End-to-end video compression for surveillance and conference videos

被引:0
作者
Shenhao Wang
Yu Zhao
Han Gao
Mao Ye
Shuai Li
机构
[1] University of Electronic Science and Technology of China,School of Physics
[2] University of Electronic Science and Technology of China,School of Computer Science and Engineering
[3] Shandong University,School of Information Communication
来源
Multimedia Tools and Applications | 2022年 / 81卷
关键词
Deep learning; End-to-end video compression; Surveillance and conference videos; Online update;
D O I
暂无
中图分类号
学科分类号
摘要
The storage and transmission tasks of surveillance and conference videos are an important branch of video compression. Since surveillance and conference videos have strong inter-frame correlation, considerable continuity at the image level and motion level between the consecutive frames exists. However, traditional video codec networks cannot fully use the characteristics of surveillance and conference videos during compression. Therefore, based on the DVC video codec framework, we propose a “MV residual + MV optimization” coding strategy for surveillance and conference videos to further reduce the compression rate and improve the quality of compressed video frames. During the testing stage, the online update strategy is promoted, which adapts the network’s parameters to different surveillance and conference videos. Our contribution is to propose an optical flow residual coding method for videos with strong inter-frame correlation, implement optical flow optimization at decoding end and online update strategy at the encoding end. Experiments show that our method can outperform DVC framework, especially on CUHK Square surveillance video with 1.2dB improvement.
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页码:42713 / 42730
页数:17
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