SYSTEMS AND METHODS FOR SIMULATENOUS LOCALIZATION AND MAPPING

    公开(公告)号:US20210201520A1

    公开(公告)日:2021-07-01

    申请号:US17249789

    申请日:2021-03-12

    Applicant: Snap Inc.

    Abstract: Various embodiments provide systems, methods, devices, and instructions for performing simultaneous localization and mapping (SLAM) that involve initializing a SLAM process using images from as few as two different poses of a camera within a physical environment. Some embodiments may achieve this by disregarding errors in matching corresponding features depicted in image frames captured by an image sensor of a mobile computing device, and by updating the SLAM process in a way that causes the minimization process to converge to global minima rather than fall into a local minimum.

    Sensor misalignment compensation
    6.
    发明授权

    公开(公告)号:US11575874B2

    公开(公告)日:2023-02-07

    申请号:US17553287

    申请日:2021-12-16

    Applicant: Snap Inc.

    Abstract: Camera compensation methods and systems that compensate for misalignment of sensors/camera in stereoscopic camera systems. The compensation includes identifying a pitch angle offset between a first camera and a second camera, determining misalignment of the first and second cameras from the identified pitch angle offset, determining a relative compensation delay responsive to the determined misalignment, introducing the relative compensation delay to image streams produced by the cameras, and producing a stereoscopic image on a display from the first and second image streams with the introduced delay.

    Systems and methods for simulatenous localization and mapping

    公开(公告)号:US10984547B2

    公开(公告)日:2021-04-20

    申请号:US16532131

    申请日:2019-08-05

    Applicant: Snap Inc.

    Abstract: Various embodiments provide systems, methods, devices, and instructions for performing simultaneous localization and mapping (SLAM) that involve initializing a SLAM process using images from as few as two different poses of a camera within a physical environment. Some embodiments may achieve this by disregarding errors in matching corresponding features depicted in image frames captured by an image sensor of a mobile computing device, and by updating the SLAM process in a way that causes the minimization process to converge to global minima rather than fall into a local minimum.

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