Video texture analysis based on HEVC encoding statistics
Video texture analysis based on HEVC encoding statistics
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DOI：
10.1109/pcs.2016.7906312
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Mariana Afonso;Angeliki V. Katsenou;Fan Zhang;D. Agrafiotis;D. Bull
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文献类型：
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作者：
Mariana Afonso;Angeliki V. Katsenou;Fan Zhang;D. Agrafiotis;D. Bull
在本文中，基于从 HEVC HM 参考软件中提取的编码统计数据，对不同视频纹理属性进行了广泛的研究。模式选择、分区、运动矢量和比特率分配都是从编码器获得的统计数据。在本研究中，提出了一个新的同质静态和动态视频纹理数据集 HomTex。对结果的全面调查揭示了动态纹理内编码统计数据的显着变化，表明该类别应进一步分为两个相关的子类别：连续动态纹理和离散动态纹理。这种情况得到了对提取的统计数据的无监督学习方法的支持。最后，根据所获得的结果，提出了视频纹理编码的一些改进建议。
In this paper, an extensive study of different video texture properties based on encoding statistics extracted from the HEVC HM reference software is presented. Mode selection, partitioning, motion vectors and bitrate allocation are among the statistics obtained from the encoder. For this study, a new dataset of homogeneous static and dynamic video textures, HomTex, is proposed. A comprehensive investigation of the results reveals a significant variability of coding statistics within dynamic textures, suggesting that this category should be further split into two relevant subcategories, continuous dynamic textures and discrete dynamic textures. This case is supported by an unsupervised learning approach on the statistics extracted. Finally, following the results obtained, some suggestions of improvements in video texture coding are presented.