Periodic parameter estimation for visual-inertial tracking systems

    公开(公告)号:US11662805B2

    公开(公告)日:2023-05-30

    申请号:US17301655

    申请日:2021-04-09

    Applicant: Snap Inc.

    CPC classification number: G06F3/012 G06F3/038 H04L67/131 G06F2203/0383

    Abstract: A method for calibrating a visual-inertial tracking system is described. A device operates the visual-inertial tracking system without receiving a tracking request from a virtual object display application. In response to operating the visual-inertial tracking system, the device accesses sensor data from sensors at the device. The device identifies, based on the sensor data, a first calibration parameter value of the visual-inertial tracking system and stores the first calibration parameter value. The system detects a tracking request from the virtual object display application. In response to the tracking request, the system accesses the first calibration parameter value and determines a second calibration parameter value from the first calibration parameter value.

    DIRECT SCALE LEVEL SELECTION FOR MULTILEVEL FEATURE TRACKING UNDER MOTION BLUR

    公开(公告)号:US20220377238A1

    公开(公告)日:2022-11-24

    申请号:US17521109

    申请日:2021-11-08

    Applicant: Snap Inc.

    Abstract: A method for mitigating motion blur in a visual-inertial tracking system is described. In one aspect, the method includes accessing a first image generated by an optical sensor of the visual tracking system, accessing a second image generated by the optical sensor of the visual tracking system, the second image following the first image, determining a first motion blur level of the first image, determining a second motion blur level of the second image, identifying a scale change between the first image and the second image, determining a first optimal scale level for the first image based on the first motion blur level and the scale change, and determining a second optimal scale level for the second image based on the second motion blur level and the scale change.

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