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首页> 外文会议>International Conference on Cloud Computing and Security >Learning Based Fast H.264/AVC to HEVC INTRA Video Transcoding for Cloud Media Computing
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Learning Based Fast H.264/AVC to HEVC INTRA Video Transcoding for Cloud Media Computing

机译：基于学习的快速H.264 / AVC到HEVC INTRA视频转码，用于云媒体计算

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摘要

Cloud video transcoding enable to convert the video standards and properties from one to another so as to adapt to different user end devices and network capacity, especially in sharing massive video contents in cloud environment. High Efficiency Video Coding (HEVC) and H.264/Advanced Video Coding are two recent high performance video coding standards that are widely used and co-existing in video industry. Video transcoding is desirable to bridge the standard gap. To effectively transcode video stream from H.264/AVC to HEVC for higher compression efficiency and meanwhile maintaining low computational complexity, a learning based fast H.264/AVC to HEVC transcoder is proposed for cloud media computing. We firstly analyze the correlation of block partition sizes between these two standards and then present a fast Coding Unit (CU) decision algorithm, in which three levels of binary classifiers are used to predict different CU sizes in HEVC intra coding and the optimal parameters are determined by statistical experiments. The experimental results show that the proposed transcoder achieves 44.3% time saving on average with only negligible quality degradation when compared with the original cascaded transcoder and is also superior than the state-of-the-art benchmarks in terms of complexity reduction and rate-distortion performance.
机译：云视频转码能够将视频标准和属性彼此转换，以适应不同的用户终端设备和网络容量，尤其是在云环境中共享大量视频内容时。高效视频编码（HEVC）和H.264 /高级视频编码是视频行业中广泛使用并共存的两个最新高性能视频编码标准。希望进行视频转码以弥合标准差距。为了有效地将视频流从H.264 / AVC转换为HEVC，以实现更高的压缩效率，同时又保持较低的计算复杂度，提出了一种基于学习的快速H.264 / AVC到HEVC转码器，用于云媒体计算。我们首先分析这两个标准之间的块分区大小的相关性，然后提出一种快速编码单元（CU）决策算法，其中使用三级二进制分类器来预测HEVC帧内编码中的不同CU大小，并确定最佳参数通过统计实验。实验结果表明，与原始的级联转码器相比，所提出的转码器平均可节省44.3％的时间，而质量下降可忽略不计，并且在降低复杂度和速率失真方面也优于最新基准表现。

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