SYSTEMS, METHODS AND APPARATUS FOR COMPRESSING VIDEO CONTENT

    公开(公告)号:US20200336725A1

    公开(公告)日:2020-10-22

    申请号:US16866447

    申请日:2020-05-04

    Applicant: GoPro, Inc.

    Abstract: Apparatus and methods for characterizing panoramic content, such as by a wide field of view and large image size. In one implementation, a panoramic image may be mapped to a cube or any other projection e.g icosahedron or octahedron. The disclosure exploits content continuity between facets, such as in the case of encoding/decoding cube-projected images. One facet may be encoded/decoded independently from other facets to obtain a seed facet. One or more transformed versions of the seed facet may be obtained; e.g., one corresponding to a 90° counterclockwise rotation, another to a 90° clockwise rotation, and one to an 180° rotation. Transformed versions may be used to form an augmented image. The remaining facets of the cube may be encoded using transformed versions within the augmented image. Continuity between transformed facets in the top row of the augmented image and facets in the middle row of the augmented image may be utilized for motion or intra prediction, and to obtain greater encoding performance compared to encoding facets independently.

    AUTOMATIC GENERATION OF VIDEO AND DIRECTIONAL AUDIO FROM SPHERICAL CONTENT

    公开(公告)号:US20200135238A1

    公开(公告)日:2020-04-30

    申请号:US16721561

    申请日:2019-12-19

    Applicant: GoPro, Inc.

    Abstract: A spherical content capture system captures spherical video and audio content. In one embodiment, captured metadata or video/audio processing is used to identify content relevant to a particular user based on time and location information. The platform can then generate an output video from one or more shared spherical content files relevant to the user. The output video may include a non-spherical reduced field of view such as those commonly associated with conventional camera systems. Particularly, relevant sub-frames having a reduced field of view may be extracted from each frame of spherical video to generate an output video that tracks a particular individual or object of interest. For each sub-frame, a corresponding portion of an audio track is generated that includes a directional audio signal having a directionality based on the selected sub-frame.

    IMAGE ALIGNMENT USING A VIRTUAL GYROSCOPE MODEL

    公开(公告)号:US20200077022A1

    公开(公告)日:2020-03-05

    申请号:US16538641

    申请日:2019-08-12

    Applicant: GoPro, Inc.

    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.

    Apparatus and methods for video compression using multi-resolution scalable coding

    公开(公告)号:US10212438B2

    公开(公告)日:2019-02-19

    申请号:US15799837

    申请日:2017-10-31

    Applicant: GoPro, Inc.

    Abstract: Apparatus and methods for digital video data compression via a scalable, multi-resolution approach. In one embodiment, the video content may be encoded using a multi-resolution and/or multi-quality scalable coding approach that reduces computational and/or energy load on a client device. In one implementation, a low fidelity image is obtained based on a first full resolution image. The low fidelity image may be encoded to obtain a low fidelity bitstream. A second full resolution image may be obtained based on the low fidelity bitstream. A portion of a difference image obtained based on the second full resolution image and the first full resolution may be encoded to obtain a high fidelity bitstream. The low fidelity bitstream and the high fidelity bitstream may be provided to e.g., a receiving device.

    IMAGE ALIGNMENT USING A VIRTUAL GYROSCOPE MODEL

    公开(公告)号:US20180316861A1

    公开(公告)日:2018-11-01

    申请号:US15967364

    申请日:2018-04-30

    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.

    Unified image processing for combined images based on spatially co-located zones

    公开(公告)号:US09965883B2

    公开(公告)日:2018-05-08

    申请号:US15724532

    申请日:2017-10-04

    Applicant: GoPro, Inc.

    Abstract: A unified image processing algorithm results in better post-processing quality for combined images that are made up of multiple single-capture images. To ensure that each single-capture image is processed in the context of the entire combined image, the combined image is analyzed to determine portions of the image (referred to as “zones”) that should be processed with the same parameters for various image processing algorithms. These zones may be determined based on the content of the combined image. Alternatively, these zones may be determined based on the position of each single-capture image with respect to the entire combined image or the other single-capture images. Once zones and their corresponding image processing parameters are determined for the combined image, they are translated to corresponding zones each of the single-capture images. Finally, the image processing algorithms are applied to each of the single-capture images using the zone-specified parameters.

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