AI

Video Description Length Guided Constant Quality Video Coding with Bitrate Constraint

Abstract

In this paper, we propose a new video encoding strategy - Video description length guided Constant Quality video coding with Bitrate Constraint (V-CQBC), for large scale video transcoding systems of video charing websites with varying unknown video contents. It provides smooth quality and saves bitrate and computation for transcoding millions of videos in both real time and batch mode. The new encoding strategy is based on the average bitrate-quality regression model and adapt to the encoded videos. Furthermore, three types of video description length (VDL), describing the video overall, spatial and temporal content complexity, are proposed to guide video coding. Experimental results show that the proposed coding strategy with saved computation could achieve better or similar RD performance than other coding strategies.