Prescient R-D optimized packet dependency management for low-latency video streaming

An improved, prescient, scheme to deliver preencoded video streams at very low latency is presented. We dynamically manage the prediction dependency for a group of packets using a rate-distortion (R-D) optimization framework that adapts to the channel, so that the expected end-to-end distortion is minimized under a given rate constraint. In our system, the R-D characteristics of each prediction mode are precomputed at compression time and stored in an R-D preamble along with the multiple compressed versions of the stream. The distortion in the preamble is estimated using an accurate loss-distortion model, and the optimal prediction modes are computed with an iterative descent algorithm. Complexity is reduced at streaming time by using the preamble to compute the optimal modes instead of actually compressing the video. Experiments demonstrate that the proposed prescient scheme provides significant performance gains over simple intra-insertion, and consistent bitrate savings compared to the greedy scheme.