A Double Background Based Coding Scheme for Surveillance Videos
Haoran Li, Wenpeng Ding, Yunhui Shi, Wenbin Yin · 2018
The rapid growth of surveillance videos poses a huge challenge for video coding technology. To make the best use of the special characteristics of surveillance videos, the prediction and coding methods with high-quality background picture (BG-picture) has been proposed. However, a large number of frames are always required for training in traditional background modeling methods, and too many bits are spent to encode the BG-picture. Therefore, we propose a double background based coding scheme for surveillance videos, in which two background frames are generated from the reconstructed frames and original frames respectively. Then residual frame between the original background and the reconstructed background is encoded to reduce the bit cost of the BG-picture. The experiments on surveillance videos shows that compared with HM14.0, the proposed method can achieve about 17 percent bit rate saving on average. Up to 40 percent bit rate saving can be observed on surveillance videos.