中文摘要：

为了降低降尺寸视频转码的运算复杂度，提出一种基于支持向量机的快速转码模式决策算法。首先从输入的高分辨率视频码流中的编码信息里选取多维特征向量，并选择与模式特征匹配的核函数训练SVM分类器模型，建立高分辨率视频编码信息与降尺寸视频宏块编码模式之间的相关性；然后构建分层式SVM分类器对降尺寸视频中宏块模式进行阶梯式预测分类，以此缩减预测模式数量，提高转码效率。实验结果证明，算法可以节省高达67．31％的运算量，同时保证转码后视频的高质量。

英文摘要：

An efficient mode decision scheme for down-sizing video transcoding in H.264 using support vector machines （SVM） was proposed. In order to reduce the high computational complexity of using conventional mode decision in the H.264 re-encoder, the proposed scheme used SVM to exploit the correlation between coding information extracted from the input high-resolution bit-stream and the coding modes of macro-blocks in down-sized video frames. The key tech- niques of training and predicting SVM including feature vector and kernel function were studied and then the SVM model was trained. After the hierarchical SVM classifier, improbable modes were eliminated and only a small number of candidate modes were carded out using the RDO operations. Hence, remarkable computing time could be saved, up to 67.31%, while maintaining nearly the same quality of the transcoded pictures.