Real-time video feed presentation enhancement system

    公开(公告)号:US11695971B2

    公开(公告)日:2023-07-04

    申请号:US17501549

    申请日:2021-10-14

    Applicant: Prezi, Inc.

    Abstract: A system is configured to enhance a video feed in real time. A live video feed captured by a video capturing device is received. A presentation of the live video feed on one or more client devices is enhanced. The enhancing includes causing a first content item of a plurality of content items to be displayed at a first location within the presentation of the live video feed. Based on a detecting of a first instance of a first gesture made by a hand at the first location in the live video feed, a content item manipulation mode with respect to the first content item is entered. The entering of the content item manipulation mode with respect to the first content includes at least one of causing the first content item to be moved within the presentation of the live video feed based on a movement of the hand or causing a scale of the first content item to be changed within the presentation of the live video feed based on a detecting of a second gesture made by the hand.

    RESIDUAL ENTROPY COMPRESSION FOR CLOUD-BASED VIDEO APPLICATIONS

    公开(公告)号:US20180310029A1

    公开(公告)日:2018-10-25

    申请号:US16020018

    申请日:2018-06-27

    CPC classification number: H04N19/94 H04N19/46 H04N19/91 H04N21/274

    Abstract: Residual vectors are compressed in a lossless compression scheme suitable for cloud DVR video content applications. Thus, a cloud DVR service provider can take many copies of the same file stored in the cloud and save storage space by compressing those copies while still maintaining their status as distinct copies, one per user. Vector quantization is used for compressing already-compressed video streams (e.g., MPEG streams). As vector quantization is a lossy compression scheme, the residual vector has to be stored to regenerate the original video stream at the decoding (playback) node. Entropy coding schemes like Arithmetic or Huffman coding can be used to compress the residual vectors. Additional strategies can be implemented to further optimize this residual compression. In some embodiments, the techniques operate to provide a 25-50% improvement in compression. Storage space is thus more efficiently used and video transmission may be faster in some cases.

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