Generating stereoscopic light field panoramas using concentric viewing circles

    公开(公告)号:US11368669B2

    公开(公告)日:2022-06-21

    申请号:US17133271

    申请日:2020-12-23

    Abstract: An example system for generating stereoscopic light field panoramas includes at least one memory; and at least one processor to execute instructions to: access images of a scene captured by a plurality of cameras, the images including light field information associated with the scene; generate, based on first portions of the images, a first stereoscopic light field panorama for a first perspective associated with a left eye viewpoint of the scene, the left eye viewpoint associated with a left eye position on a first circle; and generate, based on second portions of the images, a second stereoscopic light field panorama for a second perspective associated with a right eye viewpoint of the scene, the right eye viewpoint associated with a right eye position on a second circle, the first circle being different than and concentric to the second circle.

    Generating Stereoscopic Light Field Panoramas Using Concentric Viewing Circles

    公开(公告)号:US20210120225A1

    公开(公告)日:2021-04-22

    申请号:US17133271

    申请日:2020-12-23

    Abstract: An example system for generating stereoscopic light field panoramas includes at least one memory; and at least one processor to execute instructions to: access images of a scene captured by a plurality of cameras, the images including light field information associated with the scene; generate, based on first portions of the images, a first stereoscopic light field panorama for a first perspective associated with a left eye viewpoint of the scene, the left eye viewpoint associated with a left eye position on a first circle; and generate, based on second portions of the images, a second stereoscopic light field panorama for a second perspective associated with a right eye viewpoint of the scene, the right eye viewpoint associated with a right eye position on a second circle, the first circle being different than and concentric to the second circle.

    Techniques for adding interactive features to videos

    公开(公告)号:US09922681B2

    公开(公告)日:2018-03-20

    申请号:US15142475

    申请日:2016-04-29

    CPC classification number: G11B27/031

    Abstract: Techniques are disclosed for adding interactive features to videos to enable users to create new media using a dynamic blend of motion and still imagery. The interactive techniques can include allowing a user to change the starting time of one or more subjects in a given video frame, or only animate/play a portion of a given frame scene. The techniques may include segmenting each frame of a video to identify one or more subjects within each frame, selecting (or receiving selections of) one or more subjects within the given frame scene, tracking the selected subject(s) from frame to frame, and alpha-matting to play/animate only the selected subject(s). In some instances, segmentation, selection, and/or tracking may be improved and/or enhanced using pixel depth information (e.g., using a depth map).

    Point-to-point distance measurements in 3D camera images

    公开(公告)号:US09792687B2

    公开(公告)日:2017-10-17

    申请号:US14841609

    申请日:2015-08-31

    Abstract: Systems and methods for determining point-to-point distances from 3D image data. In some embodiments, two measure points, for example specified by a user, represent endpoints on an object of interest within an image frame. Assuming all points lying between these endpoints also belong to the object of interest, additional 3D data associated with points that lie along a measurement line defined by the measure points may be leveraged to provide a robust distance measurement. In some embodiments, total least squares fitting is performed, for example through Robust Principal Component Analysis (RPCA) to identify linear structures within the set of the 3D coordinates on the measurement line. In some exemplary embodiments, the minimum covariance determinant (MCD) estimator of the covariance matrix of the data is computed for a highly robust estimate of multivariate location and multivariate scatter.

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