located, process the sensed data to identify a first portion of the sensed data which represents redundant information, derive localization data, wherein the localization data is derived from the sensed data and the first portion is obscured during the derivation of the localization data, and transmit at least a portion of the localization data using the one or more communication modules.

    METHOD FOR MEASURING DEPTH USING A TIME-OF-FLIGHT DEPTH SENSOR

    公开(公告)号:US20220099836A1

    公开(公告)日:2022-03-31

    申请号:US17037146

    申请日:2020-09-29

    Abstract: A method and apparatus for measuring depth using a time-of-flight (ToF) depth sensor is described. The apparatus includes an emitter configured to emit a signal towards a scene comprising one or more regions with light or sound, this emitter being controllable to adjust at least one of an intensity and a modulation frequency of the signal output from the emitter. The apparatus also includes a signal sensor, configured to detect an intensity of the signal from the emitter that has been reflected by the scene. A controller is configured to receive context information about the scene for depth capture by the time-of-flight depth sensor and to adjust at least one of the intensity and modulation frequency of the signal output by the emitter in dependence on the context information.

    AUGMENTED REALITY SYSTEM
    3.
    发明申请

    公开(公告)号:US20220060481A1

    公开(公告)日:2022-02-24

    申请号:US17001187

    申请日:2020-08-24

    Applicant: Arm Limited

    Abstract: A computer-implemented method for an augmented-reality system is provided. The computer-implemented method comprises obtaining sensed data, representing an environment in which the AR system is located, determining that the AR system is in a location associated with a first authority characteristic, and controlling access to the sensed data for one or more applications operating in the AR system. Each of the one or more applications is associated with a respective authority characteristic. Controlling access to the sensed data for a said application is performed in dependence on the first authority characteristic and a respective authority characteristic associated with the said application. An AR system comprising one or more sensors, storage for storing sensed data, one or more application modules, and one or more processors arranged to perform the computer-implemented method is provided. A non-transitory computer-readable storage medium comprising computer-readable instructions for performing the computer-implemented method is also provided.

    ESTIMATING CAMERA POSE
    4.
    发明申请

    公开(公告)号:US20220036577A1

    公开(公告)日:2022-02-03

    申请号:US16943859

    申请日:2020-07-30

    Abstract: A system for estimating a current camera pose corresponding to a current point in time using a previous camera pose corresponding to a previous point in time, of a camera configured to generate a sequence of image frames. The system performs operations, including: generating, using one or more neural networks, a neural network pose prediction for the current image frame; and adjusting a previous camera pose using inertial measurement unit data representing a motion of the camera between the previous point in time and the current point in time, to provide an inertial measurement unit pose prediction for the current point in time. The inertial measurement unit pose prediction, and the neural network pose prediction are combined in order to estimate the current camera pose.

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