TECHNIQUES FOR ADAPTIVE VIDEO STREAMING
    221.
    发明申请
    TECHNIQUES FOR ADAPTIVE VIDEO STREAMING 有权
    适应性视频流的技术

    公开(公告)号:US20130329781A1

    公开(公告)日:2013-12-12

    申请号:US13631605

    申请日:2012-09-28

    Applicant: APPLE INC.

    Abstract: A vide coding server may code a common video sequence into a plurality of coded data streams, each coded data stream representing the video sequence coded using coding parameters tailored for a respective transmission bit rate. The coding may cause a set of transmission units from among the coded data streams to include coded video data from a common point of the video sequence, and a first coded frame of each transmission unit of the set to be a synchronization frame. A manifest file may be built representing an index of transmission units of the respective coded data streams. The coded data streams and manifest file may be stored by the server for delivery to a client device. During download and decode, the chunks may be decoded efficiently even when switching among streams because the first frame in each chunk is a synchronization frame.

    Abstract translation: 视频编码服务器可以将公共视频序列编码为多个编码数据流,每个编码数据流表示使用针对相应传输比特率定制的编码参数进行编码的视频序列。 编码可以使得编码数据流中的一组传输单元包括来自视频序列的公共点的编码视频数据和作为同步帧的组的每个传输单元的第一编码帧。 可以构建表示相应编码数据流的传输单元的索引的清单文件。 编码数据流和清单文件可以由服务器存储以传送到客户端设备。 在下载和解码期间,即使在每个块中的第一帧是同步帧时,即使切换流之间也可以有效地解码该块。

    SIGNAL SHAPING TECHNIQUES FOR VIDEO DATA THAT IS SUSCEPTIBLE TO BANDING ARTIFACTS
    222.
    发明申请
    SIGNAL SHAPING TECHNIQUES FOR VIDEO DATA THAT IS SUSCEPTIBLE TO BANDING ARTIFACTS 有权
    视频数据的信号形成技术无法阻挡装置

    公开(公告)号:US20130235942A1

    公开(公告)日:2013-09-12

    申请号:US13631428

    申请日:2012-09-28

    Applicant: APPLE INC.

    Abstract: Video coding systems and methods protect against banding artifacts in decoded image content. According to the method, a video coder may identify, from content of pixel blocks of a frame of video data, which pixel blocks are likely to exhibit banding artifacts from the video coding/decoding processes. The video coder may assemble regions of the frame that are likely to exhibit banding artifacts based on the identified pixel blocks' locations with respect to each other. The video coder may apply anti-banding processing to pixel blocks within one or more of the identified regions and, thereafter, may code the processed frame by a compression operation.

    Abstract translation: 视频编码系统和方法保护解码图像内容中的带状伪像。 根据该方法,视频编码器可以根据视频数据帧的像素块的内容从视频编码/解码处理中识别哪些像素块可能呈现带状伪影。 视频编码器可以基于所识别的像素块相对于彼此的位置来组合可能呈现带状伪影的帧的区域。 视频编码器可以对所识别的一个或多个区域内的像素块应用反绑带处理,然后可以通过压缩操作来对经处理的帧进行编码。

    Immersive video streaming using view-adaptive prefetching and buffer control

    公开(公告)号:US11924391B2

    公开(公告)日:2024-03-05

    申请号:US18083468

    申请日:2022-12-16

    Applicant: Apple Inc.

    Abstract: A system obtains a data set representing immersive video content for display at a display time, including first data representing the content according to a first level of detail, and second data representing the content according to a second higher level of detail. During one or more first times prior to the display time, the system causes at least a portion of the first data to be stored in a buffer. During one or more second times prior to the display time, the system generates a prediction of a viewport for displaying the content to a user at the display time, identifies a portion of the second data corresponding to the prediction of the viewport, and causes the identified portion of the second data to be stored in the video buffer. At the display time, the system causes the content to be displayed to the user using the video buffer.

    Modular Machine Learning Architecture
    228.
    发明公开

    公开(公告)号:US20230147442A1

    公开(公告)日:2023-05-11

    申请号:US17831738

    申请日:2022-06-03

    Applicant: Apple Inc.

    CPC classification number: G06N3/045

    Abstract: In an example method, a system accesses first input data and a machine learning architecture. The machine learning architecture includes a first module having a first neural network, a second module having a second neural network, and a third module having a third neural network. The system generates a first feature set representing a first portion of the first input data using the first neural network, and a second feature set representing a second portion of the first input data using the second neural network. The system generates, using the third neural network, first output data based on the first feature set and the second feature set.

Patent Agency Ranking