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.

    Image alignment using a virtual gyroscope model

    公开(公告)号:US09961261B2

    公开(公告)日:2018-05-01

    申请号:US15249347

    申请日:2016-08-26

    Applicant: GoPro, Inc.

    CPC classification number: H04N5/23258 H04N5/23267 H04N5/2328

    Abstract: A target image captured from a fisheye lens or other lens with known distortion parameters may be transformed to align it to a reference image. Corresponding features may be detected in the target image and the reference image. The features may be transformed to a spherical coordinate space. In the spherical space, images may be re-pointed or rotated in three dimensions to align all or a subset of the features of the target image to the corresponding features of the reference image. For example, in a sequence of images, background features of the target image in the spherical image space may be aligned to background features of the reference image in the spherical image space to compensate for camera motion while preserving foreground motion. An inverse transformation may then be applied to bring the images back into the original image space.

    SYSTEMS AND METHODS FOR MULTI-RESOLUTION IMAGE STITCHING

    公开(公告)号:US20180012335A1

    公开(公告)日:2018-01-11

    申请号:US15643123

    申请日:2017-07-06

    Applicant: GoPro, Inc.

    CPC classification number: G06T3/4038 G06T3/4084 H04N5/23238

    Abstract: Systems and methods for providing panoramic image and/or video content using multi-resolution stitching. Panoramic content may include stitched spherical (360-degree) images and/or VR video. In some implementations, multi-resolution stitching functionality may be embodied in a spherical image capture device that may include two lenses configured to capture pairs of hemispherical images. The capture device may obtain images (e.g., representing left and right hemispheres) that may be characterized by 180-degree (or greater) field of view. Source images may be combined using multi-resolution stitching methodology. Source images may be transformed to obtain multiple image components characterized by two or more image resolutions. The stitched image may be encoded using selective encoding methodology including: partitioning source images into a low resolution/frequency and a high resolution/frequency components; stitching low resolution/frequency components using coarse stitching operation, stitching high resolution/high frequency components using a refined stitch operation; combining stitched LF components and stitched HF components.

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