Surveillance video coding with dynamic textural background detection

Kun Yang, Fangdong Chen, Dong Liu, Zhibo Chen, Weiping Li

Abstract: Texture scenes like flickering flames, swaying tree branches, flowing water exhibit a complex stochastic motion character. It presents a great challenge to compress these dynamic texture efficiently even with the state-of-the-art video encoder. Furthermore, these contents only contain a little helpful information in surveillance analysis. In this paper, we propose an approach for compressing the dynamic textures in the surveillance video. In the proposed scheme, the dynamic texture contents are detected by the histogram of motion direction (HMD) algorithm, and then removed at the encoder, these dynamic texture contents will be restored at the decoder directly. Objective and subjective results are presented, demonstrating that the proposed approach provides about 8.7% bitrate saving with visually plausible dynamic textures in comparison with High Efficiency Video Coding (HEVC).