算法中利用的压缩参数主要有帧类型、宏块类型、DC系数、运动矢量。
Compressed parameters include type of frame, type of macroblock, DC coefficients, and motion vectors.
基于降低分辨率的视频代码转换模型，对运动矢量和宏块类型进行了精简。
The motion vectors and macroblock type during video transcoding based on resolution reduction are refined in this paper.
说明：一种具有在场和帧图中出现所有宏块类型和子块类型的编码比特流。
Specification: One kind of bitstream which contains all types of Macroblocks and blocks in the frame and the field.
提出了基于宏块空间复杂度的宏块类型判断算法，有效地降低了视频压缩算法的计算复杂度。
Macro Block (MB) type judging algorithm is proposed based on MB′s space complexity. It reduces effectively the computational complexity of the video compression.
本文算法利用亮度DCTDC值、宏块类型和运动向量来确定MPEG压缩视频中运动活动和视觉内容变化。
The proposed method determines the motion activity and visual content change of the MPEG compressed video by using the luminance DCT DC value, macroblock type and motion vector.
该算法只需要通过直接抽取MPEG视频流中的B帧、P帧中的宏块类型信息，并对其进行计算就可以检测出视频中存在的镜头边界，从而对场景变换进行精确定位。
The proposed method can detect scene boundaries through using various macroblock type of B-frame and P-frame in MPEG video flow in order to realize accurate scene change positioning.
该算法只需要通过直接抽取MPEG视频流中的B帧、P帧中的宏块类型信息，并对其进行计算就可以检测出视频中存在的镜头边界，从而对场景变换进行精确定位。
The proposed method can detect scene boundaries through using various macroblock type of B-frame and P-frame in MPEG video flow in order to realize accurate scene change positioning.
应用推荐