CONSTRUCTING REFERENCE PICTURE LISTS FOR MULTI-VIEW OR 3DV VIDEO CODING
    71.
    发明申请
    CONSTRUCTING REFERENCE PICTURE LISTS FOR MULTI-VIEW OR 3DV VIDEO CODING 有权
    构建多视图或3DV视频编码的参考图片列表

    公开(公告)号:US20140049604A1

    公开(公告)日:2014-02-20

    申请号:US13968140

    申请日:2013-08-15

    IPC分类号: H04N13/00

    摘要: In one example, a video coder, such as a video encoder or a video decoder, is configured to code a value for a layer identifier in a slice header for a current slice in a current layer of multi-layer video data, and, when the value for the layer identifier is not equal to zero, code a first set of syntax elements in accordance with a base video coding standard, and code a second set of one or more syntax elements in accordance with an extension to the base video coding standard. The second set of syntax elements may include a syntax element representative of a position for an identifier of an inter-layer reference picture of a reference layer in a reference picture list, and the video coder may construct the reference picture list such that the identifier of the inter-layer reference picture is located in the determined position.

    摘要翻译: 在一个示例中,诸如视频编码器或视频解码器的视频编码器被配置为对当前层中多层视频数据中的当前片段的片标题中的层标识符的值进行编码,并且当 层标识符的值不等于零,根据基本视频编码标准对第一组语法元素进行编码,并且根据对基本视频编码标准的扩展来编码第二组一个或多个语法元素 。 第二组语法元素可以包括表示参考图片列表中参考层的层间参考图片的标识符的位置的语法元素,并且视频编码器可以构建参考图片列表,使得参考图片列表的标识符 层间参考图片位于确定的位置。

    CLIPPING LASER INDICES IN PREDICTIVE GEOMETRY CODING FOR POINT CLOUD COMPRESSION

    公开(公告)号:US20240312067A1

    公开(公告)日:2024-09-19

    申请号:US18677789

    申请日:2024-05-29

    IPC分类号: G06T9/00 G01S17/89

    CPC分类号: G06T9/001 G01S17/89

    摘要: A method of encoding a point cloud includes determining, by one or more processors, a quantity of lasers used to capture light detection and ranging (LIDAR) data that represents the point cloud; and encoding, by the one or more processors, a laser index for a current node of the point cloud, wherein encoding the laser index comprises: obtaining a predicted laser index value of the current node; determining a residual laser index value for the current node, wherein determining the residual laser index value comprises constraining a sum of the residual laser index value and the predicted laser index value to be less than or equal to the determined quantity of lasers minus one; and encoding, in a bitstream, one or more syntax elements that represent the residual laser index value.

    ATTRIBUTE CODING FOR POINT CLOUD COMPRESSION
    75.
    发明公开

    公开(公告)号:US20240233196A9

    公开(公告)日:2024-07-11

    申请号:US18490467

    申请日:2023-10-19

    IPC分类号: G06T9/00

    CPC分类号: G06T9/002

    摘要: A method of encoding point cloud data includes receiving, for a first encoding process, geometry data of the point cloud data of a source point cloud; encoding, in accordance with the first encoding process, the geometry data to generate encoded geometry data of a target point cloud and a geometry bitstream; decoding the encoded geometry data to generate reconstructed geometry data; performing an attribute recomputing process on attribute data of the point cloud data of the source point cloud based on the reconstructed geometry data to generate recomputed, reconstructed point cloud data of the target point cloud; and encoding, in accordance with a second encoding process, the recomputed, reconstructed point cloud data to generate an attribute bitstream.

    DECODING ATTRIBUTE VALUES IN GEOMETRY-BASED POINT CLOUD COMPRESSION

    公开(公告)号:US20240185470A1

    公开(公告)日:2024-06-06

    申请号:US18488816

    申请日:2023-10-17

    IPC分类号: G06T9/00

    CPC分类号: G06T9/001

    摘要: A device for processing point cloud data is configured to determine a first attribute value for a first point of a point cloud, the first point being a closest already-decoded point to a current point of the point cloud; determine second and third attribute values for second and third points of the point cloud, the second and third points being second and third closest already-decoded points; determine a fourth attribute value for a fourth point of the point cloud, the fourth point being an already-decoded point that is either further from, or the same distance to, the current point as the third point; generate a set of predictor candidates with a subset of the first attribute value, the second attribute value, the third attribute value, and the fourth attribute value based on a comparison of a location of the second point to a location of the third point.