A cloud-based encoding pipeline which generates streams for video-on-demand distribution typically processes a wide diversity of content that exhibit varying signal characteristics. To produce the best quality video streams, the system needs to adapt the encoding to each piece of content, in an automated and scalable way. In this paper, we describe two algorithm optimizations for a distributed cloud-based encoding pipeline: (i) per-title complexity analysis for bitrate-resolution selection; and (ii) per-chunk bitrate control for consistent-quality encoding. These improvements result in a number of advantages over a simple "one-size-fits-all" encoding system, including more efficient bandwidth usage and more consistent video quality.
展开▼
