Combining independent solutions to an image or video processing task

    公开(公告)号:US10824911B2

    公开(公告)日:2020-11-03

    申请号:US15973184

    申请日:2018-05-07

    Applicant: GoPro, Inc.

    Abstract: An algorithm for performing an image or video processing task is generated that may be used to combine a plurality of different independent solutions to the image or video processing task in an optimized manner. A plurality of base algorithms may be applied to a training set of images or video and a first generation of different combining algorithms may be applied to combine the respective solutions from each of the respective base algorithms into respective combined solutions. The respective combined solutions may be evaluated to generate respective fitness scores representing measures of how well the plurality of different combining algorithms each perform the image or video processing task. The algorithms may be iteratively updated to generate an optimized combining algorithm that may be applied to an input image or video.

    Apparatus and methods for the selection of one or more frame interpolation techniques

    公开(公告)号:US10057538B2

    公开(公告)日:2018-08-21

    申请号:US15407089

    申请日:2017-01-16

    Applicant: GoPro, Inc.

    CPC classification number: H04N7/014 H04N11/20

    Abstract: Methods and apparatus for the generation of interpolated frames of video data. In one embodiment, the interpolated frames of video data are generated by obtaining two or more frames of video data; performing Lagrangian interpolation on one or more portions of the obtained two or more frames of video data to generate a Lagrangian interpolated image; performing Eulerian interpolation on one or more portions of the obtained two or more frames to generate a Eulerian interpolated image; and when the Lagrangian interpolated image and the Eulerian interpolated image should be combined, computing an average interpolated image using the Lagrangian interpolated image and the Eulerian interpolated image; otherwise, selecting either the Lagrangian interpolated image or the Eulerian interpolated image; and generating an interpolated frame of video data using one or more of the average interpolated image, the Lagrangian interpolated image, or the Eulerian interpolated image.

    Apparatus and methods for frame interpolation based on spatial considerations

    公开(公告)号:US10003768B2

    公开(公告)日:2018-06-19

    申请号:US15278976

    申请日:2016-09-28

    Applicant: GoPro, Inc.

    CPC classification number: H04N7/0137 G06T3/40 H04N7/0127 H04N7/014

    Abstract: Apparatus and methods for the generation of interpolated frames of video data. In one embodiment, a computerized apparatus is disclosed that includes a video data interface configured to receive frames of video data; a processing apparatus in data communication with the video data interface; and a storage apparatus in data communication with the processing apparatus. The computerized apparatus is further configured to: receive frames of captured video data; retrieve capture parameters associated with the frames of captured video data; generate optical flow parameters from the frames of captured video data; ascribe differing weights based on the capture parameters and/or the optical flow parameters; generate frames of interpolated video data for the frames of captured video data based at least in part on the ascribed weights; and compile a resultant video stream using the frames of interpolated video data and the frames of captured video data.

    SCENE AND ACTIVITY IDENTIFICATION IN VIDEO SUMMARY GENERATION BASED ON MOTION DETECTED IN A VIDEO

    公开(公告)号:US20190180110A1

    公开(公告)日:2019-06-13

    申请号:US16256669

    申请日:2019-01-24

    Applicant: GoPro, Inc.

    Abstract: Video and corresponding metadata is accessed. Events of interest within the video are identified based on the corresponding metadata, and best scenes are identified based on the identified events of interest. In one example, best scenes are identified based on the motion values associated with frames or portions of a frame of a video. Motion values are determined for each frame and portions of the video including frames with the most motion are identified as best scenes. Best scenes may also be identified based on the motion profile of a video. The motion profile of a video is a measure of global or local motion within frames throughout the video. For example, best scenes are identified from portion of the video including steady global motion. A video summary can be generated including one or more of the identified best scenes.

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